The KENYA INSTITUTE for PUBLIC POLICY RESEARCH and ANALYSIS Socio-Economic Status of Garissa County with COVID-19 Eldah Onsomu, Rose Ngugi, Evelyne Kihiu, Mutuku Muleli, James Gachanja, Rogers Musamali, Paul Lutta, Daniel Omanyo, Hellen Chemnyongoi, Shadrack Mwatu, Nahashon Mwongera, Paul Odhiambo, Beverly Musili, Violet Nyabaro, Japheth Kathenge, Haron Ngeno and Elton Khaemba KENYA INSTITUTE FOR PUBLIC POLICY RESEARCH AND ANALYSIS (KIPPRA) The KENYA INSTITUTE for PUBLIC POLICY RESEARCH and ANALYSIS Thinking Policy Together Socio-Economic Status of Garissa County with COVID-19 Eldah Onsomu, Rose Ngugi, Evelyne Kihiu, Mutuku Muleli, James Gachanja, Rogers Musamali, Paul Lutta, Daniel Omanyo, Hellen Chemnyongoi, Shadrack Mwatu, Nahashon Mwongera, Paul Odhiambo, Beverly Musili, Violet Nyabaro, Japheth Kathenge, Haron Ngeno and Elton Khaemba Kenya Institute for Public Policy Research and Analysis 2022 Socio-economic status of Garissa County with COVID-19 KIPPRA in Brief The Kenya Institute for Public Policy Research and Analysis (KIPPRA) is an autonomous institute whose primary mission is to conduct public policy research leading to policy advice. KIPPRA’s mission is to produce consistently high-quality analysis of key issues of public policy and to contribute to the achievement of national long-term development objectives by positively influencing the decision-making process. These goals are met through effective dissemination of recommendations resulting from analysis and by training policy analysts in the public sector. KIPPRA therefore produces a body of well-researched and documented information on public policy, and in the process assists in formulating long-term strategic perspectives. KIPPRA serves as a centralized source from which the Government and the private sector may obtain information and advice on public policy issues. Published 2022 © Kenya Institute for Public Policy Research and Analysis Bishops Garden Towers, Bishops Road PO Box 56445-00200 Nairobi, Kenya tel: +254 20 2719933/4; fax: +254 20 2719951 email: admin@kippra.or.ke website: http://www.kippra.org The KIPPRA Special Reports Series deals with specific issues that are of policy concern. The reports provide in-depth survey results and/or analysis of policy issues. They are meant to help policy analysts in their research work and assist policy makers in evaluating various policy options. Deliberate effort is made to simplify the presentation in the reports so that issues discussed can be easily grasped by a wide audience. KIPPRA appreciates any comments and suggestions arising from this report. ii Table of Contents List of Acronyms ................................................................................................................... ix Acknowledgements ................................................................................................................ x Executive Summary .............................................................................................................. xi Fiscal policy, planning and budgeting ......................................................................... xi Agriculture, Livestock and Fisheries ............................................................................ xi Water Sanitation and Hygiene (WASH) ...................................................................... xii Manufacturing, Trade and MSMEs ............................................................................ xii Infrastructure, housing and urban development ...................................................... xiii Tourism ......................................................................................................................xiii Health .......................................................................................................................... xiv Education and training .............................................................................................. xiv Social protection ...........................................................................................................xv Human resources .........................................................................................................xv 1. Introduction and Structure of County Economy .........................1 1.1 Introduction.....................................................................................................1 1.2 Level of socioeconomic deprivations ............................................................. 3 1.3 Structure of Garissa County Economy ........................................................... 4 1.4 COVID-19 caseload and implications of mobility restrictions ..................... 4 2. Socio-economic Effects of COVID-19 ...........................................7 2.1 Fiscal policy, planning and budgeting .......................................................... 7 2.2 County Expenditure Analysis ....................................................................... 10 2.3 Conclusions....................................................................................................15 3. Agriculture, Livestock and Fisheries ........................................16 3.1 Characteristics of the sector ..........................................................................16 3.2 Agri-Food Challenges in COVID-19 ............................................................20 3.3 Agri-Food Constraints Faced in the County .............................................. 25 3.4 Opportunities of COVID-19 in agriculture sector ........................................ 26 iii Socio-economic status of Garissa County with COVID-19 3.5 Emerging Issues .......................................................................................... 27 3.6 Recommendations ........................................................................................ 27 4. Water, Sanitation and Hygiene. ................................................ 29 4.1 Characteristics of the sector ........................................................................ 29 4.2 Opportunities of COVID-19 in WASH ......................................................... 37 4.3 Emerging Issues .......................................................................................... 37 4.4 Recommendations ........................................................................................ 37 5. Manufacturing, Trade and MSMEs ........................................... 39 5.1 Characteristics of the sector ......................................................................... 39 5.2 Manufacturing sector .................................................................................. 39 5.3 Micro, Small and Medium Enterprises (MSMEs) ....................................... 46 5.4 Effects of COVID-19 on household non-farm and farm businesses ............ 50 5.5 Labour dynamics ...........................................................................................51 5.6 Key Messages: ............................................................................................... 52 5.7 Opportunities of COVID-19 in Industrial Recovery and Growth ................ 52 5.8 Recommendations ........................................................................................ 52 6. Infrastructure ...........................................................................54 6.1 Transport and roads ..................................................................................... 54 6.2 Opportunities of COVID-19 in the Transport sector ................................... 57 6.3 Information and Communication Technology ............................................ 58 6.4 Opportunities of COVID-19 in ICT ...............................................................61 7. Housing and Urban Development ............................................ 62 7.1 Characteristics of the sector ......................................................................... 62 7.2 Opportunities in housing and urban development ..................................... 64 7.3 Emerging Issues ........................................................................................... 65 7.4 Recommendations ........................................................................................ 65 8. Tourism ................................................................................... 66 8.1 Characteristic of the sector ...........................................................................66 8.2 Opportunities of COVID-19 in Tourism Sector ........................................... 66 8.3 Emerging Issues ..........................................................................................66 iv 8.4 Recommendations ........................................................................................66 9. Health ..................................................................................... 68 9.1 Characteristics of the sector .........................................................................68 9.2 Effects of COVID-19 ..................................................................................... 72 9.3 Opportunities of COVID-19 in Health Sector .............................................. 75 9.4 Emerging Issues .......................................................................................... 76 9.5 Recommendations ........................................................................................ 76 10. Education and Training .............................................................78 10.1 Characteristics of the sector ......................................................................... 78 10.2 Opportunities of COVID-19 in Education and Training ..............................83 10.3 Emerging Issues ...........................................................................................84 10.4 Recommendations ........................................................................................84 11. Social Protection ..................................................................... 86 11.1 Characteristics of the sector .........................................................................86 11.2 Opportunities of COVID-19 in social protection ........................................90 11.3 Emerging Issues ..........................................................................................90 11.4 Recommendations ........................................................................................90 12. Human Resources ................................................................... 92 12.1 Characteristics of the Sector ......................................................................... 92 12.2 Effects of COVID-19 .....................................................................................92 12.3 Opportunities of COVID-19 in human resource sector ............................... 94 12.4 Emerging issues ............................................................................................ 95 12.5 Recommendations ........................................................................................ 95 13. Conclusion and Key Recommendations ....................................97 13.1 Conclusion .................................................................................................... 97 13.2 Key Recommendations ................................................................................99 v Socio-economic status of Garissa County with COVID-19 LIST OF TABLES Table 1.1:Development indicators in Garissa County ................................................................................... 1 Table 1.2: Population distribution for selected age groups in the County (2019) .......................................2 Table 1.3: Level of Deprivations for the various indicators for multidimensional poverty in the county 3 Table 1.4: Total COVID-19 cases and mobility stringency— Garissa County .............................................5 Table 2.1: Monthly cash transfers from National Government (Ksh Million) ............................................8 Table 2.2: County departmental/priority spending ................................................................................... 12 Table 3.1: Distribution of Households Practicing Agriculture, Fishing and Irrigation by County and Sub County........................................................................................................................................................... 16 Table 3.2: Area of land Under Farming ...................................................................................................... 17 Table 3.3: Distribution of Households Growing Crops by Type, County and Sub County....................... 18 Table 3.4: Distribution of Households Growing Permanent Crops by Type and County ........................ 18 Table 3.5: Fruits Grown in Garissa ............................................................................................................. 18 Table 3.6: Vegetables Grown in Garissa ..................................................................................................... 19 Table 3.7: Medicinal and Aromatic plants (MAPs) Grown in Garissa ...................................................... 19 Table 3.8: Distribution of Households Rearing Livestock and Fish by County and Sub County ............ 19 Table 5.1: Distribution of Manufacturing firms by gender and size - N (per cent) ................................... 41 Table 5.2: Employment by gender and size for manufacturing firms ....................................................... 41 Table 5.3: Level of innovation by firms in Manufacturing .........................................................................43 Table 5.4: Distribution of MSMEs by gender and size - N (per cent) ........................................................47 Table 5.5: Employment by gender and Size - N (per cent) ........................................................................48 Table 5.6: Level of innovation by MSMEs ..................................................................................................49 Table 7.1: Distribution of Population by Urban Centers by Gender ..........................................................62 Table 9.1: Health provision ..........................................................................................................................68 Table 9.2: Percentage Distribution of the Population that reported Sickness/Injury by Type of Health Provider in the County (per cent) ................................................................................................................69 Table 9.3: Percentage Distribution of the County’s Population with Health Insurance Cover by Type of Health Insurance Provider (per cent) .........................................................................................................70 Table 9.4: Proportion of Children aged 0-59 Months by Place of Delivery (per cent) .............................70 Table 9.5: Proportion of Children aged 0-59 Months Immunized Against Measles ............................... 71 Table 9.6: Health indicators in Garissa County .........................................................................................72 Table 10.1: Gross Attendance Ratio and Net Attendance Ratio by Educational Level in Garissa County 79 Table 10.3: Percentage Distribution of Population aged 15 Years and above by Ability to Read and Write (per cent) ..................................................................................................................................................... 80 Table 10.4: Percentage Distribution of Population by Highest Educational Qualification ...................... 81 Table 10.5: Percentage Distribution of Residents 3 Years and above who had ever Attended School by Highest Level Reached, and Sex for Garissa County (per cent) ................................................................ 81 Table 11.1: The proportion of households by the First Severe Shock in the County .................................86 Table 11.2: The proportion of households that received cash transfers by source, and household headship ...................................................................................................................................................... 88 Table 12.1: Distribution of Population Age 5 Years and above by Activity Status, and Sex in the County 92 vi LIST OF FIGURES Figure 1.1: Structure of the County Economy, 2013-2017 .......................................................................4 Figure 1.2: New COVID-19 cases ..............................................................................................................5 Figure 1.3: Effects of COVID-19 on economic performance ....................................................................5 Figure 2.1: Share of county revenues by source .......................................................................................7 Figure 2.2: Annual Own Source Revenue targets and actual collections ................................................9 Figure 2.3: Quarterly Own Source Revenue collection ..........................................................................10 Figure 2.4: County expenditure analysis ............................................................................................... 11 Figure 2.5:County government expenditure by economic classification (per cent of total county government expenditure ........................................................................................................................12 Figure 2.6: County Approved Expenditure and Absorption rates ........................................................14 Figure 2.7: Profile of county pending bills .............................................................................................14 Figure 3.1: Scale of Operation: per cent of households ......................................................................... 17 Figure 3.2: Agriculture Related Labor Force Participation ................................................................. 20 Figure 3.3: Changes in Hours Worked by in Agriculture Related Occupations ...................................21 Figure 3.4: Limited access to markets to purchase food items ............................................................22 Figure 3.5: Reason for Limited access to markets/ grocery stores .......................................................22 Figure 3.6: Percentage of households experiencing change in food commodity prices ......................22 Figure 3.7: Proportion of households facing large food price shocks ..................................................23 Figure 3.8: per cent Households reporting that the following food items were not readily available in their locality ............................................................................................................................................23 Figure 3.9: Figure 3.10: per cent of households where the following strategies were adopted for at least one day ................................................................................................................................................... 24 Figure 3.11: Percentage of households who experienced the below shocks in the past two weeks the KNBS Wave 2 survey ............................................................................................................................ 24 Figure 4.1: Access to sources of water by households .......................................................................... 30 Figure 4.2: Access to improved and unimproved sources of water by households .............................31 Figure 4.3: Access to safe drinking water by households ......................................................................32 Figure 4.4: Volumes of water used by households in a month ..............................................................32 Figure 4.5: Distance covered by households to and from water sources ............................................33 Figure 4.6: Access and reliability to water sources by households ......................................................34 Figure 4.7: Access to sanitation in Garissa County ................................................................................34 Figure 4.8: Access to improved and unimproved sanitation by households ........................................35 Figure 4.9: Number of households sharing a toilet facility ...................................................................36 Figure 4.10: Access to wash during the COVID-19 period ....................................................................36 Figure 5.1: Sector of operation in manufacturing ..................................................................................39 Figure 5.2:Manufacturing firms by sector and size .............................................................................. 40 Figure 5.3: Location of manufacturing firms by premises ................................................................... 40 Figure 5.4: Distribution of Manufacturing firms by gender and sector ................................................41 Figure 5.5: Education levels of manufacturing firm owners ................................................................ 42 Figure 5.6: Source of markets ............................................................................................................... 42 vii Socio-economic status of Garissa County with COVID-19 Figure 5.7: Source of material inputs .....................................................................................................43 Figure 5.8: Sources of finance ............................................................................................................... 44 Figure 5.9: Recent sources of credit ...................................................................................................... 44 Figure 5.10: Main purpose of credit .......................................................................................................45 Figure 5.11: Constraints faced by manufacturing firms .........................................................................45 Figure 5.12: Distribution of MSMEs by size ......................................................................................... 46 Figure 5.13: Sector of operation by MSMEs ......................................................................................... 46 Figure 5.14: Location of businesses by premises ...................................................................................47 Figure 5.15: Education levels of MSME owners ................................................................................... 48 Figure 5.16: Main constraints faced by MSMEs ................................................................................... 50 Figure 5.17: Effects of COVID-19 on household non-farm and farm businesses .................................. 51 Figure 5.18: Labour dynamics on household non-farm and farm businesses ...................................... 51 Figure 6.1: Main Means of Transport ....................................................................................................54 Figure 6.2: Change in Cost of Main Means of Transport ......................................................................55 Figure 6.3: Change in Travel Patterns ...................................................................................................55 Figure 6.4: Proportion of Residents Whose Service Delivery has been Affected ..................................56 Figure 6.5: Road Condition Mix-Classified Road Network ...................................................................56 Figure 6.6: Per centage Distribution of Conventional Households by Ownership of ICT Assets ........59 Figure 6.7: Reasons for Lack of Internet Connection ............................................................................59 Figure 6.8: Type of Internet Connection .............................................................................................. 60 Figure 6.9: Mobile Money Transfers Subscription and Mobile Money Banking Platform ................. 60 Figure 7.1: Distribution of households Renting/ Provided with the main dwelling unit by Provider 62 Figure 7.2: Proportion of Residents Paying Rent per Terms of Contract .............................................63 Figure 7.3: Has your household paid the rent for April 2020 on the agreed date ................................63 Figure 7.4: Reasons for not Being Able to Pay Rent ............................................................................. 64 Figure 7.5: Measures Taken by Household to Mitigate COVID-19 Effects on Rent ............................ 64 Figure 9.1: COVID-19 Testing, 2020 ......................................................................................................73 Figure 10.1: Access to ICT in Households and Schools (%) .................................................................. 83 Figure 12.1: Effects of COVID-19, 2020 .................................................................................................93 Figure 12.2: Difference between usual hours worked and actual hours worked during COVID-19 period ..................................................................................................................................................... 94 viii List of Acronyms ADPs - Annual Development Plans AFA - Agriculture and Food Authority AI - Artificial Insemination CIDC - Constituency Industrial Development Centres CIDPs - County Integrated Development Plans DSA - Drug and Substance Abuse FAO - Food and Agriculture Organization GBV - Gender Based Violence GCP - Gross County Product GDP - Gross Domestic Product HA - Hectares ICTs - Information Communication Technologies ICU - Intensive Care Unit KCB - Kenya Commercial Bank KDHS - Kenya Demographic Household Survey KNBS - Kenya National Bureau of Statistics KNOCS - Kenya National Occupational Classification Standard LREB - Lake Region Economic Bloc LVSR - Low Volume Sealed Roads M.I.C.E - Meetings Incentives Conferences and Exhibitions MSMEs - Micro Small and Medium Enterprises MT - Metric Tonnes MTPs - Medium Term Plans NGOs - Non-Governmental Organizations OSR - Own Source Revenue PFM - Public Finance Management PPEs - Personal Protective Equipment RAI - Rural Access Index SDGs - Sustainable Development Goals TVET - Technical and Vocational Educational and Training UNICEF - United Nations International Children’s Emergency Fund UN - United Nations WASH - Water Sanitation and Hygiene Socio-economic status of Garissa County with COVID-19 Acknowledgements The development of the County Technical Reports was a combined effort of various departments at the Kenya Institute for Public Policy Research and Analysis (KIPPRA) with support and inputs from the Council of Governors and the 47 Counties. Specifically, the Institute wish to thank KIPPRA’s Executive Director Dr Rose Ngugi for guiding the process. We would also like to thank the entire KIPPRA technical and research team comprising Dr Eldah Onsomu, Dr Evelyne Kihiu, Mutuku Muleli, James Gachanja, Rogers Musamali, Paul Lutta, Daniel Omanyo, Hellen Chemnyongoi, Shadrack Mwatu, Nahashon Mwongera, Paul Odhiambo, Beverly Musili, Japheth Kathenge, Haron Ngeno, Violet Nyabaro, Elton Khaemba and Ephantus Kimani for their tireless contributions to the success of preparing the report. x Executive Summary Fiscal policy, planning and budgeting Garissa county’s total revenues have been increasing steadily over the years growing by 130 per cent from Ksh 4.84 billion in FY 2013/14 to Ksh 11.11 billion in FY 2018/19, being the highest ever. Analysis of county revenues shows that the main source of revenue for the county has been the equitable share from the National Government, which averaged 81.96 per cent of the county’s total revenues from FY 2013/14 to FY 2020/21. Monthly cash transfers from the National Government have always had an increasing trend from January to June over the years. The County receives conditional grants from the National Government and development partners mainly from World Bank, Danish International Development Agency (DANIDA), Sweden and European Union. The OSR to total revenue averaged 1.22 per cent between FY 2013/14 and FY 2020/21, contributing the least amount of County revenues. County expenditure has over the years been rising as the county escalates its efforts in provision of services to its residents. Total county expenditure has grown significantly since FY 2013/14. In FY 2014/15 the county reported Ksh 460.0 million in pending bills. This increased to Ksh 980.1 million in FY 2017/18 with development spending related pending bills accounting for 872.0 per cent of this. In FY 2018/19 pending bills slowed to Ksh 619.6 million before shooting up to Ksh 877.0 million in FY 2019/20. To ensure continued recovery, the county must now move quickly to tackle the problem of pending bills, mobilize more finances from OSR to increase the available revenues for budgetary operations, seek for more funding in form of grants from development partners to cater for the critical development projects in the county and ensure that the ongoing projects are completed before launching new project and clear any pending bills and arrears owed to suppliers. Agriculture, Livestock and Fisheries Livestock production is the predominant economic activity in Garissa County. Key agricultural value chains commodities in the County include maize, bananas, tomatoes, watermelons, beans and onions, mangoes, cattle, sheep, goats, donkeys, camels, poultry production, bee keeping (apiculture). Among the socioeconomic effects on the COVID-19 pandemic on the agri-food sector in the County included negative effects on hours worked by in agriculture related occupations. An additional effect was a slow down on trade and marketing activities due to the restrictions on movements leading to price shocks and shortages of food items. Agricultural productivity in the County is also affected by:- variable and extreme weather events Poor and inadequate infrastructure; water scarcity; low agroprocessing and value addition opportunities; dependence on rainfed agriculture; low access to quality and affordable inputs; low commercialization levels and marketing opportunities; low access to major off-farm services including extension, climate and market information, and credit services; pests and livestock diseases; and farm losses and xi Socio-economic status of Garissa County with COVID-19 post-harvest waste. To successfully build resilience and enhance growth of the agriculture sector, the County will: explore partnerships to develop agro-processing and value addition capacities at the County; expansion of water harvesting projects and sustainable irrigation; scale up conservation agriculture, post-harvest management, plant and keep drought- tolerant crops and livestock breeds; link farmers to diverse product markets; strengthen the County’s institutional capacity in disaster surveillance and management; enhance farmers access to critical agricultural inputs and services and build their technical capacity to act on information obtained; provision of storage and cooling facilities; natural resource management; and strengthen agricultural cooperatives to enhance marketing. Water Sanitation and Hygiene (WASH) Clean water, proper sanitation and good hygiene remains an essential component in protecting human health in times of outbreak of infectious diseases. Frequent and correct hand hygiene has been emphasized by World Health Organization (WHO) as one of the frontline measures to curb transmission of COVID-19. This has placed a higher demand for water use in households, schools, health care facilities, marketplaces, workplaces, and public places. This therefore has necessitated the need for provision of water, sanitation, and hygiene by national and county governments to all. The county has a perennial water shortage problem, despite this, the county is dedicated in providing water to households, though also facing challenges in revenue collections since COVID-19 has resulted into reduced incomes among households and businesses, thus deferring collection of revenue from the water services it provides as well as financial support to water services providers. This in the long run could affect the development of the water and sanitation sector. Additionally, COVID-19 poses health challenges to water and sanitation officers if they get infected, they must be self-isolated, and this may lead to disruption of services. Other constraints to the sector include, drought, water leakages and destruction of water catchment areas. To ensure continuous availability of water, the national and county government should increase water supply in households, institutions, and public places through drilling of boreholes in all the sub-counties. Partner with private sector, donor agencies, local communities, and NGOs to help develop water infrastructure Manufacturing, Trade and MSMEs Manufacturing, Trade and MSMEs is an important sector in Garissa County. However, this sector’s momentum was disrupted by the COVID-19 pandemic as the containment measures associated with COVID-19 pandemic took a heavy toll on the sector. The measures that were taken, such as closure of markets, observance of health protocols in form of social distancing and handwashing served to increase the cost of production and affected access to markets for the produce. In sustaining growth in the Manufacturing, Trade and MSMEs sector, the County will: Establish an emergency rescue package for businesses and traders hard-hit by the effects of COVID-19 in the short term. The emergency Fund, supported by development partners and other stakeholders, will be used to identify and support the most vulnerable businesses and entrepreneurs affected by COVID-19. Related, the County will inject some stimulus to cushion the businesses and traders through affordable credit; waiver of some County taxes, cess, and other charges; COVID-19 has increased xii Executive Summary demand for locally produced goods in the County, and especially Personal Protective Equipment (PPEs), sanitisers, hospital beds and ventilators. It is an opportunity to spur innovation and promote manufacturing and industry development and generation of jobs for the youth; Establishments in the county will adopt to the new pandemic guidelines including rearranging floor plans to allow for social distancing and leverage and exploit its metropolitan areas status (Wajir-Garissa-Mandera) to enhance manufacturing, which is part of the Vision 2030 aspirations Infrastructure, housing and urban development The main means of transport used in the County is walking at 26.32 per cent, followed by bicycle (bodaboda). The paved County Road network covers 6.51 km, while the paved National roads cover 31.37 km. Out of the total paved road network of 37.88 km, 83.95 per cent is in good condition, 10.93 per cent in fair condition and 5.12 per cent in poor condition. The status of ICT access and use in the county is low, especially among households. The perception of that the individual does not need to use the internet, lack of knowledge and skills on internet are the leading reasons that the people of in the County do not have internet connection. Majority of the households (89.5%) did not receive a waiver or relief on payment of rent from the landlord, despite inability to pay due to the pandemic. The housing tenure is predominantly owner occupied at 87.4 per cent, with 12.6 per cent of the households under rental tenure. In addressing the prevailing challenges, the county will Identify a core rural road network for prioritization to improve the rural access index (RAI) from the current 24 per cent with a target to match the national average of 70.0 per cent; Collaborate with the Communications Authority and telecom service providers to utilize the Universal Service Fund as a “last resort” in providing ICT access in remote areas where market forces fail to expand access; and avail appropriate building technology for use by the public in house construction and improvement in every subcounty, that responds to local cultural and environmental circumstances. Tourism The key tourism attractions from Garissa County are wildlife, heritage and culture (rich Somali traditional culture) and hospitality. The proximity of the county to the tourist coastal town of Lamu makes it ideal for linkage through a tourist circuit. The County does not have classified (star-rated) hotels. However, there are 5 major hotels with a bed capacity of 450. The county has 6 wildlife conservation areas namely, Garissa Giraffe sanctuary, Ishaqbin Community Conservancy, Waso Conservancy, Arawale National Reserve, Rahole National Reserve and Boni National Reserve. There is need to enhance the exploitation and utilization of these facilities fully. Tourism contributes 0.4 per cent to overall GCP of Garissa reflecting on the need to prioritize development of the sector. The number of domestic and foreign tourists who visit the tourist sites in the county is not documented. There is need to develop a tourist action plan to enhance exploitation of existing tourism opportunities including desert tourism (camel-back expeditions, camping and dessert rallying). The county government will map all the sites with tourism potential in the county; come up with a tourism sector development master plan and set up a cultural documentation centre; tourism information centre. xiii Socio-economic status of Garissa County with COVID-19 Health In 2019/2020, the number of health facilities in the county were 200 which comprised of 180 primary health facilities and 20 hospitals. This was an improvement from a total of 129 health facilities in the previous year, 2018. The number of beds per 10,000 population is 13 against the WHO recommendation of 30 beds per 10, 000 population. In general, 2.7 per cent of the county population had some form of health insurance cover. The National Hospital Insurance Fund (NHIF) was the leading health insurance provider reported by 89.5 per cent of the population. Employer contributory insurance cover was reported by 15.4 per cent of the population, private non-contributory insurance cover was reported by 0.9 per cent of the population. The county had 2.6 per cent of the children aged 12-23 months were fully immunized against measles at 9 months. Teenage pregnancies, Sexual and Gender Based Violence (SGBV) are some of the health issues affecting the youths in Garissa County. The closure of schools due to COVID-19 has not been any good news, the social impact on the children who are now at home has been huge, the girl child has been affected, this has seen one in ten girls being victims of teenage pregnancies this is alarming. There is an enhanced collaboration within Frontier FCDC counties, which has resulted into training of the health officers and all the frontline staffs. This collaboration has also seen enhanced intercountry screening and testing centralized at the Coast general hospital. In line with the health status in the county, some of the recommendations that need attention include the following: The county should create awareness on availability and importance of free maternity services and address other constraints to access of maternal health services in the county to address risk of contracting COVID-19 in event of visiting any health facility; To reduce high burden of both communicable and non-communicable disease, the county should revamp its Community Health Strategy. This is a community based promotive and preventive health services. To make this more effective, the County should engage Community Health Volunteers (CHVs) and equip them with the relevant resources and skills. Education and training About 80 per cent of public primary schools in Garissa County have been installed with ICT infrastructure and devices under the Digital Literacy Programme (DLP). The infrastructures include learner digital devices (LDD), teacher digital devices (TDD) and the Digital Content Server and Wireless Router (DCSWR). The Gross Attendance Rate (GAR) for pre-primary school was 12.3 per cent while that of primary school and secondary school was 59.1 and 43.9 per cent respectively in 2015/16. The preprimary gross enrolment rate in the county was 12.3 per cent in 2018 and while the net enrolment rate was 4.4 per cent. The closing down of schools has worsened the situation. Cases of Female Genital Mutilation have increased tremendously, including child marriage, defilement, and domestic violence. In collaboration, the county government together with the Anti-FGM Board had beefed community vigilance. There also cases of drug and substance abuse, depression, and school dropout. Several factors are attributed to the number of students declining as the student move from primary to secondary. The county has also low internet access (6.3 percent) which constrain online learning across the County. Furthermore, only 2.6 per cent of the households had access to ICT equipment such as laptops and computers. This made it xiv Executive Summary difficult for the pupils and other students to benefit from national learning programme which had been started by the government. The county will prioritize projects that improve school water, sanitation and hygiene facilities and management in order to reduce future effect of similar or related outbreak while promoting public health in learning institutions, promote remedial/catch up lessons for learners who might have lagged behind also schools to utilize ICT platforms and have a depository of teaching and learning materials that learners could use at their own time and while at home, provide financial or in-kind support, such as school feeding, to help families overcome the increased costs of attending school, also provide psychosocial support to teachers and learners and fight drug and substance abuse among the youths in the county. This can be done through counseling and ensuring that they are not idle especially this period when learning institutions are locked. Social protection The overall poverty rates in the county stand at 66per cent which is higher than the national average of 36.1 per cent. The county’s food poverty levels are at 66per cent and 46 per cent of the total population is multidimensionally poor. The major shock in the county was droughts or floods which affected 41.7 per cent of the households followed by Severe water shortage, dearth of livestock and large rise in price of food which affected 21 percent,12.8 per cent and 11.1 per cent of the households in the county, respectively. Households in the county received various forms of social assistance or transfers or gift either in form of a good, service, financial asset or other asset by an individual, household or institution. Transfers constitute income that the household receives without working for it and augments household income by improving its welfare. Cash transfers include assistance in form of currency or transferable deposits such as cheque and money orders. COVID-19 exposed lack of preparedness among counties in terms of responding to the emergencies such as COVID-19 pandemic. It provided an opportunity to measure how county governments are prepared to handle the devolved functions. COVID-19 pandemic created effects with immediate and long-term economic consequences for children, PWDs, elderly and their families. To strengthen social protection response in face of a similar pandemic, the Garissa County government will conduct mass civic education among the people on COVID-19 prevention measures, how to handle an infected person and avoidance of stigmatization of the affected person, enroll more county residents in welfare programmes such as NHIF which will ensure that they access medical treatment in case of falling sick and give tax exemption for the SMES who have suffered losses in their business as result of diseases outbreak. Human resources Pastoralism, agriculture and trade sub-sectors are the main sources of employment in the county. This population sells livestock, livestock products, vegetables and fruits, through retail and wholesale business operations in the county. The unemployment has increased during the period of COVID-19, according to May 2020 KNBS COVID-19 Survey, 19.9 per cent of the county labour force worked at least for 1 hour for pay; 38.2 per cent had never worked, and 41.9 per cent worked in the informal sector. However, 4.2 per cent of employees did not attend to work due to COVID-19 with other 79.2 per cent of employees xv Socio-economic status of Garissa County with COVID-19 working without any pay. On average, workers in the County lost 13.4 hours per week due to COVID-19. With the loss of jobs in the Small and Medium Enterprises the livelihood of people working in these sectors were directly or indirectly affected, particularly youths as the sector employs most of the young population. In addition, the reduction in operation hours and restriction on movement in and outside Nairobi negatively impacted on the transport sector with many relying on it rendered jobless. The loss of jobs in the matatu and boda- boda industry had directly impacted on the lives of the youth as some residents avoided public means of transport in fear of contracting the virus. The Garissa County government will promote implementation of a stronger labour market interventions and policy reforms that drive employment creation. The County shall deepen technical education, training and skills development; and invest in livestock sector in the County, promote investment and entrepreneurship through provision of loans, the county Government will improve access to finance for small and medium enterprises through lending institutions and formulate measures aimed at encouraging employment creation through corporate social responsibility (CSR), including expanding the national internship programs and promoting Information Technology (IT) enabled jobs. xvi 1. Introduction and Structure of County Economy 1.1 Introduction Garissa County is one of the counties in the Frontier Counties Development Council (FCDC). The county occupies a land area of 44,174.1 km2.The county had an estimated population of 841,352 people of whom 54.5 per cent were male and 45.4 per cent were female (KNBS, 2019) as indicated in table 1.1. Of the population 5,220 (0.7%) were persons with disability. The youth constituted 38.0 per cent of the population of whom 45.0 per cent were female. The County had a population density of 19 persons per km2. About 74.9 per cent of the population live in rural areas of whom 44.6 per cent were female. The elderly population (over 65-year-old) make up 1.7 per cent of the total population of whom 43.5 per cent were female. The population in school going age group (4-22 years) was 57.0 per cent in 2019. In 2015/2016, the overall poverty rate in Garissa County was 66.0 per cent against the national poverty rate of 36.1 per cent. In addition, 45.9 per cent of the population were living in food poverty and 61.0 per cent were living in multidimensional poverty, that means being deprived in several dimensions including health care, nutrition and adequate food, drinking water, sanitation and hygiene, education, knowledge of health and nutrition, housing and standard of living, and access to information. According to KDHS 2014, 15.6 per cent of the children were stunted as compared to the average national level at 26.0 per cent. Table 1.1:Development indicators in Garissa County County National Estimated County Population (KNBS, 2019) 841,353 1.5per cent of the total population Males 458,975 54.5per cent Females 382,344 45.4per cent Intersex 34 0.004per cent Estimated Population Density (km2) 19 82 Persons with disability 0.7per cent 2.2per cent Population living in rural areas (per cent) 74.9per cent 68.8per cent Children (0-14 years) (per cent) 52.7per cent 41.1per cent School going age (4-22 years) (per cent) 57.0per cent 68.7per cent Youth 15-34 years (per cent) 38.0per cent 36.1per cent Labour force (15-64 years) (per cent) 44.5per cent 55.0per cent 1 Socio-economic status of Garissa County with COVID-19 Elderly population (over 65-year-old) 1.7per cent 3.9per cent Number of COVID-19 cases (as of 11th 300 0.89per cent of the September 2020) (MOH); National cases national cases were 35,232 people Poverty (2015/2016) (per cent) 66.0per cent 36.1per cent Food Poverty (2015/2016) (per cent) 45.9per cent 31.9per cent Multidimensional Poverty (2015/2016) (per 66.3per cent 56.1per cent cent) Stunted children (KDHS 2014) 15.6per cent 26.0per cent Gross County Product (Ksh Million) 33,394 0.5 per cent Share to total GDP (2017) Average growth of Nominal GCP/GDP 9.0per cent 15.3 per cent (2013-2017) (per cent) Data Source: KNBS (2019) The age distribution of the county residents as per the 2019 Housing and Population Census is shown in table 1.2. The bulk of the County’s population is in the age group of between 15-34 years comprising of 318,945 individuals. They are followed by persons aged between 6-13 years who are the primary school children comprising of 219,861 of the county population. The under 0-3 age comprise of 82,457 of the county population. This shows that the county has a general youthful population. Table 1.2: Population distribution for selected age groups in the County (2019) Age Group Male Female Total Under 0-3 41,822 40,635 82,457 Preprimary school age (Under 4-5) 29,224 26,832 56,056 Primary School Age (6 -13) 120,360 99,501 219,861 Secondary school age (14-17) 62,322 39,666 101,988 Youth Population (15-34) 176,200 142,745 318,945 Female Reproductive age (15-49) 184,480 184,480 Labour force (15-64) 244,054 199,383 199,383 Aged Population 65+ 8,130 6,252 14,382 Source: KNBS, 2019 2 Introduction and Structure of County Economy 1.2 Level of socioeconomic deprivations In 2015/2016, 2.7 per cent of the population had health insurance cover, 15.9 per cent lived in premises with water, 68.1 per cent lived in their own homes and 40.5 per cent had access to mobile telephone (Table 1.3) and majority of the households (94.1%) had access to toilet facility. Table 1.3: Level of Deprivations for the various indicators for multidimensional poverty in the county Percentage Indicator Details Distribution (per cent) Health care Population with Health Insurance Cover 2.7 Zero (In premises) 15.9 Drinking water (Time taken to fetch) less than 30 minutes 77.8 30 minutes or longer 5.3 Proportion of households with toilet facility 56.2 Shared Toilet 67.4 Not Shared 32.6 Sanitation and Hygiene Place to wash hands outside toilet facility 6.3 No place to wash hands outside toilet facility 92.4 Education (Population 3 Ever Attended 37.6 years and Above by School Attendance Status) Never Attended 62.2 Knowledge of health and Participated in Community nutrition (children aged 0-59 Nutrition Programmes 26.4 months that participated Did not Participated in in Community Nutrition Community Nutrition 71 Programmes) Programmes Housing and standard of Owner Occupier 68.1 living (house ownership) Pays Rent/ Lease 20.3 Television 15.6 Access to information Radio 52.7 (Population Aged 3 years and above by ICT Equipment and Mobile phone 40.5 Services Used) Computer 0.9 Internet 3.9 Data Source: KIHBS, 2015/16 3 years and Above by School Never Attended Attendance Status) 62.2 Knowledge of health and Participated in Community Nutrition nutrition (children aged 0- Programmes 26.4 59 months that participated in Community Nutrition Did not Participated in Community Programmes) Nutrition Programmes 71 Housing and standard of Owner Occupier 68.1 living (house ownership) Pays Rent/ Lease 20.3 Access to information Television 15.6 (Population Aged 3 years Radio 52.7 and above by ICT Mobile phone 40.5 EqSuoicpiom-eeconntomica sntadtus ofS Gearrvisicsae sCounCtyo wmitph uCtOeVrID-19 0.9 Used) Internet 3.9 Data Source: KIHBS, 2015/16 1.3 Structure of Garissa County Economy 1.2GariSstsrau Ccotunretyo GfrGosasr iCssoaunCtyo uPnrotyduEcct o(nGoCmP)y accounted for 0.5 per cent of total Gross GaDriosmsaesCtiocu PnrtyodGucrot s(sGDCPo)u natsy oPf r2o0d1u7c tas( GreCpPo)rtaecdc oinu nfitgeudref o1r.1.0 T.5hep GerCPc einntcroefasteodt aflroGmr oss DoKmshes 2ti7c,1P8r2o dmuiclltio(nG DinP 2)0a1s3 otof K20sh1 739a,s39r4e pmoirltleiodn inin f2ig0u1r7e re1p.rTesheentGinCgP ainn carnenauseald afvreormagek sh. 27g,1ro8w2tmh irlalioten oifn 92.00 1p3ert oceknsth. .T3h9e, 3a9g4ricmuilltliuorne isnec2t0o1r 7cornetprribesuetendti n4g2.8an pearn nceunatl oafv GerCaPg ewghriloew th ratseerovfic9e.s0, mpearnucefanctt.uTrihneg aagnrdic outlhtuerre insdecutsotrriecso nstercitbourt eshda4re2d.8 copnerstciteunttedo f48G.C0P pwerh cileenst,e r2v.9ic es, mapneur fcaecnttu arinndg 6a.0nd peort cheenrt,i nrdesupsetrciteivseslye.ctor shared constituted 48.0 per cent, 2.9 per cent and 6.0 per cent, respectively. The services sector includes such activities as wholesale and retail trade, transportation Thaendse crovnicsetsrusceticotonr. Aingcrliucdueltsurseu wchasa mctaiviintileys daosmwinhaoteleds balye liavnedstoreckta kileterpaidneg, (tbreaenfs apnodr tdaatiioryn),a nd cobnesetr ukceteiopnin.gA, garnicdu latugrreofowraesstrmya winhlyiled oinmdinuasttreides baynldiv emsatoncukfakcetuerpiinngg i(nbceluedf ea nsdmadlal-irsyc)a,leb ee keeping, and agroforestry while industries and manufacturing include small-scale production ofpcroondsuucmtieorn goof ocdosn.sumer goods. Figure 1.1: Structure of the County Economy, 2013-2017 Figure 1.1: Structure of the County Economy, 2013-2017 a) County Gross Product (2013-2017) b) Sector Contribution as share of GCP (2017) a) County Gross Product (2013-2017) b) Sector Contribution as share of GCP (2017) DaDtaatSao Suorcuer:ceK:N KBNSB(S2 0(21091)9) 1.3 COVID-19 caseload and implications of mobility restrictions As1o.4f MaCrcOh V20I2D0,-1G9ar cisassaeClouandty ahnad izmeropcliacseast.ioHonwse ovef rm, boybAiuligtuys tre20s2t0r,icthtieoCnosu nty had reported 38 COVID-19 cases with mobility stringency of 70.4. The caseload would rise As of March 2020, Garissa County had zero cases. However, by August 2020, the County had reported 38 COVID-19 cases with mobility stringency of 70.4. The caseload would rise to 1,306 by August 2021 with mobility stringency of 56.0. The mobility stringency index is a composite measure rescaled to a value from 0 to 100 (100=strictest) based on nine response mobility indicators. The nine metrics used to calculate the mobility stringency index include school closures, workplace closures, cancellation of public events, restrictions on public gatherings, closure of public transport, stay-at-home requirements, public information campaigns, restrictions on internal movements and international travel controls. An index measure closer to 100 means high incidence or severity of mobility restrictions. The County mobility stringency index implies the severity of the restrictions was moderate. 4 to 1,306 by August 2021 with mobility stringency of 56.0. The mobility Isntrtirnogdeuncctyioinn daenxd iSstraucture of County Economy composite measure rescaled to a value from 0 to 100 (100=strictest) based on nine response mobility indicators. The nine metrics used to calculate the mobility stringency index include school closures, workplace closures, cancellation of public events, restrictions on public gatherings, closure of public transport, stay-at-home requirements, public information Tc ambplaeig n1s.,4r:e sTtriocttioanls ConOinVteIrDna-l 1m9o vceamseentss annddin mternoabtioinlaitl ytr asvterl icnongtreolns.cAyn—in dGexarissa County measure closer to 100 means high incidence or severity of mobility restrictions. The County mDobailtitey stringency index implies the severity of tTheorteastlri cctiaonssewsas moderaMte.obility stringency (0-100) 13th March 2020 0 36.1 Table 1.4: Total COVID-19 cases and mobility stringency— Garissa County 23rd August 2020 38 70.4 Date Total cases Mobility stringency (0-100) 23rd August 2021 1,306 56.0 13th March 2020 0 36.1 D23ardtAau gSuosut 2r0c2e0: Oxford U38niversity 70.4 23rd August 2021 1,306 56.0 New COVID-19 cases in Garissa County were highest between September 2020-December Data Source: Oxford University 2020, March 2021-May 2021, and July 2021-August 2021. During three time-periods, sNpeiwkeCsO ViInD -1n9ewca secsasineGs airinss athCeou nCtyouwnertey hwigheerset bpertweeceendSeedp tebmyb erre2la02x0a-tDieocnem obef r COVID-19 mobility 2020, March 2021-May 2021, and July 2021-August 2021. During three time-periods, spikes rinesnterwicctaiosenssi.n RtheedCuocutnitoy nw eirne tphreec eCdeodubnytyre’sla xnaetiown cofasCeOsV IwD-a1s9 smiombiililtayrrleys trpicrteiocnes.ded by tightening of mReodbucitliiotny rinesthtreicCtoiuonntys’.s new cases was similarly preceded by tightening of mobility restrictions. FFiigguurer1e.2 :1N.2ew: NCOeVwID- 1C9OcaVseIsD-19 cases 80 100 70 90 80 60 70 50 60 40 50 30 40 30 20 20 10 10 0 0 1/1/2020 3/31/2020 6/30/2020 9/30/2020 1/1/2021 3/31/2021 6/30/2021 9/30/2021 New cases Stringency index Data Source: Oxford University DWaortkas pSaoceusrhcaev:e Obxeefnortdhe Umnoisvt erresspiotynsive to COVID-19 mobility restrictions in Garissa County. The sub-sector has sustained growth in the County since mobility restrictions were WvaocartkedspinaOccetso bhera2v0e2 1b.een the most responsive to COVID-19 mobility restrictions in Garissa County. The sub-sector has sustained growth in the County since mobility restrictions were vFaigcuarete1d.3 :inEf fOecctstoobf eCOr V2I0D-2119.on economic performance Figure 1.3: Effects of COVID-19 on economic performance 30 100 20 90 10 80 0 7060 -10 50 -20 40 -30 30 -40 2010 -50 0 Retail & Recreation Grocery & Pharmacy Parks Public Transport Workplaces Residential Stringency index Data Source: Oxford University Data Source: Oxford University The broad objective of the report is to analyze the socioeconomic effects of COVID-19 across sectors and propose interventions for mitigating the effects. The report is organized as follows. Chapter 2 focuses on fiscal policy, planning and budgeting; Chapter 3 focuses on agriculture, livestock and fisheries; chapter 4 focuses on water sanitation and hygiene; chapter 5 focuses on manufacturing, trade and MSEs; chapter 6 focuses on transport and information and communication technology; chapter 7 fo5cuses on urban development; chapter 8 focuses on tourism, chapter 9 focuses on health; chapter 10 focuses on education and training; chapter 11 focuses on social protection; chapter 12 focuses on human resources and chapter 13 concludes the report. 2 Socio economic effects of COVID-19 2.1 Fiscal policy, planning and budgeting County revenues are critical in financing its development projects and recurrent expenditures. Timely and adequate funding aid in successful implementation of the county’s projects. The County’s main revenue sources comprise of the transfers from the National Government, Conditional Grants and its own source revenue (OSR). Percentage change New COVID-19 cases from baseline 1/1/2020 3/31/2020 6/30/2020 9/30/2020 1/1/2021 3/31/2021 6/30/2021 9/30/2021 1/1/2022 COVID-19 Mobility COVID-19 Mobility Stringency Stringency Socio-economic status of Garissa County with COVID-19 The broad objective of the report is to analyze the socioeconomic effects of COVID-19 across sectors and propose interventions for mitigating the effects. The report is organized as follows. Chapter 2 focuses on fiscal policy, planning and budgeting; Chapter 3 focuses on agriculture, livestock and fisheries; chapter 4 focuses on water sanitation and hygiene; chapter 5 focuses on manufacturing, trade and MSEs; chapter 6 focuses on transport and information and communication technology; chapter 7 focuses on urban development; chapter 8 focuses on tourism, chapter 9 focuses on health; chapter 10 focuses on education and training; chapter 11 focuses on social protection; chapter 12 focuses on human resources and chapter 13 concludes the report. 6 2. Socio-economic Effects of COVID-19 2.1 Fiscal policy, planning and budgeting County revenues are critical in financing its development projects and recurrent expenditures. Timely and adequate funding aid in successful implementation of the county’s projects. The County’s main revenue sources comprise of the transfers from the National Government, Conditional Grants and its own source revenue (OSR). 2.1.1 Transfers from National Government Garissa county’s total revenues have been increasing steadily over the years growing by 130 per cent from Ksh 4.84 billion in FY 2013/14 to Ksh 11.11 billion in FY 2018/19, being the highest ever. The county’s total revenue however declined in FY 2019/20 and FY 2020/21 to Ksh 8.77 billion in both years following the adverse effect of COVID-19 pandemic that aTffraencstfeedrs vfraormioNuast iroenvael Gnouvee rsntmreeanmt s. The amount realized in FY 2020/21 was 86.2 per cent oGfa rtishsea caonuntyu’satlo tbaul rdevgeentu easllhoavceatbieoen inocfr eKassinhg s1t0ea.1di8ly omveirlltihoeny,e arns girmowpinrgobvye1m30ent from 80 per cent aptetraceinntefdro minK FshY. 42.8041b9il/lio2n0i.n TFYhe20 i1m3/1p4rotovKesmh.e1n1.t11 bilhighest ever. The county’s total revenue however declined winaFs li osnuipn pFYor2t0e1d8/ 1b9y, being theY 2019/20 and FY 201200/021 ptoer cent remittances of eKqshu.it8a.7b7leb isllihonarien abnotdh iyneacrrsefaoslloew iing ctohne daidtvieornseale fgfercatnotfsC fOrVoImD- 1t9hepa ndaetmioicntahla tgovernment. affected various revenue streams. The amount realized in FY 2020/21 was 86.2 per cent of Athneaalynnsuisa l obfu dcgoeut naltloyc artieovneonfuKessh s1h0.o1w8 sm itllhioan,t atnheim mproavienm esnotufrrocme o80f rpeervecnenute for the county has attained in FY 2019/20. The improvement was supported by 100 percent remittances of beequeinta btlhe esh aerqeuanitdaibnclree asshe ainrceo nfdriotimona tl hgrea nNtsafrtoimonthael nGatoiovnealrgnomverennmte,n wt. hich averaged 81.96 per cent of the county’s total revenues from FY 2013/14 to FY 2020/21 (figure 2.1). The amount of eAqnualiytsaisbolfec osuhnatyrere vtoen tuheses choowusntthyat hthaedm saiimn sioluarrcleyo ifnrecvreenauesefodr bthye c6o6u nptyehra csebneetn from Ksh 4.22 billion the equitable share from the National Government, which averaged 81.96 percent of the tcoo uKntsyh’s 7t.o0ta2l rbeivlelniouens ofrvoemr tFhYe2 s0a13m/1e4 ptoerFiYod2.0 D20u/2r1in(gfig FurYe 22.01)2.0T/h2e1a, mthouen Ct oofunty received 100 per ceeqnuitta oblfe tshhear eantonthueacl obunutdy gheadt saimlliolacrlaytiinocnre,a sseidgnbyifi6c6apnert ciemntpfrroomvKesmh e4.n22t fbriloliomn to96.3 per cent received Ksh 7.02 billion over the same period. During FY 2020/21, the County received 100 per cent ionf tFheY a2nn0u1a9l /bu2d0ge. tTahlloicsa thioing,hsilgingihfictasn tthimep rcoovemmemntitfmromen9t6 .3ofp etrhcee nNt raetcieoivnedali nGFoYvernment to support c2o0u19n/2ty0. oTpheisrhaitgiholinghst sththreoucogmhm titimmeentlyo ffitnhaenNcaitniogna. l Government to support county operations through timely financing. FFiigguurer2e.1 :2S.h1a:r eSohf caorunet yorfev cenouuesnbtyys oruercveenues by source 120.00 100.00 80.00 60.00 40.00 20.00 0.00 2013/14 2014/15 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 Equitable share Own source revenue Conditional grants Balance brought forward Data Source: Office of the Controller of Budget (Various reports) Data Source: Office of the Controller of Budget (Various reports) Monthly cash transfers from the National Government have always had an increasing trend from January to June over the years as shown in table 2.1. A similar trend was observed in 2020 with the transfers growing by 108 per cent from Ksh. 3.53 billion in January to Ksh. 7.34 billion in June. In comparison to 2019, the total amount transferred to Garissa County in March, April, May, and June of 2020 decreased by 5.45 per cent from Ksh. 24.13 billion to Ksh. 22.82 billion. Transfer of more cash in subsequent 7months was key to enable the county to undertake its budgetary operations as well as implement the necessary measures to curb the spread of COVID-19. Table 2.1: Monthly cash transfers from National Government (Ksh Million) Jan Feb Mar Apr May Jun Oct Nov Dec 202 3,972. 4,588. - - - - 1,981. - - Socio-economic status of Garissa County with COVID-19 Monthly cash transfers from the National Government have always had an increasing trend from January to June over the years as shown in table 2.1. A similar trend was observed in 2020 with the transfers growing by 108 per cent from Ksh 3.53 billion in January to Ksh 7.34 billion in June. In comparison to 2019, the total amount transferred to Garissa County in March, April, May, and June of 2020 decreased by 5.45 per cent from Ksh 24.13 billion to Ksh 22.82 billion. Transfer of more cash in subsequent months was key to enable the county to undertake its budgetary operations as well as implement the necessary measures to curb the spread of COVID-19. Table 2.1: Monthly cash transfers from National Government (Ksh Million) Jan Feb Mar Apr May Jun Oct Nov Dec 2021 3,972.05 4,588.10 - - - - 1,981.80 - - 2020 3,526.24 4,358.81 4,358.81 5,560.50 5,560.50 7,335.24 1,763.60 2,587.17 3,199.94 2019 3,314.70 4,597.54 4,608.71 5,324.61 6,469.61 7,728.15 6,469.61 1,915.38 2,723.18 2018 3,035.01 3,065.67 4,186.28 4,816.63 4,858.06 7,161.70 850.07 2,235.57 2,469.07 2017 - - 4,423.69 4,951.46 5,507.08 6,565.02 1,040.77 - - 2016 - - 3,588.87 4,631.26 5,150.66 5,150.66 - - - Data source: Gazette Notice (Various issues) 2.1.2 Conditional grants The County receives conditional grants from the National Government and development partners mainly from World Bank, Danish International Development Agency (DANIDA), Sweden and European Union. Conditional grants continue to be a major source of financing county operations and contributed an average of 8.06 per cent between FY 2013/14 and FY 2020/21 (figure 2.1). In FY 2020/21, the County received Ksh 62.23 million and Ksh 923.79 million from National Government and Development partners respectively. The share of conditional grants to total revenue exhibits a steady trend averaging at 8.06 per cent over the period under review. Notably, the amount has grown by 188 per cent from Ksh 475.03 million in FY 2013/14 to Ksh 1.37 billion in FY 2020/21. To sustain the robust contribution and attract more grants, the County Government need to continue fostering the good relationship with development partners as well as adhering to the conditionalities of the grants. 2.1.3 Own Source Revenue The OSR to total revenue averaged 1.22 per cent between FY 2013/14 and FY 2020/21, contributing the least amount of County revenues (figure 2.1). However, OSR contribution to total revenue has registered significant improvements from 0.74 per cent in FY 2013/14 to 1.16 per cent in FY 2019/20. Going forward, it would be important for the county to strengthen its OSR collection framework as well as policies to sustain the upward trajectory. Analysis of annual County OSR performance shows a fluctuating trend over the years with the highest collection amounting to Ksh 130.7 million in FY 2013/14 and the lowest of Ksh 81.2 million in FY 2016/17 (figure 2.2). Improved performance of OSR collection was registered in FY 2019/20 when the county collected 109.92 million, an increase of 1.6 8 Socio-economic Effects of COVID-19 per cent from Ksh 108.22 million realized in FY 2018/19. The marginal increase indicates some resilience in the County OSR following the disruptions of economic activities due to COVID-19 pandemic. The county has been revising its OSR target downwards from Ksh 700 million in FY 2014/15 to Ksh 150 million in FY 2020/21 (figure 2.2). Based on its revised OSR targets, the ratio of actual OSR versus target OSR indicate that the county is closer to achieving its targets over the years. The performance of actual OSR versus target indicate that the county has registered improvements from achieving 18.67 per cent of its targets in FY 2014/15 to 73.28 per cent in FY 2019/20. Figure 2.2: Annual Own Source Revenue targets and actual collections Figure 2.2: Annual Own Source Revenue targets and actual collections 800.00 80.00 700.00 70.00 600.00 60.00 500.00 50.00 400.00 40.00 300.00 30.00 200.00 20.00 100.00 10.00 0.00 0.00 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21 OSR Target OSR Actual % of OSR against target Data Source: Office of the Controller of Budget (Various reports) Data Source: Office of the Controller of Budget (Various reports) Analysis of the quarterly OSR show that collections in the third quarter have been the Ahnigahleysstisd uorfin tghteh equpaerritoedrluyn dOeSr Rre vsihewowe xtcheaptt fcoorlltehcetiFoYn2s0 i1n4 /t1h5ea nthdirFdY 2q0u1a9r/t2e0r whhaevne itbeen the hdiegchliensetd dsulirgihntlgy t(hfieg upreer2io.3d). During FY 2019/20, OSR collections in the first three quartersexhibit a decreasing trend, h uanvidnegrd reecvreieawse dexbcyep1t7 .f3orp ethrcee nFtYf r2o0m14K/sh15. 2a6n.7d FmYill i2on01in9/t2he0 when it dfeircsltinqueadr tselrigthotlKys h(fi2g2u.1rem 2i.l3lio)n. Dinurthinegt hFiYrd 2q0u1a9rt/e2r.0A, Os SpaRrt cooflltehcetiCoOnsV IiDn- t1h9ec fiornstat itnhmreenet quarters emxheaibsuitr eas ,dtehcerecaosuintgy twraeinvedd, hCaEvSiSngfe edse,carnedasheadd bnyo t17y.e3t pcoelrle cetendt rferovemnu Kesfhro 2m6.b7u sminiellsison in the fipresrtm qitusaartnedr ltaon dKsrhat e2s2.a1f fmecitlilnigont hien tthhierd thqiuradr tqeur acrotlelerc.t iAons spasirgtn oiffic tahnetl yC.OTVheIDc-lo1s9u rceonotfainment markets such as Dagahley market also affected revenue streams. For instance, the daily mCoeuansutyrerse,v ethnuee cofruonmtyt hweamivaerdk eCt EbSefSo rfeeetsh,e apnadn dheamdi cnowta yseat pcporollxeicmtaetde lryevKeshn.u6e0 f0r,o0m00 .business pHeorwmeivtesr ,anfodll olawnindg rtahteeso nasffeet cotfintghe thpea ntdheimrdic q, uthaertreerv ecnoulleecratinognesd sbigetnwiefiecnanKtslhy.. T30h,e0 0c0losure of manadrkKesths. s8u0c,0h0 0asp eDradgaayh. lTehye mOSaRrkceotl leaclstio nasffdeucrtinegd trheevfeonuurteh sqturaeratemr sw. aFsorro binussttaangacien,s tthe daily Cthoeunlotyw reexvpeencutaet iofrnos.mT htheec mouanrtykerte mbeafinoerde trehseil ipenatndanedmmica wnaagse daptporocoxlilemctatKeslhy. K3s8h.5 6400,000. million in the fourth quarter, the highest amount compared to the first three quarters of FY H2o01w9e/v20e.r,D fuorlilnogwFinYg2 t0h2e0 /o2n1,seqtu aorft etrhlye OpSaRndceomlleicct,i otnhse rreemvaeinneude hriagnhgeexdc ebpettwduereinng Kthshe 30,000 asnedco Kndshq 8u0ar,t0e0r.0 Tpheer dpaeryf.o Trmhaen OceSRsh coowlletchtaitonthse duCroiunngt ythre mfoauinrethd qreusailrietenrt wduarsi nrgobtuhset against thCOe VlIoDw-1 9exppaencdteamtiiocnpse.r iTodhee vceonuanstyth reeCmoauinntreyd erxepseirliieenncte danlodw mecaonnaogmeicd atcot ivcitoiellse.cWt iKthsh 38.54 mthiellioimproved economic activities across the Country, the OSR collectmaintanin inth tehuep wfoaurdrtthra qjeucatorrtye.r, the highest amount compared to t ihone fiisrsetx tpherceteed qtuoarters of FY 2019/20. During FY 2020/21, quarterly OSR collections remained high except during thFieg usreec2o.n3d: Qquuaartretrelyr. OTwhne SpoeurrfcoerRmeavenncuee schoollwec ttiohnat the County remained resilient during the COVID-19 pandemic period even as the Country experienced low economic activities. With the improved economic activities across the Country, the OSR collection is expected to maintain the upward trajectory. 9 Amount (Ksh Million) Percentage Socio-economic status of Garissa County with COVID-19 Figure 2.3: Quarterly Own Source Revenue collection 45.00 40.00 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21 1st Quarter 2nd Quarter 3rd Quarter 4thQuarter Data Source: Office of the Controller of Budget (Various reports) Data Source: Office of the Controller of Budget (Various reports) County expenditure analysis 2E.c2on omCicoaundnptoyli tEicaxl pcreisens,dniatturaled Aisanstaerlsy(suicsh as droughts and flooding), security challenges and health crisis (such as the COVID-19 pandemic) highlight the consequential Ericsokns oamndic uanndder lpyoinlgitivcualln ecrraisbeilsit,i ensaitnurnaalt idoinsaalsatenrds c(osuuncthy alesv delrobuugdhgetsta arynda nfldoopdlainnngin),g security system. These can substantially affect public resources and in cases of weaker planning cshyasltleemnsgtehse aynmda hyeimalptahc tcrthiseisn a(stuurceha ansd tlehvee Cl oOf VseIrDvi-c1e9d pealivnedryemtoicth)e hcigitihzeling.ht the consequential risks and underlying vulnerabilities in national and county level budgetary and planning sTyhseteUmN. STuhsetasien acbalne DsuevbesltoapnmteianltlyG oaafflsec(tS DpGusb)liecm rpehsaosuizreceths eapnrdo diunc tcivaeserso leofo wf teaargkeetre dplanning saynsdtesmtrsa ttehgic county level expenditure. The 2014 UN Secretary General's Synthesis Reporton the Susetayi nmabalye imDepvaeclotp tmheen nt aGtuoarels a(nSdD Glesv)esl toatfe sserthvaicte“ dmealnivyeroyf ttoh ethinev ceisttimzeenn.t s to Tahchei eUvNe tShuesstuasitnaainbalbel eDdeevveellooppmmeennttg Goaolsalws i(llStDakGesp)l aecme pathtahseizseu bthnaet ipornoadl luecvteilvaen rdoblee olefd targeted by local authorities”1. It is at the counties that economic activity takes place and when asnpden sdtirnagtepgriiocr ictioeusnatnyd leexveeclu etxiopneanrdeidtuornee. jTushter i2g0ht14th UenNt hSeeccoreutnatyrya nGdencoeurnatlr’ys Swyilnl btheesseits Report otno tthheed Sesuirsetdaidneavbelleop Dmevnet ltorapjmecetonrty .Goals (SDGs) states that “many of the investments to achieve the sustainable development goals will take place at the subnational level and be leDde sbpyit elotchaelir acuotnhsotrraiitnieeds”f1i.s Icta lisa uatto tnhoem cyo(usuncthieas sthinaatb eilictyontoomboicrr oawctifvuintdys t)aakneds rpellaatcieve alynd when small budgets, the county government has a key role to play in promoting growth as sepsepnodusinedg pinriotrhietieKse annyad eCxoencsutittuiotinon a.reT hdios nies jupastrt irciuglhartl ythtehne thcaes ceouwnitthy adnevde lcoopumnetnrty will be sextp teon tdhiteu rdee, swirheicdh disevweitlhoipnmtheenats tsriganj ecdtorermy.it of county as per the PFM Act of 2012 and is key to the county’s future growth prospects given several decades of underinvestment which Dheasvpeictoen tshtreaiirn ceodnpsrtordauicnteivde ficaspcaacl iatyuitnonthoemloyc a(sl ueccohn aosm iyn.ability to borrow funds) and relatively small budgets, the county government has a key role to play in promoting growth as eTsrpeonudsseda nidnp rtohfei leKoefncyoau nCtoyngsotivtuertniomne. nTtheixsp eisn dpiaturtriecsularly the case with development County expenditure has over the years been rising as the county escalates its efforts in epxrpoevinsidointuorfes,e wrvhiciecsh tios iwtsitrhesinid etnhtes .aTsostiaglnceodu nrteymeixtp oefn dciotuurnetyh aassg proewr nthseig PniFfiMcan Atlcyts oinfc 2e012 and isF Yke2y0 1t3o/ 1t4h.e Wcoithuntthye’si mfuptleumr e ngtraotiwontho fptrhoespfiersct sf ugllivyeena rsecovuenratyl dbuedcgaedtesin oFfY u2n0d1e3r/i1n4v,estment wahctiucahl hexapveen cdoitnursetrianintheedc poruondtyuicntcirveea sceadpafrcoimty Kinsh t.h2e, 1l6o9c.a4l mecilolinonomtoyK. sh. 8,464.4 million in 2020/21 (Figure 2.4). Cumulatively the county has spent a total of Ksh 54.8 billion between FY 2013/14 and FY 2020/21. This comprises of a cumulative Ksh. 39.1 billion and Ksh 15.7 billion on recurrent and development expenditures representing 71.4 per cent and 1 UN General Assembly (2014), p. 22, par. 94. 1 UN General Assembly (2014), p. 22, par. 94. 10 Amount (Ksh Million) Socio-economic Effects of COVID-19 2.2.1 Trends and profile of county government expenditures County expenditure has over the years been rising as the county escalates its efforts in provision of services to its residents. Total county expenditure has grown significantly since FY 2013/14. With the implementation of the first full year county budget in FY 2013/14, actual expenditure in the county increased from Ksh 2,169.4 million to Ksh 8,464.4 million in 2020/21 (Figure 2.4). Cumulatively the county has spent a total of Ksh 54.8 billion between FY 2013/14 and FY 2020/21. This comprises of a cumulative Ksh 39.1 billion and Ksh 15.7 billion on recurrent and development expenditures representing 71.4 per cent and 28.6 per cent of the cumulative recurrent and development expenditure respectively. This s2i8g..n6aplse rrthcaetn ttthoeffretth ies cau mgruelalattteiivre orrpepcourrrrtreunnttitayn tdo dpeuvsehllo pdmeveenltot pemxpeenntd iiettuxrpreenrredsiptuercettii vheillgy.h. eTrh iaisnd siignalls tthatt ttherre iis a grreatterr opporrttuniitty tto push devellopmentt expendiitturre hiigherr and ssuuppppoorrrttt ddeeeeppeenniininggo offfc acappiittiatllasl psepnedniindginiign ittnh ethceo ucnotutyn..ty. Figure 2.4: county expenditure analysis Fiigurre 2..4:: countty expendiitturre anallysiis FFiigiguurree 22.4..4(a()a:) :T: renTdresn idns actiiunal aagcgtrueagllateF iigFuirgeur2e ..24.4( b(b))::: TTrreennddss iinin aactcutaula llperp cearpita aegxgpreengdaitteureexpendiiture capexiitpaeenxdpiteunrediiture 10,,000 9,,000 1144,,443300 8,,000 1100,,550066 ..22 ..99 1111,,443333 1100,,006600 7,,000 1100,,558866 ..11 ..55 6,,000 1100,,444433..88 99,,996666....66 5,,000 55 4,,000 3,,000 2,,000 33,,448811.. 1,,000 88 0 Reccurrrrentt Devellopmentt Tottall DDaatttaa SSoouurrrcece:::O Offffffiiiceceo fof ftt hteheC Conottnrrotrlllloelrrleorff oBfu dBguedttget CCoonnssiiissttteenntttw wiitiththt tthheen noommiininalal gl grrorwowtththiin ina cattcutaullacl ocuonuttnyteyx epxepnedniitdtuirrteusr,,essp, espnedniindginogn oanp ae prrecra cpaiittpaita bbaassiiiss hhaass sshhoowwnn uuppwwaarrrddg grrroowwtththo ovveerrrtt htheep peerriiroido..d.I nInF YFY2 021031/31/41,,4p, eprrecra cpaiipttaitsap sepnedniindginiing ittnh ethe countty was aboutt Ksh.. 3,,481..8 comparred Ksh.. 14,,430..2 iin FY 2018/19 and Ksh 10,,060..5 iin cFoYu2n0t2y0 w/2a1s.. aTbhoeuat vKesrrahg 3e,4p8er1r.c8a pcoiittma sppaerneddi inKgshb e1tt4w,e4e3n0.F2Y in20 F1Y3 /21041a8n/d19F Yan2d0 2K0s/h21 10st,to0o6d0.a5tt in FKsYh 2..0102,0,1/1231..7. .T. he average per capita spending between FY 2013/14 and FY 2020/21 stood at Ksh 10,113.7. Utiilliizatiion of publliic resources iin the county A2n.2al.ly2s iis Uoffteilxipzeantdiioittunrr eosf bpyuebcolinco rmeiicsoclulasrsciifefiicsa ittniio nthaen dcobyundetpyarrttmentts (spendiing prriiorriittiies) rreveall iintterresttiing iinsiightts.. Itt iis eviidentt tthatt siince iincepttiion off devolluttiion,, tthe countty Agonvaelryrnsmise nottf perrxiioprreiittniizdeidtunreasrrr robwyii ngecotthneomecico ncolmasiicsifiacnadtiosonc iiaallnidin ffrrbays ttrrduectptuarrretmgaepnst.s. M(supcehndofifng pgorivoerrrintimese)n trtedveevaell loinptmeerenstttienxgp einndsiiitgtuhrrtess. Ihta sis beeveindednotm thiinaatn sttiniincep rironvcieispiiotnioonff ohfe daellttvhosluetrrivoiicne,s t,,he publliic worrks,, educattiion,, agrriiculltturre,, as wellll as ttrrade and iindusttrry.. county government prioritized narrowing the economic and social infrastructure gaps. Much of government development expenditures has been dominant in provision of health services, public works, education, agriculture, as well as trade and industry. 11 AAmmoouunntt ((KKsshh MMiilllliioonn)) 22001133/ 2 /2 10 10 441144/ 22 /1 0 10 51 5155/ 2 /2 10 10 661166/ 2 /2 1100 71 7177 2 / / 2 10 10 81 8188 2 / / 2 1100 91 9199/ 22 /2 0 20 02 0200//2211 AAmmoouunntt ((KKsshh)) 22001133//11 22 44001144//11 22 55001155//11 22 66001166//11 22 77001177//11 22 88001188//11 22 99001199//22 22 00002200//2211 Socio-economic status of Garissa County with COVID-19 Figure 2.5:County government expenditure by economic classification (per cent of total cFouignutyreg o2v.e5rn:Cmoeunnt etyxp geondvieturrnement expenditure by economic classification (per cent of total county government expenditure 100% 22.4 15.5 24.0 21.5 80% 44.3 39.7 34.3 26.4 29.4 35.2 21.460% 24.0 21.9 25.6 27.0 40% 33.8 20% 48.2 49.3 49.6 54.1 57.1 34.7 38.7 21.9 0% 2013/14 2014/15 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 Compensation of Emloyees O&M Development Expenditure Data Source: Office of the Controller of Budget Data Source: Office of the Controller of Budget CCoouunntytyd deevveeloloppmmeennt te exxppeenndditiuturerea accccoouunnteteddf oforra ann aavveerraaggee ooff 2288..55 ppeerr cceenntt ooff tototatal lccoouunntyty ssppeennddininggb beetwtweeeennF FYY2 2001133//1144a anndd FFYY2 2002200/2/121a assr reepprreesseenntteeddi ninF Fiigguurree 22..55.. IInn FFYY 22001144//1155 ddeevveeloloppmmeennt t eexxppeennddiittuurree aaccccoouunntteedd fofro 4r 44.34 .p3erp ceerntc oefn ttheo cfouthnety ceoxupnetnydietuxrpee,n tdhiet uhrieg,hetshte hsiignhcees dt esvinocluetidoenv aonludti roenmaaninderde bmealoinwe d30b epleorw ce3n0t opfe mr ocestn ot fo tfhem poasstt ofifsctahle yeparsst sfaisvcea floyre FaYrs s2a0ve15f/o1r6 FaYnd2 0F1Y5 2/10616a/n1d7 wFYhe2n0 d1e6v/e1l7opwmhent dsepveenldoipnmg eanctcosupnenteddin fgora 3c9c.o7u anntedd 3f4o.3r 3p9er.7 ceanntd 3o4f. 3copuenrtyc eenxpt eonfdcitouurnet yresepxepcetnivdeitluyr. e Ornes tpheec toivtehleyr. haOnnd,t hcoemoptheenrsahtiaonnd ,ofc oemppelonyseaetiso nhaos f ebmepenlo ybeuersgehoansinbge ebnetbwueregne oFnYin 2g0b14et/w15e eanndF Y2022001/42/11.5 Tahned a2v0e2ra0g/2e 1s.hTarhee oafv ceoramgpeenshsaartieono f coofm epmepnlsoaytieoens oinf teomtapll ocyoeuenstyin sptoentadlincogu bnettywsepeenn FdiYn g20b1e5t/w1e6e annFdY F2Y0 2105/2106/2a1n dwaFsY 4270.22 0p/e2r1 was 47.2 per cent. Surprisingly in FY 2019/20 and FY 2020/21, compensation of employees accecnotu. nStuerdpfroisrionvgelyr ihna lFf Yo f2t0h1e9c/o2u0n atyndto FtaYl 2sp0e2n0d/i2n1g,. compensation of employees accounted for over half of the county total spending. RReeflfleecctitninggo onne exxppeenndditiutureressb byyf fuunnccttioionnaal lc clalassssifiificacatitoinon( p(priroiroitryitys psepnednidnign)g,)t,h tehec ocouunntytys sppeennt ta cao mcobminbeidneadv earvaegraegoef o6f 46.46.6p peerrc ceenntto off tthhee ttoottaall eexxppeennddiittuurree dduurriinngg tthhee ppeerriioodd FFYY 22001144//1155 toto FY 2020/21 on non-administrative services such as health and sanitation services (27.7 per cFeYnt 2);0r2o0a/d2s1, oann dnotrna-nasdpmoritni(s8t.r8atpiveer cseernvti)c;ews asutecrha ansd hierrailgtaht aionnds searnviictaetsio(n8. s6e)r;veicdeusc a(2ti7o.n7%an);d larobaodusr, (a6n.9d ptrearncsepnotr)t; (l8a.n8d%s,); hwouasteinrg anandd irwriograktsionan sderuvribcaesn (d8e.6ve);l oepdmuecnattio(4n. 3anpde rlacbeonutr) ; a(g6r.i9cu%lt)u; rlea,ndlivse, shtooucksinagn dancdo owpoerrkasti vaensd (u4r.3bapne rdecveenlot)p;mtreandte (,4e.3n%te)r;p raigsericdueltvuerloep, mliveensttoacnkd toanurdis cmoo(p1e.r3atpiveersc (e4n.t3)%; )e;n tvriardone,m eenntet,rpernieserg dyevaenldopnmateunrta al nreds toouurrciessm (1(.13.%2 )p; eernvceirnotn);mwenhtil,e geennedregry andd snoactiuarl asle revsicoeusrcaecsc o u(1n.t2e%d )f;o wr h1i.l0e gpeenrdecre natndan sdocGialr isesraviMceusn iaccipcoaulitnyteadc cfour n1t.e0d foprer0 c.7entp aenrdc eGnatr.issa Municipality accounted for 0.7 per cent. Table 2.2: County departmental/priority spending Average 2014/15 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 Average share of spending spending (per cent) Health & Sanitation 1,245.6 1,432.2 1,695.0 2,063.3 2,780.5 2,910.8 2,441.7 2,081.3 27.7 Finance & Economic 1,769.2 1,643.0 1,608.0 1,162.5 1,457.6 1,353.8 2,396.2 1,627.2 21.6 Planning County Assembly 346.4 657.5 669.5 697.0 753.5 745.0 763.7 661.8 8.8 Roads and Transport 1,021.2 1,000.1 1,122.0 480.6 206.5 456.3 331.7 659.8 8.8 12 Socio-economic Effects of COVID-19 Water & Irrigation 756.6 864.4 740.0 297.4 817.2 698.2 340.7 644.9 8.6 Services Education & Labour 229.5 371.8 324.0 509.0 918.3 569.0 691.5 516.1 6.9 County Executive Services 427.4 134.4 290.3 568.6 365.4 416.9 292.2 356.5 4.7 Lands, Housing and works, Urban 182.7 - 251.0 337.0 826.1 386.8 266.4 321.4 4.3 Development Agriculture, Livestock & 262.0 262.8 204.0 235.7 415.3 381.2 475.2 319.5 4.3 Cooperatives Trade, Enterprise Development and 84.7 112.6 102.0 64.4 135.1 94.2 75.1 95.4 1.3 Tourism Environment, Energy & Natural 213.6 28.7 80.5 59.3 61.4 117.9 61.4 89.0 1.2 Resources Gender, Social Services & Sports 57.3 38.9 37.2 31.6 155.7 155.4 49.2 75.0 1.0 Garissa Municipality - - - - 49.3 66.8 246.5 51.8 0.7 County Public Service Board - - - - 48.9 33.0 33.0 16.4 0.2 Total 6,596.2 6,546.4 7,123.5 6,506.2 8,990.9 8,385.3 8,464.4 7,516.1 100.0 Data Source: Office of the Controller of Budget On the other hand, during the review period co-ordination and administrative functions accounted for a combined 35.4 per cent with Finance and economic planning accounting for 21.6 per cent followed by county assembly at 8.8 per cent, county executive services 4.7 per cent, while county public service board accounting for 0.2 per cent. 2.2.3 Effectiveness of County spending Total budget execution averaged 79.6 per cent in the period FY 2013/14 to FY 2020/21. In 2013/14 overall total budget execution stood at 44.8 per cent. This execution improved to 94.1 per cent in FY 2016/17 before taking a downward trend to 77.2 per cent in FY 2019/20. At the end of FY 2020/21 budget absorption stood at 83.2 per cent meaning that in FY 2020/21 only Ksh 8,464.4 million was utilized out of the approved budget of Ksh 10,176.8 million (Figure 2.6). With regards to development budget execution in the county, the average absorption rate between FY 2013/14 to FY 2020/21 was 58.4 per cent (implying that on average over 41.6 per cent of the development budget is not absorbed). This implies existence of shortfalls in budget implementation and the county should continue tightening budget implementation to ensure achievement of greater absorption rates to keep help achieve the targets in annual development plans (ADPs) and the county integrated development plans (CIDPs). On recurrent expenditure, the execution has been robust over the years, the average absorption rate has been 92.4 per cent leaving about 7.6 per cent of unspent recurrent budget. 13 On thOen oththeerothhearndh,anddu,ridnugrinthgethreevrieevwiewpeprieordiodcoc-oo-rodridniantaitoionn aanndd aaddmmiinniissttrraattiivvee ffuunncctitoionnss accouanctceodunftoerdafocroamcboinmebdin3e5d.435p.4erpceer nctenwtitwhitFhinFainnacneceanadndeeccoonnoommicic ppllaannnniinngg aaccccoouunntitninggfofor r 21.6 p21e.r6cpeenrtcfeonlltofwoellodwbeydcboyucnotuynatyssaesmsebmlyblayta8t.8.8peprecrecnetn,t,cocouunnttyyeexxeeccuttiivvee sseerrvviicceess44.7.7ppeer r cent,cwenhti,lewchoiluenctoyupnutyblpicubsleicrvsiecrevibceoabrodaradccaocuconutinntgingfofror0.02.2ppeerrcceenntt.. EffecEtfifveecntievsesnoesfsCofuCnotuynstpyesnpdeinndging TotalTboutadlgbeutdegxeetceuxteiocnutiaovnearavgereadge7d9.769.p6epr ecrecnetnitninthtehepepreiroioddFFYY2200113//14 tto FFY 22002200//2211. .InIn 2013/210413o/v1e4raolvletroatllaltobtauldbguedtgeexteecxuetciountiosntosotododata4t 44.48.8peprercecennt.t.TThhiiss eexxeeccuuttiioonn iimpprroovveeddtoto 94.1 9p4e.1r cpeenr tceinntFiYn 2FY01260/1167/1b7efboerfeorteaktiankginga adodwownwnwaradrd trterenndd ttoo 7777..22 ppeerr cceenntt ininFFYY 2019/22001.9/A2t0t.hAet ethned eonfdFoYf 2F0Y2200/2201/2b1udbgudegt eatbasbosroprtpiotinonstsotoooddaatt8833..22 ppeerr cceenntt mmeeaannininggththaat t in FYin20F2Y02/20210/o2n1lyonKlsyh.Ks8h,.4684,4.644.m4ilmlioilnliown awsasutuilitzileizdedouout tooffththee aapppprroovveedd bbuuddggeett ooffKKshsh. . 10,17160.,817m6i.l8liomnil(lioFnig(uFrigeu2r.e62)..6). With regards to development budget execution in the county, the average absorption rate With breetgwaerdens FtoY d20e1v3e/lo1p4mtoenFtY b2u0d2g0e/2t1ewxeacsu5ti8o.n4 pinerthceentco(iumnptyly,intghethaavteornagaevearabgseoropvteiorn41ra.6te betwepeenr cFeYnt2o0f1t3h/e14detvoelFoYpm2e0n2t0b/2u1dgwetasis 5n8o.t4apbesorrcbeendt).(Timhipslyiminpglietshaetxiostnenacveeroafgsehoorvtfearlls41in.6 per cbeundt goeft tihmepldeemveenlotaptmionenatndbuthdegectouisntnyosthaobusldorcboendti)n.uTehtiigshitmenpilniegsbeuxdigsteetnimceploefmsehnotarttfioanllstoin budgetnsimurpeleamcheienvteamtioentaonfdgtrheeatceor uanbtsyorsphtoiounldractoensttinoukeeetipghteelpninacghbieuvdegtehteimtaprgleemtseintatnionunatlo ensurdeevaeclhoipemvemntenptlaonfs g(rAeDaPtes)r aabnsdortphteioncoruantteys itnotekgereatpedhedlpevaeclohpiemventhpelatnasrge(CtsIDinPs)a.nnOunal develroepcmurerenntt pelaxnpsend(AituDrPes,) thaendextehceuticoonunhtyas inbteegnratreodbusdtevoevleorpmtheent ypealarns,s t(hCeIDaPvse)r.agOen rSeoccuior-raeebcnosnotormpeticxio psnteatnruads tioetfu Ghraear,sissbtah eCeonune9tyx2 ew.4cituhp tCieoOrnVcIDehn-a1t9sleabveiengn arboobuuts7t .6ovperr ctehnet oyfeaurnss,petnhtereacuvrerreangte absorbputdiognet.rate has been 92.4 per cent leaving about 7.6 per cent of unspent recurrent budget. Figure 2.6: County Approved Expenditure and Absorption rates FFiigguurree2 2.6.6: :C CouonutnytAyp AprpopvreodvEexdp eEnxdpiteunredaitnudrAeb asnordp tAiobnsroartpestion rates Figure 2.6(a): Approved versus actual Figure 2.6(b): Absorption rates for Figucoreu n2t.y6(sap)e: nAdpinpgro(vKesdh vMerilsluiosn )actual Figure c2u.6rr(ebn):t Absorpatniodn ratesd feovre rleocpumrreentt Ficgouurnety2 s.p6e(nad)i:nAg p(Kpsrho vMeidlliv94. one)rsus actualandF idegexuvpreeelonpd2mit.6uern(ebt s)e:x(peAnrbdcsieotnurtrp)etsi o(pner rcaetnets) for county spending 8(4K. s88h. M1 illio8n3.) 83. recurrent and development12,000 81. 0 944. 7 8 77. 100 2 90 expenditures (per cent)88. 2 12,00010,00084. 14 81. 83. 83. 101.3 10080 96.4 96.2 98.2 98.4 99.3 97.7 0 7 8 77. 2 90 70 10,0008,000 44. 2 80 60 96.4 87.0 101.3 96.2 98.2 98.4 99.3 97.778.8 6,000 8 70 50 72.38,000 44. 60 40 87.04,000 51.4 78.8 56.6 6,000 8 50 30 53.9 20 72.32,000 40 42.3 45.3 4,000 10 51.430 31.0 56.6 53.900 00 2,000 20 42.3 45.3 10 31.0 00 00 Approved Budget Actual Expenditure Overall absorption Recurrent Development Approved Budget Data Source:AcOtuffailcEexpoefntdhiteurCe ontroller of Budget Overall absorption Recurrent Development Pending Bills Data ISnoFuYrc2e0:1O4f/f1ic5ethoef tchoeunCtyonretrpoollreterdofKsBhu.d4g6e0t.0 million in pending bills. This increased to Ksh.Data9 8S0o.u1rmcei:ll iOonffiicneF oYf 2th0e1 7C/o1n8twroitlhledr eovfe Bloupdmgeentt spending related pending bills accounting for Pend8i7n2g.0Bpilelsr cent of this. In FY 2018/19 pending bills slowed to Ksh. 619.6 million before In2.F2Y.s42h o0o1Pt4ien/n1g5duitpnhtego cBKoisulhlnst8y77re.0pomrtilelidonKisnh.FY46200.109m/2i0ll.ioAnt itnhepeennddinogf FbYills2.0T20h/is21inccoruenatsyedpetnodKinsgh. 980.1 million in FY 2017/18 with development spending related pending bills accounting for 8I7n2 F.0Y 2p0e1r4c/e1n5t thoef ctohuisn.tyI nrepFoYrt2e0d1 K8s/h1 946p0e.n0d miniglliobnill sin sploenwdeidngt obilKlss.h T.h6is1 i9n.c6Praemgaesileli2do6 ntoo bKfes6fho2 re s9h8o0ot.1in mg iullpiotno inK sFhY8 27071.70/1m8i llwiointhi ndeFvYelo2p0m19e/n2t0 s. pAetntdhienge rnedlaotefdF Ype2n0d2in0g/2 b1ilclso uancctyoupnetnindgin g for 872.0 per cent of this. In FY 2018/19 pending bills slowed to Ksh 619.6 million before shooting up to Ksh 877.0 million in FY 2019/20. At the end of FY 2020/21 coPuangtey p2e6ndoifng6 2 bills amounted to Ksh 870.8 million with development related pending bills accounting for 9bi7ll.s5a pmeoru ncteendtt.o GKesnhe8r7a0l.l8y,m pilelinondiwnitgh bdielvlse lroeplmaetnetdr teola tdeedvpeelnodpinmg ebnillts haaccvoeu nbteinegnf ogrreater than those r9e7l.a5tpeedr cteon tr.eGceunrerraelnlyt, peexnpdeinngdbiitllus rreel aotend atovedervaegloep macecnot uhanvteinbgee fnogrr e7a6te.r8t hpaenrt hcoesnet of the pending related to recurrent expenditure on average accounting for 76.8 per cent of the pending bills bpoilrltsfo plio.rtIfopleiond. iInfg pbeinllsdifonrg dbeivlelslo pfomre ndtevwelroeppmaidenint wtheerire rpeaspidec tiinve thfiesciarl ryeesapr,ecthtieve fiscal year, the eexxeeccuutitoinonof odef vdeelovpemloenptmbuedngte tbiundsugbeste qinue snut byesaerqsuweonultd yimeaprrosv we.ould improve. Figure 2.7: Profile of county pending bills Figure 2.7: Profile of county pending bills 1,200 980.1 1,000 877.0 870.8 800 619.6 600 460.0 446.8 400 310.5 200 0 2014/15 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 Recurrent Devevelopment Total Pending Bills DDaatataS oSuorcuer:cOef:fi cOeffiofcteh eoCf otnhtero ClleornotfrBouldlgeert of Budget In order to achieve its overall goal of improving lives and livelihoods of its residents, the county government must now move quickly to tackle the problem of pending bills. Increasing and persistent pending bills is a threat to the survival of the private sector particularly primary firms that trade with the county government. These firms are critical for employment creation as well as driving economic activi1ty4within the county. These bills have not only affected their profitability and overall performance but have also become a threat to private sector in general and the families that depend on these firms through ripple effect. If not well monitored these could grow and eat up on the county’s already thin revenue sources. 2.2 Conclusions i. Mobilize more finances from OSR to increase the available revenues for budgetary operations. ii. Seek for more funding in form of grants from development partners to cater for the critical development projects in the county. iii. Ensure that the ongoing projects are completed before launching new project and clear any pending bills and arrears owed to suppliers. iv. Ensure the ongoing infrastructure project are completed and suppliers paid within the specified timelines for optimal returns to investment and to spur private sector activity. v. Improve budget execution and absorption of development budget by harmonizing project implementation cycles to budgeting and fast-track exchequer releases. vi. Reduction of expenditure on compensation of employees within the PFM requirement since ballooning compensation of employees potentially affects execution of key development programs especially if not brought to sustainable levels. Page 27 of 62 Amount (Ksh Million) Amount (Ksh Million) 20 Amount (Ksh Million)1 2 30 /11 4 2 4 2 /1 010 31 5 20 /5 1420 /1 1 6 2 41 /1 2 6/ 0 1 1 5 0 7 2 517 0 /1 1 62 /1 2 60 8 0 /1 18 720 / 1 1 2 79 0 /1 19/ 1 8 20 2 8 2 0 20 /19 0 1/ 92 20 /1 22 00/21 Overall PaebsoOvrerc r ae p lln ttion (per cent) Paebrsocrepnttion (per cent) 2013/ 21 01 2 4 3/0 114 2 4 / 01 15 42 /0 115 2 5 / 01 1 2 6 5/1 01 2 6 6 0/ 11 6 2 7 /1 0 2 717 0/ 11 7 2 8 /1 2 801 08 1/ 81 / 2 9 19 0 21 09 1/ 92 /0 22 2 0 0 02 20 0/ /2 21 1 Socio-economic Effects of COVID-19 In order to achieve its overall goal of improving lives and livelihoods of its residents, the county government must now move quickly to tackle the problem of pending bills. Increasing and persistent pending bills is a threat to the survival of the private sector particularly primary firms that trade with the county government. These firms are critical for employment creation as well as driving economic activity within the county. These bills have not only affected their profitability and overall performance but have also become a threat to private sector in general and the families that depend on these firms through ripple effect. If not well monitored these could grow and eat up on the county’s already thin revenue sources. 2.3 Conclusions i) Mobilize more finances from OSR to increase the available revenues for budgetary operations. ii) Seek for more funding in form of grants from development partners to cater for the critical development projects in the county. iii) Ensure that the ongoing projects are completed before launching new project and clear any pending bills and arrears owed to suppliers. iv) Ensure the ongoing infrastructure project are completed and suppliers paid within the specified timelines for optimal returns to investment and to spur private sector activity. v) Improve budget execution and absorption of development budget by harmonizing project implementation cycles to budgeting and fast-track exchequer releases. vi) Reduction of expenditure on compensation of employees within the PFM requirement since ballooning compensation of employees potentially affects execution of key development programs especially if not brought to sustainable levels. vii) Monitoring and prompt payment of pending bills as they limit execution of planned activities in subsequent budgets. 15 Socio-economic status of Garissa County with COVID-19 3. Agriculture, Livestock and Fisheries 3.1 Characteristics of the sector Agriculture accounts for a significant share of economic activity in Garissa County. More than 40 per cent of the County economic activity is driven by the agriculture sector. In 2017, agriculture accounted for Ksh 16,845 million out of the total Ksh 39,394 million Gross County Product (GCP) amounting to 42.8 per cent of the County’s GCP. Over 30per cent of the households in Garissa County practice farming. About 3.1 per cent of the households produce crops, 32.6per cent produce livestock, 1.4 per cent practice aquaculture and about 1.0 per cent are involved in fishing. About 1.3 per cent of the households practice irrigation farming. Table 3.1: Distribution of Households Practicing Agriculture, Fishing and Irrigation by County and Sub County County/ Total Farming Crop Livestock Aquaculture Fishing Irrigation Sub County Households Households Production Production Kenya 12,143,913 6,354,211 5,555,974 4,729,288 29,325 109,640 369,679 Garissa 141,394 47,645 4,406 46,154 1,981 1,411 1,817 Balambala 4,337 1,786 428 1,653 144 109 220 Dadaab 35,793 9,315 410 9,128 313 250 86 Fafi 23,671 6,556 929 6,263 326 263 473 Garissa 30,518 3,335 1,032 2,849 128 99 488 Hulugho 20,254 13,731 1,147 13,478 681 448 341 Ijara 18,481 8,136 413 8,021 311 158 191 Lagdera 8,340 4,786 47 4,762 78 84 18 Source: 2019 Kenya Population and Housing Census The estimated acreage under food crops in 2020 is 5,850 acres of which 5,500 acres are under small scale farming. A significant share of the land under farming (crops) is under commercial farming compared to the area under subsistence farming. 16 Agriculture, Livestock and Fisheries Table 3.2: Area of land Under Farming 2015 2016 2017 2018 2019 2020 Area of land Under Farming (Food crops) Acres 3,950 4,250 4,550 5,050 5,550 5,850 Area of land Under Small Scale 3,750 4,050 4,300 4,800 5,300 5,500 Area Under Irrigation Farming (Acres) 3,050 3,200 3,450 3,800 4,150 4,200 Proportion of Farming Households Practicing Farming 0.25 0.25 0.25 0.25 0.25 0.25 Strictly for Subsistence Area of Land under Subsistence Farming, Acres 900 1,050 1,100 1,250 1,400 1,650 PPrrooppoorrttiioonn ooff FFaarmrminingg Households 0.75 0.75 0.75 0.75 0.75 0.75 Hpouurssueihnoglds pufrasruminingg farminasg as a ab buusisninesess/sc/ocommmmerecricailal purppuorspeos ses 0.75 0.75 0.75 0.75 0.75 0.75 ((ppeerr cceennt)t) Area of Land Under Commercial 3,050 3,200 3,434 3,777 4,155 4,200 AFraeram oinf gLand Under Commercial Farming 3,050 3,200 3,434 3,777 4,155 4,200Source: Garissa County Source: Garissa County On the scale of production, the FAO criterion on land size is used to identify small holder Ofna rtmhee rsscaalse othf opsreodpurcotdiounc,e rtshe thFaAtO“ fcarlilteirnionth oen bloatntdo msiz4e0 is puesredc etnot idoefnttihfey scmumalul lative hodlidsterri bfuartimone’r’s( Kash athliloeset aplr.o, d2u0c1e7r)s. tUhsaitn “gfatlhl isinc trhite rbi ontt,onmo n4e0 opfetrh ceenfatr omf inthge hcouumseuhlaotlidvse (Crop diPsrtroidbucttioionn’’, (LKivheasltiol cekt aPlr.o, d2u0c1t7io).n ,UsinAg qtuhaisc uclrtuitreer,ioFnis, hninongea onfd thIrer igfartmioinn)g inhoGuasreihssoaldCs ounty (Carroep“ Psmroadlul-cstciaolne,” Lfaivremstinogckw Pitrhodaulcatniodnh, oldinAgqoufa0cu.6lt7u5reo,r lFesishaincrge saonfdl anIdrr. igation) in Garissa County are “small-scale” farming with a land holding of 0.675 or less acres of land. FiFgiguurree 33..11:: SSccaallee ooff Oppeerartaiotino:np:e pr ecre ncteonft hoofu hseohuosledhs olds 120 100 80 60 40 20 0 Medium and Large_Scale Small_Scale Garissa Source: KIHBS 2015/2016. Figures for a period of the 12 months Source: KIHBS 2015/2016. Figures for a period of the 12 months ThTeh eCoCuonutnyt yisi sclcalasssisfiifeiedd aass aa NNoorrtthh AASSAALLSS aaggrrooeeccoollooggiiccaall zzoonnee aass ppeerr tthhee AAggrricicuultluturaral lS ector Transformation and Growth Strategy (ASTGS) 2019-2029. An overall analysis of the County Seacgtroirc uTltruarnaslfoprrmodauticotnio nanidn dGicraotwesth aSmtroantgegyth (eAStoTpGSf)o o2d01c9r-o2p0s29p.r o dAunc eodverbayll haonuaslyeshios lds in ofG tahreis sCaouinnctlyu daegrmicauilzteu,rbala nparondaus,cttioomn aitnodeisc,awteast earmmoenlogn tsh,eb etoapn sfoaondd cornoiposn sp.roduced by households in Garissa include maize, bananas, tomatoes, watermelons, beans and onions. Table 3.3: Distribution of Households Growing Crops by Type, County and Sub County County/Sub County Garissa Balambala Dadaab Fafi Garissa Hulugho Ijara Lagdera Maize 2,590 250 17 260 651 451 724 244 10 Bananas 1,902 171 70 630 655 197 175 4 Tomatoes 1,808 193 98 598 560 177 179 3 Watermelon s 1,727 198 119 519 526 205 157 3 Beans 1,326 113 161 315 202 338 192 5 Onions 1,132 180 88 380 229 129 124 2 Kales 804 88 38 226 188 120 143 1 Sorghum 748 82 120 123 31 280 108 4 Potatoes 696 96 46 134 91 166 159 4 Source: 2019 Kenya Population and Housing Census Page 29 of 62 Socio-economic status of Garissa County with COVID-19 Table 3.3: Distribution of Households Growing Crops by Type, County and Sub County County/Sub County Garissa Balambala Dadaab Fafi Garissa Hulugho Ijara Lagdera Maize 2,590 250 260 651 451 724 244 10 Bananas 1,902 171 70 630 655 197 175 4 Tomatoes 1,808 193 98 598 560 177 179 3 Watermelons 1,727 198 119 519 526 205 157 3 Beans 1,326 113 161 315 202 338 192 5 Onions 1,132 180 88 380 229 129 124 2 Kales 804 88 38 226 188 120 143 1 Sorghum 748 82 120 123 31 280 108 4 Potatoes 696 96 46 134 91 166 159 4 Source: 2019 Kenya Population and Housing Census Key permanent crops among households in Garissa include Mangoes. Table 3.4: Distribution of Households Growing Permanent Crops by Type and County County/Sub County Mango Garissa 1,726 Kenya 796,867 Source: 2019 Kenya Population and Housing Census Resource productivity is another key important factor in determining the agro-processing potential (scale) of the County and would have a great impact on farmers’ incomes and the County’s GCP. An assessment of horticultural productivity indicates Garissa’s value of fruits production in 2019 amounted to Ksh 338.9 million. The area under fruit was 1,795 Ha with a production of 21,601 MT. The major fruits grown in order of value importance are; banana, mango and watermelons. Table 3.5: Fruits Grown in Garissa Type of Fruit Area in Ha Production in Tons Value in Shillings Banana 889 14,190 195,780,000 Mango 604 5,163 66,479,000 Watermelons 171 1,475 62,170,000 Pawpaw 98 690 12,155,000 Sweet Melons 10 50 1,500,000 Lemons 23 33 800,000 Total 1,795 21,601 338,884,000 Source: Agriculture and Food Authority, 2019 18 Agriculture, Livestock and Fisheries In 2019, the value of vegetables production in the County amounted to Ksh 14.7 million. The area under vegetables was 206 Ha with a production of 711 MT. The major vegetables grown in order of value importance are tomato and bell pepper/sweet paper. Table 3.6: Vegetables Grown in Garissa Type of Vegetables Area in Ha Production in Tons Value in Shillings Tomato 151 584 11,940,000 Bell Pepper/Sweet Paper 36 90 2,220,000 Kales 19 37 560,000 Total 206 711 14,720,000 Source: Agriculture and Food Authority, 2019 In 2019, the value of MAPs production in the County amounted to Ksh 25.3 million. The area under MAPSs was 88 Ha with a production of 453 MT. The major MAPs grown are Bulb Onions. Table 3.7: Medicinal and Aromatic plants (MAPs) Grown in Garissa Medicinal and Aromatic Area in Ha Production in Value in Plants (MAPs) Tons Shillings Bulb Onion 65 419 24,100,000 Long Cayenne Chilies 23 34 1,235,000 Total 88 453 25,335,000 Source: Agriculture and Food Authority, 2019 Being an ASAL County, animal production is a key economic activity in Garissa County. Other than rearing the traditional livestock (i.e. cattle, sheep, goats, donkeys and camels), the County has promoted poultry production and bee keeping (apiculture) and among farming households in the County. Table 3.8: Distribution of Households Rearing Livestock and Fish by County and Sub County County/Sub County Garissa Balambala Dadaab Fafi Garissa Hulugho Ijara Lagdera Goats 41,468 1,464 8,064 5,639 2,517 12,284 7,194 4,306 Sheep 37,684 1,020 6,968 4,844 1,914 12,006 6,950 3,982 Indigenous cattle 23,444 669 3,217 2,359 1,341 10,619 3,825 1,414 Donkeys 20,630 821 5,072 3,431 1,341 5,045 1,891 3,029 Camels 17,624 1,110 6,508 3,871 1,611 891 316 3,317 Indigenous Chicken 5,852 108 476 284 239 3,774 908 63 Exotic cattle -Dairy 1,376 83 291 325 144 170 314 49 19 Socio-economic status of Garissa County with COVID-19 Exotic Chicken 1,307 69 240 223 113 301 349 12 Layers Beehives 833 67 64 147 48 362 141 4 Exotic Chicken 832 63 120 138 22 232 249 8 Broilers Exotic cattle -Beef 608 66 124 175 29 71 131 12 Rabbits 285 62 48 86 20 46 19 4 Source: 2019 Kenya Population and Housing Census The above characterization of farming households highlights the priority value chain opportunities in maize, bananas, tomatoes, watermelons, beans and onions, mangoes, cattle, sheep, goats, donkeys, camels, poultry production, bee keeping (apiculture). With majority of the households farming the identified products, the current Garissa transformation strategy in agriculture should prioritize value chains in the identified areas to positively impact of households’ livelihoods. 3.2 Agri-Food Challenges in COVID-19 i) Human capital/employment levels – by gender Agricultural labor participation in Garissa indicates relative dominance by either gender in specific agriculture related occupations. Majority of the population in Garissa are farm workers where the group covers occupations related to: Field Crop, Vegetable and Horticultural Farm Workers; Poultry, Dairy and Livestock Producers; and Crop and Animal Producers. This subcategory is strongly dominated by males. The classifications are based on the Kenya National Occupational Classification Standard (KNOCS). FFiigguurree3 .32.:2A:g AricgurlitucrueltRuerlaete Rd eLlaabtoerdF oLrcaebPoarr tFicoipractieo nParticipation 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 1 2 3 4 5 6 7 8 Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 An assessment of the COVID_19 effects on hours worked by in agriculture related occupations indicates workers in most of the identified sub-sectors worked fewer hours in the reference period as compared with the usual hours worked per week. The most affected workers are the agriculturalists and related professionals who recorded the highest difference of 16 hours between the usual and actual hours worked in a week. The workers in this sub-major group conduct research and improve or develop concepts, theories and operational methods; apply scientific knowledge20relating to crop husbandry. Figure 3.3: Changes in Hours Worked by in Agriculture Related Occupations Agricultural, Fishery And Related Labourers Farm Workers (Except Fish) Administration Middle Level Personnel:Lands, Agricultural And Livestock Officials Agriculturalists And Related Professionals 0 10 20 30 40 50 60 How many hours did you actually work in the last 7 days? How many hours do you usually work per week ? Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 The identified COVID_19 effects on labour force participation are likely to have negative effects on output thereby increasing yield gaps. The effects are also likely to have negative effects on household’s income. ii) Market operations Page 33 of 62 Number of People Figure 3.2: Agriculture Related Labor Force Participation 18,000 16,000 14,000 12,000 10,000 8,000 6,000 Agriculture, Livestock and Fisheries 4,000 2,000 0 An assessment of the CO1VID-19 2 effects 3on hou4rs worke5 d by in6 agricu7lture re8lated occupations inSoduirccaet:eKsN BwSoSrukreverys oin SmocoiosEt conf otmhiec IimdpeancttiofifeCdO VsuIDb-1-s9eocntoHrosu swehoorldkse-dW afveew2er hours in the reference period as compared with the usual hours worked per week. The most An assessment of the COVID_19 effects on hours worked by in agriculture related affected workeorcscu apraeti othnse iangdirciactuesltwuorrakleisrstsin anmdos rteolaf ttehed ipdreontfiefisesdiosunba-slse cwtohrso wreorckoerddfeedw etrheho huirgshinest difference of 1t6he hroefuerresn bceetpwereioedna tshceo mupsaureadl awnithd tahcetusaula lhhoouurrss woorkrekdepde rinw eae wk.eTehke.m Tohste awffeocrtkeders in this sub-mawjoorrk egrsroaurpe ctohendaugcritc urletusreaalisrtcsh aannddr eimlatpedrovpreo foers sdioenvaleslowph oconrecceoprdtesd, tthhee highestdifference of 16 hours between the usual and actual hours worked in a week. Theowrioerkse arsnd operational mientthhoisdsu;b a-mppajloyr sgcrioeunpticfioncd kunctorwesleadrgche arnedlaitminpgro vtoe corodpe vheulospbcaonndcerpyt.s, theories and operational methods; apply scientific knowledge relating to crop husbandry. Figure 3.3: Changes in Hours Worked by in Agriculture Related Occupations Figure 3.3: Changes in Hours Worked by in Agriculture Related Occupations Agricultural, Fishery And Related Labourers Farm Workers (Except Fish) Administration Middle Level Personnel:Lands, Agricultural And Livestock Officials Agriculturalists And Related Professionals 0 10 20 30 40 50 60 How many hours did you actually work in the last 7 days? How many hours do you usually work per week ? Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Source: KNBST hSeuridveenytif ioedn CSOoVcIiDo_ E19coenffoecmtsico nImlapboaucrt foofr cCeOpVarItiDcip-a1t9io onna rHe oliukesleyhtooldhasv-eWnaevgaet i2ve The identifiede fCfeOctVs IoDn -o1u9tp uetfftehcetresb oynin clraebaosiungr yfield gaps. The effects are also likely to have negaeffects on household’s income. orce participation are likely to have neg taivteive effects on output thereby increasing yield gaps. The effects are also likely to have negative effects on houisi)ehMoaldrk’se tinocpoemratei.ons ii) Market operations Page 33 of 62 Successful transformation of smallholder agricultural production in Garissa County from subsistence to an innovative, commercially oriented and modern agricultural sector, as aspired in the national ASTGS, is dependent on the ability of the County market its commodities both in domestic, regional and international markets. Among the marketing issues faced by the County is road access, a key indication of access to markets. Garissa’s rural access index (RAI)- which measures “the number of rural people who live within two kilometers (typically equivalent to a walk of 20-25 minutes) of an all- season road as a proportion of the total rural population- fairs poorly at 24 per cent. This is low compared to the national average of 69.38 per cent. As a result of COVID-19, there has been a further slow down on trade activities due to the restrictions on movements. From the KNBS conducted between 30th May and 6th June 2020, 38.3 per cent of the households in Garissa County indicated over the past 1 week there had been instances where the household or a member of the household could not access the markets/grocery stores to purchase food items. 21 Number of People Successful transformation of smallholder agricultural production in Garissa County from subsistence to an innovative, commercially oriented and modern agricultural sector, as aspired in the national ASTGS, is dependent on the ability of the County market its commodities both in domestic, regional and international markets. Among the marketing issues faced by the County is road access, a key indication of access to markets. Garissa’s rural access index (RAI)- which measures “the number of rural people who live within two kilometers (typically equivalent to a walk of 20-25 minutes) of an all- season road as a proportion of the total rural population- fairs poorly at 24 per cent. This is low compared to the national average of 69.38per cent. As aSorecsiou-ltecoof COVID-19, there has been a further slow down on trade activities due to therestrictions onnommovice msteanttuss. oFfr oGmartihsesaK CNBoSunctoyn wduitchte CdObVetIwDe-e1n9 30th May and 6th June 2020, 38.3 per cent of the households in Garissa County indicated over the past 1 week there had been instances where the household or a member of the household could not access the markets/grocery stores to purchase food items. FiguFreig3.u4:rLeim i3te.d4a:cc Lessimto mitaerkdet satoccpuercshsas etofo omd itaemrskets to purchase food items 38.3% 61.7% Yes No Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 MajMoritayjoofrtihteyh ooufs tehhoeld hs oinudiscaetehdotlhdesk eiynrdeiacsoantsefdor tnhoet akcceeyss rinegatsheonmsar kfoetrs/grocerystores to purchase food items were movement restrictions (46.5 per cent) and closur enooftt haeccessing the markets/grocery marskteotsr/gerso cetroy sptourersc(2h7a.9sepe rfcoeontd). items were movement restrictions (46.5%) and closure of the markets/grocery stores (27.9%). Figure 3.5: Reason for Limited access to markets/ grocery stores Figure 3.5: Reason for Limited access to markets/ grocery stores 50.0% 46.5% 45.0% 40.0% 35.0% 30.0% 27.9% 25.0% 50.0% 20.0% 46.5% 45.0% 15.0% 12.5% 11.9% 40.0% 35.0% 10.0% 30.0% 52.07.%9% 0.6% 0.6% 25.0% 0.0% Page 34 of 62 20.0% Markets/stores Transport Movement Security concerns Concerned about Others 15.0% were clo1s2e.d5% limitations restrictions(eg. 11.9% leaving the house 10.0% 5.0% curfe0w.6)% due to o0u.6t%break 0.0% MSaorkuertsc/est:orKesNBS STurarnvspeoyrton SocMioovEemcoenntomiScecIumritpyacocntcoerfnsCOCoVnIcDern-1ed9aboonutHousOethhoerlsds-Wave 2 Sowuerreccleo:se Kd NBSl imSiutartivonesy onr eSstoricctcuri ioon sE(ecgo. nomic Impaclte aovfinfew) due t gCtOheVhoIuDse-19 on Households-Wave 2 Livestock trade has especially been majorly affected aosouttrbaredaekrs are unable to take the Source: KLNliivvBeeSsstStooucrckvket yotrotahndeSeom chaioraksEe cteo.snpomeciciaIlmlyp abceteonf CmOVaIjDo-r1ly9 oanffHecotuesdeh oalsd st-rWaadveers2 are unable to take the Livestocklivtreasdteochka stoe tshe mRestrictions apffeecciaatilnlyrkbet. g seeanmlmesasjomrlyovaefmfeecntetdofasfootrdadceorms maroediutineasbaleretoliketalyketothceause a hike in livestockRtpoerstichtersicmtiainorknnesto .na-ffperoctdiuncgti osneaamreleasss amndovfeamll einnt porfi cfeosodin copmrodmuoctdioitniesa raeraes .li8k2elyp etro cceanutseo fa hike inh opursiecheosl disn innoGna-prisrsoaduCcotuionnty airnedaicsa taenddt hfaaltl oinve pr rtihceesp ians tp2rowdueecktisonfr oamreathse. 8r2ef epreern ceRestrictions a cent of perifofedc,twinhgilsee1am7 lpeesrs cmeonvteinmdeincat toefdfothoadt ctohmeymhoadditinesotaerexpliekreielyntcoedcaauscehaangheikeininthe prices prices inhonuons-ephrodldusct iionn Garaeraissan Cd ofuanll tyin inprdiciecsateind ptrhoadtu cotivoenr atrheea sp. a8s2t 2pe wr eceknts ofrfom the reference householpdFesirgiiunordeG, a3wr.i6sh:sialPee C1roc7eu pnntteayrg cienedonifcta hitoneuddsiecthhaaottelddos vteehxraptte htrehieenpyca ishntgad2c hnwaoneteg kesxipnfreforomioednthcoeemdr meaf eocrdheiatnyncepgrei ciens the prices period, while 17 per cent indicated that they had not experienced a change in the prices Figure 3.6: Percentage of households experiencing change in food commodity Figure 3.p6:rPicercentage of FhOoOuDsPeRhICoEldS sHAeVxEpIeNrCREes ien AcSiEnDg chaFnOgOeD iPnRIfCoEoSdHAcVoEmDmECoRdEAitSyEDpricesNO CHANGES FOOD PRICES HAVE INCREASED FOOD PRICES1H7A%VE DECREASED NO CHANGES 1% 17% 1% 82% Source: KNBS Survey on Socio Econo8m2%ic Impact of COVID-19 on Households-Wave 2 Source: KSNoBuSrcSeu:r vKeyNoBnSS SoucirovEecyo noonm SicoIcmiop aEcct onf oCmOViIcD I-m19poanctH ouf sCeOhoVldIsD-W-1a9v eon2 Households-Wave 2 On the magnitude of the price shocks, 62 per cent of the households indicated they faced a large rise in food prices in the past two weeks from the reference period. On the magnitude of the price shocks, 62 per cent of the households indicated they faced a large rise Finigfuoroed3p.r7ic:ePsrionptohretiopnasotftwhoouwseehekosldfsrofmacitnhge lraerfge2ere2fnocoedpperriicoed.shocks Figure 3.7: Proportion of households facing large food price shocks Page 35 of 62 Page 35 of 62 Agriculture, Livestock and Fisheries On the magnitude of the price shocks, 62 per cent of the households indicated they faced a large rise in food prices in the past two weeks from the reference period. Figure 3.7: Proportion of households facing large food price shocks No Yes 38% 62% Source: KNBS SuSrvoeuyrocne:S KocNioBESc Sonuormveicy Iomnp Sacotcoiof CEOcoVnIDo-m19ico InmHpoaucste hoof lCdsO-WVIaDve-129 on Households-Wave 2 Poor access to markets also hinders the ability to supply food to the population as shown Poor access to m the below figure.i anr ktehtes baelsloowhi nfidgeurrset.he ability to supply food to the population as shown in FFiigguurere3 .38:.8p:e rpceern tceHnouts Hehooludsserehpoorltdinsg rtehpatotrhteinfogll otwhiangt tfhooed fiotelmloswwienreg nfootordea idtielyms were navoati larbeleadinilthye airvloaciallaitby le in their locality 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Cereals, Legumes / Milk and Meat, fish Vegetables Fruits Oil / fat / Sugar or Condiments grains, nuts other dairy and eggs and leaves butter sweet / Spices roots and products tubers Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 SAoukerycec:o KncNerBnSi sSuthravteyth oenf oSoodcigor oEucposnaofmfecitce Idmmpoasctta oref CthOeVnIuDt-ri1ti9o uosn fHoooducsaetheoglodrise-sW- ave 2 Ave kgeetya bcloesn,cearnnd isfr utihtsa-tw hthiceh foaroed ngercoeusspasr yafffoerctebdoo mstiongst tahree itmmune system of thepopulation. he nutritious food categories- vegetables, and fruits-which are necessary for boosting the immune system of the pAompounlgattihoen.key strategies adopted by households to mitigate COVID_19 effects on food consumption include purchase food on credit or incurred debt (44.1 per cent), relying on Alemssopnrgef etrhred kaenyd sletsrsateexgpienss iavedofopotdesd( 4b2y. 4hpoeursceehnot)l,dlsim tito pmorititoignastieze CaOt mVeIDalt-i1m9e se(ff3e6c.9ts on food cpoenr scuenmt)patniodnb oinrrcolwudfoeo dp,uorrcrhealyseo nfohoeldp foronm carefdrieitn doro rinreclautrivreed(2 7d.e9bpte (r4c4en.1t)%. ), relying on less pFrigeufererr3e.d9: aFnigdu rlees3s.1 e0x: ppeerncseivnet offohooduss e(h4o2ld.4s%w)h,e lriemthite pfoolrlotwioinng ssitzreat eagt iems ewaelrteimadeosp (te3d6.9%) and bforrraot wlea fsotoodn,e odra ryely on help from a friend or relative (27.9%). Sold assests to buy food? Decreased buying some non-food product? Skip entire days without eating? Reduce number of meals eaten in a day? Ration the money you have and buy prepared food? Feed working members of household at the expense of non-working members? Reduced portion size for children? Page 36 of 62 Reduced portion size for women? Restrict consumption by adults for small children to eat? Limit portion size at mealtimes? 23 Send household members to beg? Send household members to eat elsewhere? Consume seed stock held for next season? Gather wild food, hunt, or harvest immature crops? Purchase food on credit or incurred debt? Borrow food, or rely on help from a friend or relative? Rely on less preferred and less expensive foods? 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Page 37 of 62 Figure 3.8: per cent Households reporting that the following food items were not readily available in their locality 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Cereals, Legumes / Milk and Meat, fish Vegetables Fruits Oil / fat / Sugar or Condiments grains, nuts other dairy and eggs and leaves butter sweet / Spices roots and products tubers Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 A key concern is that the food groups affected most are the nutritious food categories- vegetables, and fruits-which are necessary for boosting the immune system of the population. Socio-economic status of Garissa County with COVID-19 Among the key strategies adopted by households to mitigate COVID_19 effects on food consumption include purchase food on credit or incurred debt (44.1 per cent), relying on less preferred and less expensive foods (42.4 per cent), limit portion size at mealtimes (36.9 per cent) and borrow food, or rely on help from a friend or relative (27.9 per cent). Figure 3.9: Figure 3.10: per cent of households where the following strategies Figure 3.9: Figure 3.10: per cent of households where the following strategies were adopted were adoptedfo rfoatrle aastt oleneadsaty one day Sold assests to buy food? Decreased buying some non-food product? Skip entire days without eating? Reduce number of meals eaten in a day? Ration the money you have and buy prepared food? Feed working members of household at the expense of non-working members? Reduced portion size for children? Reduced portion size for women? Restrict consumption by adults for small children to eat? Limit portion size at mealtimes? Send household members to beg? Send household members to eat elsewhere? Consume seed stock held for next season? Gather wild food, hunt, or harvest immature crops? Purchase food on credit or incurred debt? Borrow food, or rely on help from a friend or relative? Rely on less preferred and less expensive foods? 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Additional significant challenges faced by the County during the COPaVgIeD3-719of 6p2andemic include DesertA dldoictiuonsatlss ig(n2i.f3ic%an)t;c hFallleonogdes/fa cMedubdystlhiedeCso/u ntLyadnurdinsglitdhesC O(V5I.D2-%19);p aandnedm icLiinvcelusdteock Diseases (22.7%D)e.sert locusts (2.3 per cent); Floods/ Mudslides/ Landslides (5.2 per cent); and Livestock Diseases (22.7 per cent). Figure 3.11: PFiegurrcee3n.1t1a: gPeer coenft ahgoe uofsheohusoelhdolsd swwhhooe xepxeprieenrceidenthceebdel otwhesh obceksloinwth eshpaosct ktwso in the past two weeeeksktsh ethKNeB SKWNaBveS2 Wsuravevye 2 survey Desert Locust Floods/ Mudslides/ 2.3% Landslides 5.2% 97.7% 94.8% No Yes No Yes Livestock Diseases 22.7% 77.3% No Yes Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Source: KNBS Survey on Socio Economic Impact of COVID-19 on Households-Wave 2 Further, the County faced the following COVID effects: Further, the Coau)nGtya rfisascaeCdo tuhnety fioslltohewilanrgge CstOsVupIpDlie er ffoef clitvse:stock and livestock products in East and Central Africa. There was a decline in livestock in the region owing to livestock diseases; a) Garissa Couthnistyw iass tchome ploaurngdeesdt bsyupthpelicelors uorfe loifveWsatjoirc-Sko manaldia lBiovredsetroscinkc eprGoadrisuscatsu ipnpl ieEsast and Centrall iAvefsrtioccak.t o TShomeraeli aw. as a decline in livestock in the region owing to livestock b) The closure of the borders and livestock markets such as Dagahley market affected diseases; thitrsa wdeasin cothme preoguionnd. eAdls ob,yt hthe en celwossuthraet olifv eWstoacjkir-cSanomcoanltiraac Bt othredeCrO sViInDc-1e9 Gvairruisssa supplies livemsottoivcakte tdot hSeocmlosaulriea.o f the markets. c) The livelihoods of farmers and traders were further affected due to the closure of the Wednesday market (which is the main market day of the week) in Dadawa and Mogadasha. Market routes, particularly the Garissa, Nairobi and Garissa, Mombasa routes were affected by the partial lockdowns. d) During the COVID period, the f2ar4mers in Garissa lost most of their produce due to floods; the losses included funds lent to Farmer Organizations (FOs). Further, access roads to markets were destroyed by the floods. Only fruit crops for mango and lemons survived the harsh weather. Agri-Food Constraints Faced in the County Among the key constraints the County faces include: Page 38 of 62 Agriculture, Livestock and Fisheries b) The closure of the borders and livestock markets such as Dagahley market affected trade in the region. Also, the news that livestock can contract the COVID-19 virus motivated the closure of the markets. c) The livelihoods of farmers and traders were further affected due to the closure of the Wednesday market (which is the main market day of the week) in Dadawa and Mogadasha. Market routes, particularly the Garissa, Nairobi and Garissa, Mombasa routes were affected by the partial lockdowns. d) During the COVID period, the farmers in Garissa lost most of their produce due to floods; the losses included funds lent to Farmer Organizations (FOs). Further, access roads to markets were destroyed by the floods. Only fruit crops for mango and lemons survived the harsh weather. 3.3 Agri-Food Constraints Faced in the County Among the key constraints the County faces include: i) Comparatively low road networks in comparison to other counties, critical for access to input and output markets. ii) Need to undertake livestock farming as a business and not just for cultural purposes iii) Farmers low access to quality and affordable inputs including certified seeds, water, animal feeds, artificial insemination (AI) services, fertilizers, livestock vaccination and mechanized ploughing services by County tractor hire services. iv) Dependence of rain fed agriculture despite frequency in extreme climate conditions, such as drought episodes, delayed and erratic rains, floods, and high temperatures among other climate shocks, v) Low productivity due to poor natural resource management vi) Water scarcity which is a constraining factor that limits productivity for both livestock and food crops production vii) Low livestock, livestock products and food crops marketing opportunities necessary for improved incomes viii) Low commercialization of farming where majority of farmers practice farming for subsistence purposes and as a hobby rather than a business. ix) Low adoption of early-maturing plant varieties, water harvesting, and post-harvest storage that would increase farmers returns x) Desert locusts’ infestation, Floods/ Mudslides/ Landslides, and Livestock Diseases xi) Low livestock and crops processing and value addition opportunities among small scale farmers xii) Slow uptake of digital platforms to market agricultural produce. xiii) Inadequate extension and veterinary services xiv) Farm losses and post-harvest waste. 25 Socio-economic status of Garissa County with COVID-19 The above challenges combined will lead to the overall impact of reducing farm output, farmer incomes and increasing the vulnerability of households to food insecurity and climate variability particularly flood and drought episodes. 3.4 Opportunities of COVID-19 in agriculture sector An assessment of the sector linkages to other sectors highlights that the sector is enabled by: i) Businesses/ MSMEs: Businesses and MSMEs are crucial in providing inputs and requirements to the agricultural sector. The sector would facilitate the efficient access to ii) Transport, Storage and ICT sectors iii) Financial and insurance activities iv) Accommodation Food services v) Manufacturing: The manufacturing sector plays a crucial role in agro-processing. Agricultural inputs also contribute to the processing of other manufacturing commodities The County has opportunities in: a) Developing County-private partnership in enhancing agroprocessing and value addition and Linking farmers to product markets b) Access to quality and affordable inputs including certified seedlings, water and hay for animals, AI services, fertilizers, livestock vaccination and ploughing services by County tractor hire services. c) In addition to agroprocessing, provision of storage and cooling facilities particularly at collection points to minimize spoilage and post-harvest losses particularly for milk. d) Uptake of digital platforms to build capacities of farming households in modern agricultural technologies; access advisory and information services; and market agricultural produce. e) Expansion of water harvesting projects and sustainable irrigation in the County through partnership with development partners with the aim of increasing food productivity at the County. f) Scaling up conservation agriculture, post-harvest management, planting drought- tolerant, early maturing varieties and modern crop varieties, and agro-forestry. g) Increased livestock production through: - routine vaccination, deworming and vector control to maintain animal health; destocking and change of livestock species; decentralized veterinary services; disease surveillance; storing and conserving pastures and fodder; capacity building on animal management and training on preservation and value addition techniques; controlled movement of animals ; capacity building on stock route and market inspection ; and improved milking hygiene and animal housing. 26 Agriculture, Livestock and Fisheries h) Adoption of drought resistant livestock pastures/fodder and crops and also fodder and feed conservation i) Rearing livestock breeds adapted to drought j) Livestock Production for Niche Markets k) Adoption of natural resource management to include soil and water conservation, tree planting, changing of crop type and water harvesting. l) Enhance supportive services to include early-warning systems, financial services such as insurance schemes for livestock / crop and credit facilities, advisory and information services through extension and training. m) Enhancing farmers technical capacities to act on advisory information received n) Improved crop and livestock emergencies surveillance systems in the County. o) Strengthening farmers’ associations and cooperatives as an additional solution to marketing challenges 3.5 Emerging Issues i) Environmental degradation has reduced productive capacity of farms leading to increased risks to food insecurity and reduced farmers income. ii) Climate change, manifested in increased frequency and intensity of extreme weather conditions such as floods, droughts and pest invasion 3.6 Recommendations To successfully build resilience and enhance growth of the agriculture sector, the County will: i) Develop partnership with the National Government, NGOs, Development partners, Research Institutions and the Private sector in establishment of fully equipped meat and leather processing plants and horticultural processing and value addition plants to include banana, mango and watermelons processing plants. ii) Establishment of abattoirs and cold storage facilities (on-site cold storage and refrigerated vehicles to transport the meat to markets in Kenya and abroad). iii) Invest in access roads to enhance linkage between farms and markets. Extensive rural road infrastructure plays a central role in provision of affordable access to both markets for agricultural outputs and modern inputs. Garissa’s rural access index (RAI) fairs poorly at 24 per cent compared to the national average of 69.4 per cent. There is thus need for the County to invest in access roads to enhance linkage between farms and markets. Other crucial market infrastructure includes lighting and water services to facilitate trade activities. iv) Digitize the agri-food sector to enhance: - training and building capacities of farming households in modern agricultural technologies, provision of advisory and 27 Socio-economic status of Garissa County with COVID-19 information services, marketing agricultural produce at a wider scope beyond the County level, and improving access to innovative support services including credit and insurance services. v) Access to quality and affordable inputs including: - water, animal feeds, AI services, fertilizers, livestock vaccination and ploughing services by County tractor hire services. In addition, there are opportunities in enhanced access to agriculture, livestock and fisheries extension services for improved agricultural and livestock production. vi) Promote uptake of agricultural insurance, particularly livestock insurance among households. With recurrent natural disasters like droughts, floods, land/mudslides, pest and disease outbreaks in ASALs, it is crucial that the County seeks affordable index-based insurance from development finance institutions (DFIs) to safeguard livelihoods. vii) Empower livestock producers to participate in high-value product markets, such as, niche markets for livestock products (e.g. organic milk and meat). This will create value for the County in several ways including: - farmers accessing premium process for the produce; rearrangement of the food chain to marketing structures that bypass exploitative middlemen; steady revenues for farmers; and increased economic incentives in adopting SLM practices. viii) Diverse production in the County to suite the high heterogeneity of land associated with ASALs, the selection of products which fit in each niche and into each climatic cycle. Potential areas of production include horticultural production (mainly fruits), beekeeping and fisheries and aquaculture ix) Invest in sustainable irrigation and water pan projects for provision of water to be used for livestock, food and horticultural production in the County through partnership with development partners. Current completed include: - Galma Water Pan and Irrigation Project, Waldena water pan, Hirimani DM and Walestoka water pan. To support expansion of sustainable irrigation, there is need to promote development of Irrigation Infrastructure and technologies in the County. x) Establish programmes for surveillance of disasters, such as extreme weather conditions and livestock disease, at the County level equipped with relevant technical specialists and finances to effectively prepare, respond and prevent risks. The County will mitigate disasters, such as those related to floods, through institutional capacity development, vulnerability analyses and updates, monitoring and early warning systems, and public education. xi) Strengthen agricultural cooperatives through effective stakeholder engagement and implementation of interventions for more sustainable models of financing and customized training of cooperative members. 28 4. Water, Sanitation and Hygiene 4.1 Characteristics of the sector Garissa County has a water scarcity problem with only 23.8 per cent of the population having access to safe water. Access to piped water is limited to the sub-county headquarters where approximately 27,725 households have connection. The main source of water in the county is River Tana and seasonal Laghas. Other water sources include 25 shallow wells, 109 boreholes, 195 water pans and one dam. The average distance to the nearest water point is 25 km. Water supply is by the Garissa Water and Sewerage Company, GAWASCO, which supplies water to approximately 27,725 households in Garissa Town and its environs. The proportion of the population of the county that uses pit latrines as a means of sanitation is 46.76 per cent while 2.6 per cent use VIP latrines. Majority of the population (50.63%) uses other means of sanitation such as bushes. There is only one sewerage connection that is currently being constructed in Garissa town. However other towns in the county do not have sewerage connections. Over the last two years, the County has suffered from consistent drought and lack of water. During the FY 2019/20 they received an allocation of Ksh 1.4 billion from the national Government for the sector. The County has provided 50,000 cubic meters of water within sub-Counties using dams. The dams have been solarized. Note: the sub-Counties do not have any permanent water sources. Currently, the County has 85 per cent water supply/ coverage due to water programs being implemented by development partners2 such as drilling boreholes; however, the county foresees a water shortage soon due to competing needs for water by the human population and livestock. The challenges being faced is that the boreholes were submerged due to floods thus requires repairs 4.1.1 Access to source of water by households The major source of water for drinking utilized by households in the county is water from dug well(unprotected) (34.8%), piped water into plot/yard (34%) and piped water (public tap/standpipe) (11.6%). Water from unprotected dug wells and piped water into plot/ yard are also majorly used for other domestic purposes at 34.99per cent and 34per cent respectively. Additionally, most households in rural areas uses water from unprotected wells (53.3%), piped water (public tap/standpipe) at (14.5%) and piped water into plot/ yard (9.5%). While majority of urban households relies on piped water into plot/yard at 81.3 per cent, piped water into dwelling at 10.2 per cent. Households in peri-urban obtain their drinking water from surface water(rivers/dams/streams/pond/lake) at 81 per cent followed by piped water (public tap/standpipe) at 19.1 per cent. 2 For instance, Partnerships with UNICEF through the Kasha Water Supply has enhanced access to water for residents. 29 Socio-economic status of Garissa County with COVID-19 FigureF 4igu.1re: 4A.1c: Accecessss toos osuorcuesrocf ewsat eorfb ywhaoutsehro lbdsy households 5.9 Surface water - river/streams/pond/dam/lake/cannal/irrigation channel 81.0 0.2 Vendors - cart with small tank/drum/bucket 3.9 Vendors - tankers-truck 2.4 53.3 Dug well - unprotected well 0.3 Dug well - protected well 11.3 Tubewell/borehole with pump 14.5 Piped water - public tap/stand pipe 6.1 19.1 9.5 Piped water - piped into plot/yard 81.3 1.2 Piped water - piped into dwelling 10.2 0 10 20 30 40 50 60 70 80 90 Peri urban Urban Rural Other Domestic uses Drinking Source:S KouNrceB:SK N2B0S12501/52/2001166 Combating COVID-19 pandemic has already placed high demand for water for both Combatdionmge sCticOuVsaIgDe -in19ho upsaehnodldes,mheical th acasr eainlsrteitautdioyn s,plleaarcneindg ihnsitgithut iodnse,mmaarnkedt plfaocers , water for both and other public places. Water also remains important to other sectors of the economy such domestiacs uagsraicgueltu irne ahnoduinsdeuhstoriladl sus, ahgee,aaltmho ncgaroteh einrss. tWitituhttihoenpsla, nlneeadrnrei-nopge niningstoitf uscthiooonlss, marketplaces, and othaenrd puupbcolmicin pgllaocwersa.i nWseaatseorn samlseoa nrsemthaat itnhes ipmrespsuorretoannwt atote rortehsoeurr cseescwtoillrbse ohfi gthh,e economy such this therefore means that the demand for water will be high and if the supply will be low, as agrichuolutsuerheol dasnadre inlikdeulysttorifaill utosaobgsee,r vaemCOoVnIgD -o19thperervse.n Wtionitmhe tahsuer epslaofnhnaend wreas-hoinpgening of schools and upcwohmichinmgay lionwtu rrnaleinad stoeahisgohntrsa nmsmeisasinons otfhCaOtV ItDh-e19 p. ressure on water resources will be high, this theTroefeonrsuer emcoenatinnusi ttyhoaf tq utahliety dweamterasnupdp lyfo, trh ewreaitsenre ewdiflolr bthee hcoigunhty atno din viefs tthinew sautepr ply will be low, harvesting and storage facilities both at household and institutional level, this may include househosuldppso ratirneg slcikhoeollys itnob ufaildilin gtor aoinbhsaerrvevseti nCgOanVdIDsto-r1a9ge psrtreuvcteunretsioinns cmhoeoalssfurormest hoef hand washing which mscahyoo ilns ttruucrtnur eleraodof ttoop sh, isguhpp torrtainngsmhouisseshioolnds oinf CraOinVwaItDer-1h9ar.v esting during rainfall times. Other interventions may include digging boreholes, supply of water to households To ensutrheat ceoxpnetriiennuceistyw aotfe rqsucaarcliittyy. water supply, there is need for the county to invest in water harvestiTnhger eafnorde, sfotroerqaugaelit yfaincialcitcess to water the county government can waive or reduce thewater bills for urban househoildessw bhootuhs eastp hipoedusweahteor lads waenllda sinsusptpitourttwioantear lv elnedvoersl, inthis may include supportaicncges s ctohocloealsn isnaf ebwuailtedrinatg arareidnu chedarcvoests. tTinhisg wainll dm esatnorfianagnec iasltrsupcptourtretos winat esrchools from the school ssterrvuiccetucormep raonioesf.toOpthse,r slounpg-pteormrtimnegasures include inclusion of both rural, urban, andperi-urban dwellers into decision making in hreoguarsdetho owladtesr mina nraageinmwenat taendr ghoaverrvneansctei.ng during rainfall times. OAtchceesrs itnotiemrpvreonvetdioannsd umnaimyp irnovceluddsoeu drciegsgoinf wg abteorrbeyhhooluesse, hsouldpsply of water to households that experiences water scarcity. Page 43 of 62 Therefore, for equality in access to water the county government can waive or reduce the water bills for urban households who uses piped water as well as support water vendors in access to clean safe water at a reduced cost. This will mean financial support to water service companies. Other long-term measures include inclusion of both rural, urban, and peri-urban dwellers into decision making in regard to water management and governance. 4.1.2 Access to improved and unimproved sources of water by households Clean and safe water is essential for good health and goes a long way in ensuring reduced infections. Access to improved drinking water3 is high in the county among households at 92.2 per cent, improved source of drinking water. Only a small portion of the households have access to unimproved source at 7.8 per cent unimproved sources of water. Both male 3 improved sources of water include water from the following sources Piped water - piped into dwelling, Piped water - piped into plot/yard, Piped water - public tap/stand pipe, Tubewell/borehole with pump, Dug well - protected well, Dug well - unprotected well, Water from spring - protected spring). Unimproved sources of water include Water from spring - unprotected spring, Rain water collection, Vendors - tankers-truck, Vendors - cart with small tank/drum/bucket, Vendors-bicycles with bucket, Surface water river/streams/pond/dam/lake/can- nal/irrigation channel Bottled water). This is according to WHO and UN classification of sources of water 30 Clean and safe water is essential for good health and goes a long way Winateenr sSuarniintagtiorne daundc eHdygiene infections. Access to improved drinking water3 is high in the county among households at 92.2 per cent, improved source of drinking water. Only a small portion of the households have access to unimproved source at 7.8 per cent unimproved sources of water. Both male aanndd ffeemmalle headed housseehhooldldssa assw weelllla assb booththr urruarl,alu,r ubrabnaann adnpde rpieurrib uarnbhaonu hseohuosledhsohladvse have ssimimiillaarr hhiigghheerrc hchanacnecseos foafc aceccssestso timo pimropverdovderdin kdirnignkwiantge rwsaotuerrc esoouf rwcaet eorf awsastheorw ans isnhtohwe n in thfigeu firegubreelo bwe.low. FFiigguurree4 4.2.:2A: cAccecssetsos itmop irmovpedroavndedu nainmdpr uovneidmspourrocevseodf swoauterrcbeys hoofu wseahtoeldrs by households Access to improved and unimproved sources of water by households Households 92.23 7.77 Rural 36.68 63.32 Urban 97.59 2.41 Peri-urban 19.05 80.95 Male (HHs) 92.46 7.54 Female(HHs) 92.5 7.5 0 20 40 60 80 100 Improved water source Un improved water source SSoouurrccee:: KKNNBBSS2 200151/52/0210616 Inequalities in access to safe and clean drinking water may put households at risk of Icnoenqturaacltiitniegsi nifne caticocuessds isteoa sseasfea sawnedl l calseamna kderitnhkeihnogu sweahtoeldr smleasys opbuste rhvaonucseehoof lCdOsV aIDt -r1i9sk of cmonetarsaucrteisngo finhfaencdtiohuygsi denisee.aOsense ams iwtigeallt iaosn mmaekaes uthree thhoautsmehayolbdes luensdse orbtaskeernvabnyceth oef cCoOunVtIyD-19 mtoeainscurreeass eofa hccaensds htoygimiepnreo.v eOdnwe amteitrigsoautirocen, minecalusduerec otnhnaet cmtinagy tbhee uhnodueserthaokldesn wbiyth thpeip ceodunty tow aitnecr,reianscere aascecetshse tdoe vimelopprmoveendt owf aitmepr rosvoeudrcseo, uirncecsludofe wcaotnenr eecstpinecgi atllhye inhoruursaelhaorledass .with Long term measure to support access to water all households is to have both male and pfiepmedal ewahteeard, eidnchroeuasseeh tohldes dteovebloeppmaertnto fofw iamteprromvaenda gsoeumrecnets/ goofv ewrnaatenrc eestpeeacmialalyn dini nrural adreecaiss.i oLnomngak tienrgmin mweaatesrumrea ntoa gseumpepnotr.t access to water all households is to have both male and female headed households to be part of water management/governance team and in Other important consideration is to have separate water drinking point for livestock, ddeicffiesrieonnt mfroamkinthge inh owuasteehro mld awnaatgeer mdreinnkti.ng water sources to minimize water contamination Oatshwere llimaspocorntaflnictt coovenrsiwdaetreartiroenso uisr cteo. Ohtahveer lsoenpga-treartme mwaeatesru redsrianrkeintog apvooiindta gforirc ullitvuerastl ock, activities along the upstream to minimize water pollution. different from the household water drinking water sources to minimize water contamination as well as conflict over water resource. Other long-term measures are to avoid agricultural aActcicveitsisest oalwonagt ethr etr uepasttmreeanmt mtoe mthiondims ize water pollution. Access to water treatment methods Majority of the households (81.3%), both male (79.4%) and female (87.2%) do nothing to 3 improved sources of water include make it safe for drinking. Otherw amter from the following sources Piped water - piped into dwelling, Piped water -piped into plot/yard, Piped water - public tap/stanedtphipoe,dTsu boefw ewll/abotreerh otlerewaithtmpuemnp,t Daurgew bello-ilpirnotgec taednwde lcl,hDluogrwinella-tion. Suenepr otthecet efidgwuerll,e Wbaetelor wfrom spring - protected spring). Unimproved sources of water include Water from spring - unprotected spring, Rain water collection, Vendors - tankers-truck, Vendors - cart with small tank/drum/bucket, Vendors- bicycles with bucket, Surface water river/streams/pond/dam/lake/cannal/irrigation channel Bottled water3). This is according to WHO and UN classification of sources of water Page 44 of 62 31 Socio-economic status of Garissa County with COVID-19 FFiigguurree4 4.3.:3A:c Acecscsetosss atfoe sdrainfeki ndgrwinakteirnbgy whoautseehro bldys households 0.3 let it stand and settle 0.4 0.2 Use water filter 0.3 6.8 Add bleach/Chlorine 8.9 3.6 Figure 4.3: Access to safe drinking water by households 11.3 Boil 11.0 0.3 9.2 let it stand and settle 0.4 81.3 Do nothing 79.4 0.2 Use water filter 0.3 87.2 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 6.8 Add bleach/Chlorine 8.9 3.6 Female HHs Male HHs Households 11.3 Boil 11.0 9.2 Source: KNBS 2015/2016 81.3 SoDuorncotehi:n gKNBS 2015/2016 79.4 87.2 Volumes for water used by households in a month 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 4M.1o.s3t hoVusoelhuolmdseuss efobre twweaetner1 0u0s0e-1d9 9b9yl ithreosuosfewhaoteldr sin itnh eap masot one month at 39.8 percent which is the same Fevmoallue HmHse usMeadle HbHsy ruHroaulsehhooldus seholds per monntthh at 48.3 per cent, compared to 38.1 per cent utilized by urban households and 38.1 per cent used by peri- MSuoroubsracten :hKhoNouBusSsee2h0ho1o5ll/dd2ss0. 1u6Asded ibtieotnwalelye,nm 1a0jo0r0it-y19o9f 9m lailterehse oadf ewdahteoru sienh otlhdes puasest boentwee menon10th0 0a-t 39.8 pV1eo9rl9 uc9meenlistr fewosrhwoicafhtew riasut setehrdepb seyarhmomueos nevhtoholludamst ien4 3au.ms7eodpne tbhryc reuntrawl hioleusfemhoaledsh peaedr emd ohnotuhs eahto 4ld8s.3u speesr cent, cMboeomsttwpheaoerunese1dh0 o0tldo0s -31us98e9.1b9 epltiwtereree snceo1nf00wt0 -au1tt9ei9rl9iiznleitrdteh seboypf awusartteboraninne tmhheoopunatsshet hoanotel4dm3s.o 2natphnedart c33e98n.8.t1.p perer cent used by peri- cent which is the same volume used by rural households per month at 48.3 per cent, ucrobmapnar ehdotuo s3e8h.1oplders.c eAntdudtiiltizieodnbaylluyr,b amn ahjoousreithyol dosf amnda3l8e. 1hpeeardceendt husoeudsbeyhpoelrdi-s use between 1000- 1uF9ri9bga9unr elhiot4ur.se4es:h oVolodfsl u.wmAadedtsietioro fnpawlelyar,t emmraujoosnreittydhob faytmh ao4leu3s.he7eh apodeleddrs hiconeusnaethm owlodnshtihulsee fbeemtweaelne 1h0e00a-ded households uses 1999 litres of water per month at 43.7 per cent while female headed households uses bbeettweeeenn10 0100-019099-1li9tr9es9Vo lfoiwlturameteser ooinff twwheaatpteaersrtu osinneed tmbhyoenh tpohauasstet4 ho3o.n2ldeps emirncotehnnett.hpa astt m43on.2th per cent. Figure 4.4: Volumes of water used by households in a month Figaubroev4e.540:0V0olliutrmeses of water used 5b.y23hous 1e0h.o89lds in a mo2n1th.78 3.3 8.66 Volume of wa3te.9r51u.6s8ed by households in the past monthbtwn 4000 to 4999 litres 9.123.461.207.489 above 5000 litres 5.23 21.78 3.3 8.66 12.4 btwn 3000 to 3999 litres 12.59 3.951.68 11.87 23.81 btwn 4000 to 4999 litres 9.126.46 9.913.46.274 19.85 btwn 2000 to 2999 litres 12.4 18.38 22.35 btwn 3000 to 3999 litres 1112.8.579 38.19.91 10.03 23.81 19.886.46 19.85 39.76 bbtwtwn n201000to02t9o 48.28 9919lit9re9slitres 18.38 22.35 23.6719.88 38.1 35.7110.03 4433.1.782 8.66 39.76 btwn 48.28btwn1050000tot1o999999litrlietsres 6.31 9.95 23.672.38 35.7111.56 43.728.66 27.85 43.18 btwn 500 to 999 litres 9.952.38 6 Less than 500 litres 1 ..3261.5764.191.56 27.85 2.76 2.65 Less than 500 litres 1.65 4.9 4.442.65 0 4.44 10 20 30 40 50 60 0 10 20 30 40 50 60 Female (HHs) Male (HHs) Peri_urban Urban Rural Households Female (HHs) Male (HHs) Peri_urban Urban Rural Households Soouurcrec:eK:NKBNSB2S01250/21051/62016 Source: KNBS 2015/2016 From the above figure, most households utilize large volPuamgee4s 6oof fw6a2ter per monthly with most households using between 1000 to 1999 litres of water (39.8%Pa) gfeol4lo6woefd6 b2y rural households (48.3%) urban households (23.7%) and peri urban (35.7%). With the opening of schools, it means more water will be needed by the institutions. Water remains a 32 Water Sanitation and Hygiene From the above figure, most households utilize large volumes of water per monthly with scmaorcste hcooumsemhoodldistyu asinndg ibne tween 1000 to 1999 litres of warural households (48.3 per pcleancte)su orbra mn ohnouthsesh wolhdesr(e2 3w.a7tpere tiesr s(c3a9r.c8e,p ter cent) followed byr cent) and pheisri murabya nha(3v5e. 7anp eerffect once nfat)m. Wiliieths tahnedo pheinndinegr otfhsecmho ofrlso,mit mobesaenrsvminogr eCwOaVteIDr w-1i9ll bperenveeendteidonb ygtuhiedeinlisntietus.t ioCnosr.rect utWilaizteartiroenmsa oinfs waastecar rrcescooumrcmeos dsihtyoaunld bine pelamcepshaosr imzeodn tahts hwohuesreehwoladtesr’ liesvsecla, rsciem, tihlaisrlmy,a tyhere ish naeveda nfoerf cfeocntsoenrvfamtioilnie sofa nwdatheinr dceartcthemmenfrto amreoabss.e rving COVID-19 prevention guidelines. Correct utilizations of water resources should be emphasized at households’ level, similarly, 4t.h1e.r4e isDneisetdafnorcceo cnosevrevarteiodn toof wwaatetrecra stcohumrecnet aarneads .average time spend to and from Distanctheec owvaertedr tsouwracter source and average time spend to and from the water source MMaajojorriittyy ooff tthhee hhoouusseehhooldlds sb obtohthru rrualr,aul,r buarnb,aann,d anpedr ip-uerrbi-aunrcboavne rcsolveesrsst hleasns 1th00anm 1e0tr0e smtoetres tow wataetresro suorucersceast a9t5 9.65.p6e rpecre nctenmte maneinagnitnhge ythheayv ehawvaet ewrawteitrh iwn itthheinir tphreemir ispersemorisceloss oert oclose their compounds. Only a small portion of households covers more than 500 metres to water tos otuhreciers caotm4.p4opuenrdcse.n Ot nanlyd a1 .s2mpaelrl cpeonrttriuorna lo. f households covers more than 500 metres to water sources at 4.4 per cent and 1.2 per cent rural. FFigiguree4 4.5.5: :D Distiasntcaenccoev ecroedvebryehdo ubsyeh hooldus stoehanodldfrso mtow aantedr fsroourmce swater sources 4 Households 96 1 Rural 99 11 Urban 89 Peri urban 100 0 20 40 60 80 100 120 less than 100 metres Above 500 metres SoSouurrccee:: KKNNBBSS 22001155/2/2010616 If water is available to households, schools, health institutions within the shortest distances Ifp wosastiebrle i,s iat veaaislialybleen tcoo uhroaugseeshooblsdesr,v sincghohoalnsd, hheyaglitehn eintshtuitsumtiionnims iwzinitghiinnf ethcteio snhso.rItneslet adrinsitnagnces poinssstitbulteio, nist, eitamsilinyi meinzecsourarategseso fosbcsheorovlindrgo phoauntsd ahmyognigengei rltsh. uWso meinimheiazdinegd hinoufescethiolnds. In leaarrendinisga dinvasntittaugteiodnins, aict cmesisntiomdizreinsk irnagtews aotef rswchitohoinl dshroorpteosuttsd isatmanocnegs agnirdlst.h Wis ommayenm hakeeaded htohuesmehvoulldnse raarbel editsoadcvoanntrtaacgtiendg inCO aVccIDes-1s 9toa dsrwinekllinags wotahteerr winiftehcitnio ushs odritseesats desis. tTaoncseusp apnodrt this hand hygiene among households there is need to have water supply closer to households mhaeya dmedakbey twhoemme nv.ulnerable to contracting COVID-19 as well as other infectious diseases. To support hand hygiene among households there is need to have water supply closer to hAouccseehssoladns dherealdiaedb ibliyty woofmweant.er sources Majority of households in Garissa County must rely on the main source of drink water all year round at 95.5 per cent, therefore in case of the source drying up, households will lack 4w.1a.t5e r reAscuclteinsgs inatnodn orneloibasberivliatnyce oof fwCaOtVeIDr -s1o9umrecaessu r es of hand washing. On the other hand, most households must go to fetch drinking water from the sources per day at 17.4 Mpaejrorcietnyt ,ofr uhroaul sheohuoseldhso lidns Gatar1is4s.8a Cpeoruncetny tmaundst urreblyan onh otuhsee hmoaldisn astou8r8c.9e opfe rdrciennkt .wTahtiesr all yemaera rnosutnhde raet m95a.y5 bpe rm coernet,o tfhienrtefroarceti oins cawsieth oof theer shoouursceeh dolrdyimnge mubpe, rhsoiunseahreoalsdsw wheilrle lack wwataeter rressouulrtciensg ianreto snhoanre odb, stehrivsamncaey olfe aCdOVtoIDin-c1r9e amseeaosunreinsf eocft hioannsdo wf aCsOhVinIDg.- 1O9n wthhee roether hand, most households must go to fetch drinking water from the sources per day at 17.4 per cent, rural households at 14.8 per cent and urban households at 88.9 per cent. This means there may be more of interactions with other household members in aPraegaes 4w7heorfe6 w2ater sources are shared, this may lead to increase on infections where COVID-19 guidelines of social distance and avoidance of crowded place may not be observed. 33 Socio-economic status of Garissa County with COVID-19 COVID-19 guidelines of social distance and avoidance of crowded place may not be Ito ablsseorv iemd.plies that households may not be having water storage facilities that can minimize nIutmalbsoeri mopf lireispsth taot hwoautseerh oplodsinmtsa yinn oat dbaeyh, atvhienrgewfoarte rthsteoyra mgeafya cbileit iaest rthisakt coafn wmaitneimr iszheortages dnuurminbge rdroyf mriposnttohsw.ater points in a day, therefore they may be at risk of water shortages during dry months. FFiigguurree4 4.6.:6A:c Acecscseasnsd arenliadb irlietylitaobwialtietrys toou rwceastbeyrh soousuerhcoeldss by households In which season do you rely on the How many times in a month do your source of drinking water? household fetches water? 4.46 Household 14.79 84.69 Rural 17.44 82.56 Urban 9.49 88.9 95.54 Peri-urban 100 0 20 40 60 80 100 120 all year Only dry only rain Per Day Per Week Per Month Per Year SSoouurrcce: KNBBSS2 021051/52/0210616 SoSuorcuer:cKeN: BKSN2B0S15 2/2001156/2016 TToopp inintteerrvveennttioionnssa arerep prortoetceticotnioonf othf etheex isetxinisgtimngaj omr awjoarte wr asoteurrc seosufrocrehs ofuosre hhooldusseahnodlds and development of new water sources, this may include rainwater harvesting at individual and dienvsetiltouptiomneanl lte voef ln. Perwo twecattioenr soof uwracteesr ,c tahtcish mmeanyt ianrecalus.de rainwater harvesting at individual and institutional level. Protection of water catchment areas. Access to sanitation Access to sanitation is very important since it can help to detect the genetic residues of 4d.i1s.e6as esAinccweassste twoa tsear nasittahotsioe nwho are infected are thought to shed traces of the virus in faeces thus prompting for immediate action from the health officials. There is no sewerage Apclcaenstsi ntoa llsathneitmataijoonr tiosw vnesrya nidmtpraodritnagncte snitnrecse init tchaenc ohuenlpty .toM daejotreictyt othf eth geehnoeutsiech roeldssidues of d(is4e6a.1sepse rinc ewnat)stheawveatneor taosil etht ofasceil iwtyh; oth aisreis imnfoerceteadm oanreg trhuroaul ghhotu steoh sohldesd( 6tr9a.4cepse or fc ethnte) .virus in faOencetsh ethouths eprrhoamndp,tiunrgb afnorh iomusmeheodldiasteu saectpiiot nla ftrrionme wthithe hsleaablt(h2 3o.ffi9 pciearlsc.e nTth)efroell oiws endo bsyewerage improved pit latrines (17 per cent) and flush to septic tank at 7 per cent. plant in all the major towns and trading centres in the county. Majority of the households (46.1%) have no toilet facility; this is more among rural households (69.4%). On the other hFaingudr,e u4r.b7a:nA chcoeusssetohosaldnsit autsioen pinit Glaatrrisisnae Cwoiutnht yslab (23.9%) followed by improved pit latrines (17%) and flush to septic tank at 7 per cent. Figure 4.7: Access to sanitation in Garissa County No facility/bush/field 46.10.9 69.4 Pit latrine without slab 11.01101.5.4 Pit latrine with slab 9.9 14.6 23.9 Ventilated improved pit latrine 3.5 8.1 17.0 Flush to somewhere else 0.30.9 Flush to pit (latrine) 5.9 18.3 42.2 Flush to septic tank 1.44.0 Flush to piped sewer 0.20.7 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Urban Rural Households Page 48 of 62 SSoouurrccee: :K NKBNS B20S1 52/2001156/2016 Access to improved and unimproved sanitation Access to improved sanitation is very important in maintaining hygiene and keeping infectious diseases away, good sanitation can help to detect the genetic residues of diseases in wastewater as those who are infected are thought to shed traces of the virus in faeces thus prompting for immediate action from the health officials. Majority of the households have access to access to improved sanitation facilities at 53.9 per cent, improved sanitation includes (Flush to piped sewe3r4, flush to septic tank, flush to pit (latrine), flush to somewhere else, flush to unknown place, ventilated improved pit latrine, pit latrine with slab, pit latrine without slab). Only a small proportion have access to unimproved sanitation at 46.1 per cent these include (Composting toilet, bucket toilet, hanging toilet/hanging, no facility/bush/field, others). Male headed households have a higher access to improved sanitation at 59.85 per cent compared to female headed households at 53.8 per cent. Figure 4.8: Access to improved and unimproved sanitation by households Households 53.9 46.1 Male(HHs) 59.85 40.15 Female (HHs) 53.84 46.16 0 20 40 60 80 100 120 improved unimproved Source: KNBS 2015/2016 Page 49 of 62 No facility/bush/field 46.10.9 69.4 Pit latrine without slab 1111.010.5.4 Pit latrine with slab 9.9 14.6 23.9 Ventilated improved pit latrine 3.5 8.1 17.0 Flush to somewhere else 0.30.9 Flush to pit (latrine) 5.9 18.3 42.2 Flush to septic tank 1.44.0 Water Sanitation and Hygiene Flush to piped sewer 0.20.7 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Urban Rural Households 4.1.7 Access to improved and unimproved sanitation AScocuesrcse :toK NiBmSp2r0o1v5e/d2 0s1a6nitation is very important in maintaining hygiene and keeping inAfcecetisosutso dimseparsoevs eadwany,d guonoidm sparnoitvaetdiosna cnaitna htieolnp to detect the genetic residues of diseases inA cwceassstewtoatiemr parso vtehdossea nwithaoti oanrei sinvfeecrytedim aproer ttahnotuginhtm taoi nsthaeindin tgrahceygs ieonf ethaen vdirkuese ipnin fgaeces thinufse cptriooums pditsienags efosra iwmamy,egdoioadtes aancittiaotnio nfrcoamn thheelp hteoadltehte ocffit tche genetic residues of diseasesin wastewater as those who are infected are thought to shediatlrsa.ces of the virus in faeces Mthaujosrpitryo mopf ttinhge fhoor uimsemheodlidaste haacvtieo nacfrcoemss tthoe ahcecaeltshs otfofi ciimalsp.roved sanitation facilities at 53.9 per cent, improved sanitation includes (Flush to piped sewer, flush to septic tank, flush toM apjiotr i(tlyaotrf itnhee),h ofluusseh otlods shoamveewachceerses teolsaec,c eflsusstho itmo puronvkendoswani taptliaoncef,a cvielitnietislaatte5d3 .i9mpperroved pcite nlat,triminper,o pveitd lsaatnriitnaeti ownitinhc lsuldaebs, (pFiltu slahtrtoinpei pwedithsoewute rs,laflbus)h. Otonlsye pat iscmtaanllk ,pfrloupshorttoiopnit have (latrine), flush to somewhere else, flush to unknown place, ventilated improved pit latrine, acpciteslas ttroin eunwimithprsolavbe,d psiatnliattartinioen waitt h4o6u.t1 pslearb )c.enOtn ltyheases minaclllupdreo p(Corotmionpohsatvinega tcocielsest, tboucket touinleimt,p hroavnegdinsgan titoaitlieotn/haatn4g6i.n1g,p enro cfeanctilitthye/sbeuisnhc/lufideeld(,C ootmhpeorsst)i.n gMtaoliele th,ebaudcekde thotouilseet,holds hhaavneg ain hgigthoeiler ta/hcacnegssin tgo, inmoprfaocvielitdy /sbaunsiht/aftieioldn, aott h5e9r.s8)5. pMearle cehneta cdoemd phaoruesde htol dfesmhalvee haeaded hhoiugsheehr oaldccse asts 5t3o.8i mpeprr ocveendt. sanitation at 59.85 per cent compared to female headed households at 53.8 per cent. FFigiguurree4 4.8.:8A: cAcecscsetsosi mtop riomvepdraonvdeudn iamnprdo vuendismanpitraotiovnedby shaonuisteahtoilodsn by households Households 53.9 46.1 Male(HHs) 59.85 40.15 Female (HHs) 53.84 46.16 0 20 40 60 80 100 120 improved unimproved Source: KNBS 2015/2016 Source: KNBS 2015/2016 4.1.8 Sharing of a toilet facility Page 49 of 62 Additionally, 59.6 per cent of the households do share a toilet facility with other households, this is also similar in rural areas at 61.5 per cent and urban areas at 58.5 per cent. There are large proportions of households who share a toilet facility with 20 other households at 67.9 per cent, male headed households at 59.8 per cent, and female headed households at 58.4 per cent. Only a small proportion of households do share a toilet facility with less than 5 other households at 26.7 per cent and 30.2 per cent for male headed households and 25.7 per cent for female headed households. 35 Socio-economic status of Garissa County with COVID-19 Figure 4.9: Number of households sharing a toilet facility Figure 4.9: Number of households sharing a toilet facility Households sharing a toilet facility No of households sharing a toilet faccility Figure 4.9: Number of households sharing a toilet facility 5967 Households sharing a toile4t0.38 Above 20 houNseohoolfdhsouseholds sharing a toilet faccili5ty8 .9 Households facility 0. ..48 59.62 Between 16 and 20 households 0. 67 Above 20 households 03 4 59 40.38 . 58 .9 Households 38.47 2. .8 Rural 59.62 Between 11 to 15 households 19. 0. .4 61.53 Between 16 and 20 households 21 0. 4734. . Between 6 and 10 households 20. 14 38.47 2. Rural 41.5 Between 11 to 15 households 19 6. .8 26 Urban 3061.53 Less than 5 households58.5 2 14. 2.757. .2 Between 6 and 10 households 2 14.76 0 10 20 30 40 41.550 60 70 .8 26 Urban 30Less than 5 households 25 58.5 .7.2 yes No Female (HHs) Male (HHs) .7Households Source: KN0BS 2100152/0201360 40 50 60 70 Source: SoKuNrBcSe:2 K01N5B/2S0 126015y/e2s 016N o SourcFee:m KaleN(HBHSs) 201M5a/l2e 0(H1H6s) Households SShSoahuraricnrieng:g KoNof fBtSotoi2liel0et1t 5ffa/a2cc0iill1iitt6iieess wwitihthl alragregen unmubmebr eorf ohfo uhsoeuhsoeldhsolpdust spuintdsi viindudaivlsidautalrsis kato frisk of KcNoBnStra2c0t1in5g/2C0O16VID-19, and other infectious diseases in cases where proper hygiene i Ssonuortce: comntarinatcatiinnegd CasOwVeIlDl a-s19so, caianl dd isotathnceirn ginmfeeactsiuoruess. Sdiimseilaarsleys, WinH Ocagsueids ewlinheesrree qpuriroepseerp ahryagteiene is nSoshtaa nmriintagitniootnafifntaoecidillei ttaiessf awfcoeilriltli seauss psweocitctheiadll aCdrOgiseVtaIDnn-uc1mi9nbgce armseoesfaswhuhoriuechsse. hhSooiulmdsseilhaporulldytss, WminaHdyivOind ogutualbisdeealatibnlreissk toreoqfuire sceopancahtrriaetvceti nsganCitOaVtiIoDn-1 f9a,cailnitdieost hfoerr sinufsepceticotuesdd CisOeaVsIeDs -i1n9 ccaasseess wwhheircehp hropuesrehoygldiesn me aisy nnoott be ambAlaeci ncttoea sianscethdoieaWvseAwSeHll adsusrioncgialthdeistCaOncVinIDg-m19eapseurreiosd. Similarly, WHO guidelines require separate saWnAitSaHtionhasfacbieliteinesidfeonr tisfuiesdpevcetreyd imCOpoVrItDa-n1t9incahseelspinwghitcoh chuorubsetrhaonlsdms ismsiaoyn nooft inbfeecatibolues to 4a.cd1hi.si9eeav seeAs,cdceesspsit etoth Wis AmoSsHt o df uthreinhogu tsehheo lCdsO(V91I.D5 -p1e9r pceenrt)ioind the county do not have a AhcacnedswsatsohiWngASfaHcildituy riinngtthheier ChOouVsIeDh-o1ld9s.peOrniodthe other hand, 68.8 per cent of the WWhAAoSuHse hhoaldss bheaevne iaidcecnestsifiheaded households attif7ie teoddW vveAerSrHy i(mWpatoerrtaanndt isno ahpe) ldpuinrign gtoth cisuprber itorda3.6 peyr cimenptoratnadnt feinmahleelphinegadetod chuorubsethroalndsm nosfismCsiOiosVnsIiDoon-f1 9ion,ff meicnatflieoeuctsious ddisAisedeadasisteieossn,, adl e1s3p.i6itteep tehtrhis m s at 85.8 per cent. cise notmsotofsottfh etohfeh othuoseue shheoohlduoslsdehsha(vo9iln1dg.s5 a(pc9cee1r.s5cs%etno)t )biniont htthwea ctceooru,unnstyotaydp odaonno dtnhohatan vdheaave a hhasanandndwiwtizaaessrhh, iinmngga lfeafachcieilliaittdyye idnin hthotuehsierei hr olhudosue1sh0eo.h8lodlpdse.s rO. cnOe ntnht.etO ohntehlyeorat hhseamrnadlhl,a p6no8dr.t,8io np68eo.r8f cheopnuetsr oefhc toehlndets hhooafuvsetehheolds hhaaovcuecs eeashcsoctledosssw htaaotve erWoaAnclScyeHsas t(8Wto.2aWpteeArrS Hcaenn(dWt wasotheailrepa)1n 4dd.u2sropinaeprg) ctedhnuitsri onfgfethmisalepehreioaddeodf hCoOuVsIeDh-o1ld9s, dmoalehneoatdehdavehoaucsceeshsoltdoswaatter7,3s.o6appenrorcheanntdasnadn female heade pderhioouds eohf oCldOs VaItD8-159.8, mpearlec ehneta.ded hAodudsietihoonaldl s1 3a.t6 7p3e.6r pceenrt coefntt haendho fuesmehaoleld sh iteizha er. adveindg haocucesseshotoldsb oatth 8w5a.8te rp,esro caepnat.n dAdhdaintdional 1s3a.6ni tpizeerr ,cemnat leofh tehaed hedouhsoeuhsoelhdosl dhsa1v0in.8g apcecrecsesn tto. Obontlyh awsamtearl,l spooarptio anndof hhaonuds eshaonlditsizhear,v emale haecFacidgeuesrdse th4oo.1uw0sa:etAhecrocleodsnssl y1to0a.wt8a8 ps.2herdp ucererincgte. ntOhtenwClyhO ilaVe IsD1m-41.a29llp peorrirotcdieonnt off hfeomuaselehohledasd ehdavheo uascechesosld tso dwoater onnolyt haatve access to water, soap nor hand sanitizer.Is 8th.2er epearp lcaecne tf owr hhailned w14as.2hi npgeirn cent of femHoaulsee hhoeldasdAeccde shsotouWseAhSHolddusri ndgoC OnVoIDt -h19ave access to water, soap nory ohuarnfadc isliatyn?itizer. period Figure 4.1 8.52 45..Figure 4.01:0A:c Acecscsetsosw taos hwdausrhin gdtuhreiCnOgNV otIhNDoe-n1 aC9t aOplleVriIoDd -19 perio16d14110.23 Is there a place for handwashing in yes wateHro, suosaeph,ohladnsdAsacncietiszserto W13..A.8S .6H during COVID-19 your facility? yes only hand sanitizer per5i8od 68 8.52 yes water & soap 73 85 8.5. .8.6 yNeo 4. s, Nwoanteartoanllly 96. 14 .8 91.48 291 1 yes water, soap, hand sanitizer 10.2 3 3. .8.6 yes only hand sanitizer 1.58 68 yes water & soap 73 85 yes No Female HHs Male HH89s. Households .8.6 yes, water only . .8 91.48 29 Page 51 of 62 yes No Female HHs Male HHs Households Source: KNBS KIHBS 2015/2016 Source: KNBS COVID-19 wave 2, 2020 Page 51 of 62 36 0 0 .0 1 .0 10 0 2 .0 0 2 .0 0 . 0 3 . 0 0 0.0 10 3 .0 0 . 0 4 .0 10 2 0.0 0 4 .0 00 5 .0 20 .3 0 0 . 0 5 .0 6 .0 3 0 . 0 0 0 .0 0. .0 40 6 .0. 7 0 4 0 0 5 0 7 00 8 .0 .0 05 .0 8 .0 0 0 60 0 9 .0 .6 0 .0 7 00 9 .0 10 .0 . 0 1 0.0 0 0 .0 0 .0 70. 80 0 0.0 .0 80.0 Water Sanitation and Hygiene More of hand washing should be emphasized especially to those who are not observing hand hygiene to help decrease the spread of the virus, this should be facilitated by provision of water, soap/hand sanitizer to households 4.2 Opportunities of COVID-19 in WASH COVID-19 has highlighted the need to maintain a clean safe water, proper sanitation and hand hygiene which places more demand on water and therefore the county needs to leverage on lessons learned from COVID-19 by improving its water and sanitation coverage. 4.3 Emerging Issues The County has provided wash taps within shops in the town center as well as handwashing facilities in County and sub-County offices. The county has undertaken a distribution of water tanks, water and soaps at points of entry as well as developed hand washing booths in the informal settlements. The booths are made by students from the TVET institutions 4.4 Recommendations The recovery strategy recommends the following strategies for implementation: i) The county to increase water supply in households, institutions, and public places by fast-tracking ongoing water projects such as drilling of boreholes, construction of dams and water pans. ii) Construct water storage facilities iii) The county to promote water harvesting through roof catchments and provision of tanks to poor households iv) Fasttrack rehabilitation of the existing water sources by protection of water springs and wetlands v) The county to facilitate water tracking to households and communities during times of droughts and emergences. vi) Map out water sources and their capacity to help in the management and conservation of water resources vii) Expand and rehabilitate the existing piped water connection infrastructure to help increase access to water. There is low access to piped water which stands at 32.5 per cent in urban 12.6 per cent in rural and 6.4 per cent in peri urban areas. This means low revenue from piped water for the county government. Similarly, it also implies low access to clean and safe water which is guaranteed through piped water system. To increase piped water connectivity to households. The county government can collaborate with the private sector, Non-Governmental organization and the local community to expand the water infrastructure. 37 Socio-economic status of Garissa County with COVID-19 viii) The county to put in place a decentralized wastewater and facial sludge management plan ix) Establish water supply monitoring system for efficiency water supply and management. x) Expand sewer infrastructure to accommodate more households, currently there is low access to piped sewer among households which is 15.6 per cent urban and less than 1 per cent coverage both in rural and peri urban areas. Low connectivity to piped sewer denies the county the much-needed revenue from sanitation services as well as access to safe sanitation. xi) Improve access to safe and improved toilets in schools, health care facilities, workplaces and public places. Additionally, 69.4 per cent of rural peri urban households do not have a toilet facility. On the other hand, 42.6 per cent rural, 39.61 peri urban and 2.6 per cent urban households have no access to toilet facility. Similarly, sharing of a toilet facility with other households is common which stands at 61.5 per cent rural, 58.5 per cent urban. Toilet sharing puts households at risk of contracting COVID-19, and other infectious diseases in cases where proper toilet hygiene is not maintained. Increased access to sanitation can be achieved through collaboration between county government, national government, development partners and PPP to expand sewer infrastructure and to accommodate more households. xii) Promote the importance of handwashing and construct WASH facilities to increase access at the household level. Currently access to WASH is high among households with majority having access to water and soap at 68.8 per cent, water soap. On the other hand, 91.5 per cent of the households do not have a designated handwashing facility in their households. This may compromise hand washing hygiene of households thus making households vulnerable to contracting COVID-19. Increased access to WASH can be achieved by supporting households with access to water, soap and WASH facilities, sensitization on the importance of handwashing. Collaboration between County Government, Non-Governmental Organizations, local community and the media is important to realize increased access to WASH among households. xiii) Enforce the WASH regulation of having toilets in all public facilities such as supermarkets, hotels and banks etc. xiv) The county to organize sensitization forums on the importance of handwashing through the media and in community forums. 38 5. Manufacturing, Trade and MSMEs 5.1 Characteristics of the sector 5 Manufacturing, Trade and MSMEs 55..21 CMhaarnacutfearicsttics of the sectora) Manufacturuinrginsegc stoerctor Garissa County has 157 establishments involved in manufacturing activities which comprise Goaf r2is.9sap Ceorucnetnyt hoafs a15t7o etastlaobfli5s,h4m58enftirsm insv(oKlvNeBdS i,n2 m0a1n6u).facIntutreinrmg ascotifvsitiizees, w1h4i2ch( 9c0o.m6ppreisrec ent) oafr e2.9m ipceror cwehnitl eof1 a5 t(o9t.a4l poef r5,c4e5n8t )fiarrmess (mKaNllB. ST,h 2e0m16a)i.n Idnr ivteerrms so foft hseizee,c o14n2o m(9y0o.6f%th) earceo unty miniclruod ewhaigler ic15u lt(u9r.4e%()4 3arep esrmcaelln. tT),hes emrvaiicne sdr(i4v4ersp eorf tcheen te)coannodmmy aonf uthfaec tcuorui ngty (i3ncpluedr ec ent) a(gGrCicPu,lt2u0r1e9 ()4.3%), services (44%) and manufacturing (3%) (GCP, 2019). 5S.e2c.1to rSoef operaAccording cttoort hoef t oiopnKNeBrSati2o0n16 survey, the key sub-sectors that drive manufacturing to Ainccclourddei:ngw toe tahrein KgNaBpSp 2a0re16l s(u3r5v.e9y, tpheer kecye nsut)b,-sfeucrtnoirtus rtehat( d30ri.v9e mpearnucfeacnttu),rinFga tbor iicnactleudde:m etal wperoadriuncgt sa,ppeaxrceelp (t35m.9a%ch),i nfuerrynitaunrde (e3q0u.9ip%m),e Fnat b(r2ic1a.t4edp meretcael nptr)o,dauncdts, teexxcteilpets m(1ac2hipneerryc ent) (figure 5.1). These are some of key sub-sectors that are essential in dealing with COVID-19 aanndd eqarueipmlikeenlyt (t2o1.4e%xp)e, raienndc teexitnilcerse a(1s2e%d )a (cfitgivuitrye, 5a.1n).d Tehsepsee caiarell ysoimn ep orof dkueyc tsiounb-soefctPoerrss onal tPhraott aerceti veesseEnqtuiaipl mine dneta(lPinPgE sw)itahn CdOhVoIsDp-it1a9l abnedd sa.re Tlihkeelyk etoy epxrpoedruiecntsceu isnecfruelaisnedv aalcuteiviatdyd, ition aanndd edsprievciniagllym iann purfaocdtuucrtiinogn ionfc PluedresoMnaela Pt,rodtaeicrtyi,veli vEeqsutoipcmk eanntd (PhPoEnse)y apnrdo dhuocstpioitna,l baendds.s kins Tahned kheiyd epsropdrouccetss suisnegf.ul in value addition and driving manufacturing include Meat, dairy, livestock and honey production, and skins and hides processing. FFiigurree5 5.1.1:: SSeecctotor ro foof poepraetrioantioinnm inan mufanctufraincgturing 40.0 35.9 35.0 30.9 30.0 25.0 21.4 20.0 15.0 12.0 10.0 5.0 0.0 Textiles Wearing apparel Fabricated metal Furniture products, except machinery and equipment SSoouurrccee:: KKNNBBSS,, 22001166 5S.e2c.2to rSoefcotopre roaft oiopnerbaytsioizne by size Most establishments in Garissa County are micro in nature and operate in the wearing Mapopsat reeslta(3b5li.s9hmpeernctse nint) Ganardisfsuar nCitouurnety(2 a1r.e4 mpeicrrcoe nint) n, aatnudref aabnrdic aotpeedramtee tianl tphreo dwuecatsr,inegx cept amppacahreinl e(r3y5.9a%nd) aenqdu ifpumrneintut r(e2 (12.14.4p%e)r, acnedn tf)ab(rfiigcautreed 5m.2e)t.alS pmroadlluscitzse, dexecesptatb mlisahcmhiennetrsy only aonpde reaqtueipinmfeunrnt i(t2u1re.4(%9). 5(fipgeurrcee 5n.t2)).. Small sized establishments only operate in furniture (F9i.g5u%re). 5.2:Manufacturing firms by sector and size 39 Page 54 of 62 Socio-economic status of Garissa County with COVID-19 Figure 5.2:Manufacturing firms by sector and size 40 35.9 4350 30 35.935 3250 21.4 21.4 2205 15 21.4 21.420 12 110 9.5 5 12 150 9.5 50 0 Textiles Wearing apparel Fabricated metal products, Furniture Textiles Wearing apparel Feaxbceripctamteadcmhineetaryl parnodducts, Furniture exceeqputimpmacehnitnery and Micro Small equipment Micro Small Source: KNBS, 2016 Source: KNBS, 2016 Source: KNBS, 2016 5L.2oc.3a tioLnoocfamtiaonnu foafc tmuraingufiarmctsubryintygp fieromf psr ebmyi tsyespe of premises LCoocmamtioonnporfemmisaensuufasecdtubryinmg afnirumfasctbuyrintgypfiermosf in Garissa County are building sites and Croomadmwoonr kpsr(e4m5.i4sepse rucsendt )b,yc ommamneurfcaiacltuprreinmgis efisrm( p2r1e.4mpiesrescent), re Common premises use s in Garissa Cosuidnetnyt iarlew bituhoiludtinspge sciiatel s and rooaudtf itwaonrdksre (s4id5e.n4t%ia)l ,w cit dh sbpyecmiaal nouufacturing firms in Garissa Countyommercial tpfirt,emboitsheas t(1221.p4e%r )c,e nret s(ifdigeunretia5.l3 w). are building sites and road works (45.4 per cent), commercial premises (21.4 per cent), resiidtheontuiat lswpiethcioault osuptefictia al nd reoFsuigitdufiertenat5ni.ad3l: rweLsoiitcdhae tsnioptnieacloiwfamilt hoaunsutpfifeatcc,i tabuloroitnuhgt fafiitr, m1b2so ptbhyerap tcree1mn2tisp (eefisrgcuernet 5(f.i3g)u. re 5.3). FFiigguurree5 5.3.3: :L oLcoatcioantioofnm oafn umfaactnuurinfagcftirumrsinbyg pfirremisse bsy premises Residential without special outfit 12.0 Residential without special outfit 12.0 Residential with special outfit 12.0 RBeusiliddienngtsiaitlews iatnhdsproeacdiawl oourktfsit 12.0 45.4 BOupieldninggrosuitnedswanitdhorouat dstwanodrks 9.5 45.4 OCopmenmgerrocuianldprweimthisoeust stand 9.5 21.4 Commercial premises 0.0 5.0 10.0 15.0 20.0 2215..04 30.0 35.0 40.0 45.0 50.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Source: KNBS, 2016 SSoDouiusrtrcrceieb:: uKtNioBnSS,o, 2f20M011a66nufacturing firms by gender and size Manufacturing establishments in Garissa County are dominantly owned by males (76.1 per 5Dc.e2ins.tt4)r, ibware malD uitthiisoftnermiobaflueMsacnoumfparciste owned, wthion of M iunrgain2g3u.f9fiarpmcetrsucbreyinntg.geI nnfidrteemrrmsas nbodyf s mgiziecenrod-seizre danfirdm ss,iz7e3.6 per cent Manufacturing estabilliesh2m6.e4ntpserinceGnatraisrseafeCmouanletyowarneedd.oSmminaallnstilzyedowfinrmeds baryemalal leoswn(7ed6.1byper mal Mceannt e)s, (w1i0th0 pfeer cent) (taufacturingm easletsabcloism ble 5 hpmrisi .n1g).ents 2in3 .G9 apreisrscae Cnto.uInntyte armres doofmminicaron-tsliyz eodwfniremds b, y7 3m.6alpees r(7c6en.1t%), wairteh mfeamleaolewsn ceodm, wphriilsein2g6 .243p.9er pceern tceanret. feInm atelermows noefd .mSimcraol-l ssiizzeedd ffiirrmmss,a r7e3.a6ll poewrn ecdenbty are mTaableles 5(.110:0Dpisetribceuntito)n(otafbMle 5.1).male owned, while 26.4 paenru fcaectnutr iangref irfmems ablyeg oewndneerda.n Sdmsizaell -sNiz(edpe fir rcmenst )are all owned by mGaelensd (e1r00%) (table 5.1). A11 Micro Small TMaablele 5.1: Distribution of 1M2a0nu(7fa6c.1tu) ring firms by g1e0n5de(7r3a.n6d) size - N ( per15ce(n1t0)0) GFeemnadleer 38 (A2131.9) 38 (M26ic.4ro) Sma0ll(0) Male 120 (76.1) 105 (73.6) 15 (100) Female 38 (23.9) 38 (26.4) Page0 5(05) of 62 Page 55 of 62 40 PercPeenrtcent Manufacturing, Trade and MSMEs Table 5.1: Distribution of Manufacturing firms by gender and size - N (per cent) Gender A11 Micro Small Male 120 (76.1) 105 (73.6) 15 (100) Female 38 (23.9) 38 (26.4) 0 (0) Joint 0 (0) 0 (0) 0 (0) TJoitnatl 157 (100)(0) 142 (100) 0 (0) 15 (100) 0 (0) Total 157 (100) 142 (100) 15 (100) SoSuorucrec:e K:NKBNSB, S2,02160.16. 5.2.5 Distribution of Manufacturing firms by gender and sector Distribution of Manufacturing firms by gender and sector MMoosts otf othf et hsueb-ssuebct-osresc itno rmsainnufmacatnuurifnagc atureri mngalea rdeommianlaeteddo inmcilnuadtinegd fuinrcnliutudrine g(30fu.9rn%it)u, re (30.9 per wceeanritn)g, awpepaarreinl g(23a.p9p%a)r, ealnd(2 fa3b.9ricpaeterd cmeentta)l, parondducftasb, erixccaetpetd mmacehtianlerpyr aonddu ecqtsu,ipemxecnetp t machinery and equipment (21.4 per cent). Females are mostly found in textiles (12 per cent) and the (2w1.e4a%ri)n. gFeampaplaesr ealre(1 m2opstelry cfoeunntd) (infi gteuxrteile5s. 4(1)2.%) and the wearing apparel (12%) (figure 5.4). FFigiguurree 55.4.4:: DDisisttrriibuttiioonn ooff Maannuufafcatcutruinrignfgir fimrsmbsy bgye gnednedrearn adnsde csteocrtor 35.0 30.9 30.0 25.0 23.9 21.4 20.0 15.0 12.0 12.0 10.0 5.0 0.0 Textiles Wearing apparel Fabricated metal Furniture products, except machinery and equipment Male Female SoSuorucrec:e K:NKBNSB, S2,02160.16. In terms of employment, the manufacturing sector employs more men (91.6%) than women (8I.n4%te)r. mMsosot fmeemn palroey fmouenndt ,int hthee mmaicnruo-fsaiczteudr einngterspercitsoers (e5m1.4p%lo)y ws hmiloe r4e0.m2 epner (c9e1n.t6 arpee r cent) than inw sommalel-nsiz(8ed.4 per cent). Most men are found in the microwhile 40.2 p eesrtacbelinsthmareentisn. Asmll awlol-msiezne d(10es0t%ab) laisreh mfouenndts i.nA thllew m -siiczreod enetnetreprrpisreisse (stab(5le1 .4 per cent)omen (100 per cent) are found in 5.t2h)e. micro enterprises (table 5.2). TTaabblele 55.2.2: :EEmmpploloyymeenntt bbyy ggeennddeerr aanndd ssiizzee ffoorr maannuuffaacctuturirnigngfi rfimrms s Numbbeerr oof feemmplpolyoeyeeses MMicricoro SmaSlml all TotalTotal Maallee 2282 (2518.4()51.4) 178 (4107.28) (40.2) 406 (91.460)6 (91.6) Female 38 (8.5) 0 (0) 38 (8.4) Female 38 (8.5) 0 (0) 38 (8.4) Total 265 (59.9) 178 (40.2) 443 (100) TSootuarlce: KNBS, 2016 265 (59.9) 178 (40.2) 443 (100) SoEudrucec:a KtNioBnS,l e2v01e6ls of Manufacturing firm owners Nearly all the owners of enterprises in manufacturing have secondary (79.1 per cent), and vocational or youth Polytechnique (20.9 per cent) (figure 5.5). 41 Figure 5.5: Education levels of manufacturing firm owners Page 56 of 62 Percent Socio-economic status of Garissa County with COVID-19 5.2.6 Education levels of Manufacturing firm owners Nearly all the owners of enterprises in manufacturing have secondary (79.1%), and vocational or youth Polytechnique (20.9%) (figure 5.5). Figure 5.5: Education levels of manufacturing firm owners 20.9 Vocational Or Youth Polytechnic Secondary 79.1 20.9 Vocational Or Youth Polytechnic Secondary 79.1 SSoouurrccee:: KKNNBBS,S2, 021061.6. Source of markets 5SMo.o2usr.tc7eo :fKSmNoBaSun,ur2fca0ec1t6 uo.rfin mg afirmksetasnd MSMEs rely on individual consumers for markets at 64.3 per cent and 71.2 per cent respectively (figure 5.6). Additionally, non-MSMEs are also MSimopusortcr teoafno tfmmsaoanurukrfceaetcstuorfinmg afirkremtss afonrd tMheSseMEsesc troerlsy aotn 1in2dipveirducaeln tcoannsdum16e.r3s fpoerr mceanrtkets at 6Mr4eos.s3pt epoceftirvm ecaleynn.utfMa acantnuduri fn7ag1c.tf2uir rmpinesgra acnneddnMtM SrSMeMsEpsEesrcemtlyivaoerknlyeit n(sdfiiigvniudGruaer l5isc.so6an)s.C uAomduendrstiytfiooarrnemablalorykt,eh ntsnooantt-Mi6n4vS.o3MlveEds ianre also peexrpocretntmaanrkde71.2 per cent respectively (figure 5.6). Additionally, non-MSMEs are alsoiimrmesppuoolrtrtatoanftnCtOs soVouIu tsr,chese nocfe mraedrkuecitnsg fopro tthenetsieal snecetgoartisv eat e1x2p poseurr ceentot athnem and esperDce-1s 9.of markets for these sectors at 12 per cent andd 1166..33 ppeerr ce cnially as acent trespectively. Mreaspneucftiavcetlyu.rMinagn uafancdtu rMingSManEdsM mSMaErskmetasr kient sGinarGiasrsisas aCCoouunntty arreeb botohthn ont ointv oinlvveodlivned in export mexaprokrtetms,a rhkeentsc,eh reendceucreindugc ipnogtepnotteinatli anl engeagtaitvivee eexxppoossuurree ttoo tthheemma nadndes epsepcieacllyiaallsy aas a result of rFeigs ulrteof5C.6O:VSIoDu-1rc9e. of markets COVID-19. FFiigguurer805e..0 65:.S6o:u Srcoe uofrmcear koeft smarkets 71.2 70.0 64.3 8600.0.0 71.2 7500.0.0 64.3 6400.0.0 50.0 30.0 40.0 20.0 16.3 30.0 12.0 12.0 12.0 10.0 6.2 6.4 20.0 16.3 0.0 12.0 12.0 12.0 10.0 O6th.2er (Specify) 6.4 MSMEs Non-MSMEs Direct exports Individual Government 0.0 consumers Other (Specify) MSMEs Non-MSMEs Direct exports Individual Government MSMEs Manufacturing consumers MSMEs Manufacturing Source: KNBS, 2016. Source: KNBS, 2016. Source: KNBS, 2016. Source of material inputs SOovueracell,omf manautfearciatulriinpgutfisrms and MSMEs source for material inputs from amongst non- OMvSeMraElls, amta4n7u.f9acptuerrincgenfitrmansdan2d4.1MSpMerEscesnoturrceespfeocrtimvealtyer(ifaigl uinrepu5ts.7f)r.omIndaimviodnugaslt snuopnp-liers as MwSeMll Eass aMt S4M7.E9spaerrecaelnstoainmdp2o4rt.1anptetrocethnet rseuspppelcytivoeflyin(pfuigtusr.eM5S.7M)E. sIanldsiovidsuoaulrcseupfpolrieirnspausts from wdierlel cats iMmSpMoErtssa(r2e.8alspoeirmcpeonrtta)natntdo tfhaermsueprsply(1o.f4inppeurtsc.eMntS)M. EDsisarlusoptsioonursceinfotrheinpeuxttserfrnoaml source dmiraerckteitmsptohretsre(f2o.r8e phearscaednvt)erasnedimfarpmlicearstio(1n.s4tpoeMr SceMnEt).oDpeisrrautpiotinosnsininGtahreisesaxteCronuanl tsyo.urce markets therefore has adverse implications to MSME operations in Garissa County. Page P5a7goef 5672 of 6242 PercentPercent Manufacturing, Trade and MSMEs 5.2.8 Source of material inputs Overall, manufacturing firms and MSMEs source for material inputs from amongst non- MSMEs at 47.9 per cent and 24.1 per cent respectively (figure 5.7). Individual suppliers as well as MSMEs are also important to the supply of inputs. MSMEs also source for inputs from direct imports (2.8%) and farmers (1.4%). Disruptions in the external source markets therefore has adverse implications to MSME operations in Garissa County. FFigiguure 5..77::S Soourucercoef mofa tmeraiatleinrpiuatls inputs 60.0 50.0 47.9 44.4 40.0 30.0 26.4 28.423.9 24.1 20.0 10.0 0.6 1.4 2.8 0.3 0.0 Other (Specify) MSMEs Non-MSMEs Farmers Direct imports Individual Government suppliers MSMEs Manufacturing Source: KNBS, 2016 Source: KNBS, 2016 Level of innovation by firms in Manufacturing 5M.2a.n9u faLcteuvriengl oefs tianbnlisohvmaetnitosnin bGya rfiisrsma Cso iunn tMy awneruefiancvotulvredinign both process and market innovations. However, only the small-sized category was involved: process (9.3 per cent) Maanndumfaacrtkuertin(9g. 3esptearbcliesnhtm) iennntosv ianti oGnasrirsessap eCcotiuvneltyy (wtaebrlee i5n.v3o).lved in both process and market innovations. However, only the small-sized category was involved: process (9.3%) and mTaarbkleet 5(.93.:3L%e)v einl onfoivnantoiovantsio rnesbpyefcirtmivseliny (Mtaabnulef a5c.t3u)r.i n g Table 5T.y3p:e Loefvel of innovation bMyi cfirorms in ManufacturSimngall innovation TotalDon't knowMicNroo Yes No SmYeasType of ll iPnrondouvcat tion 0 (0) 142 (90.7) 0 (0) 15 (9.3) 0 (0) 157 (1T00o)talDon’t know No Yes No Yes PPrroocdeuscst 00 (0(0)) 14124 (29(09.07.)7) 00 ((00)) 0 (105) (9.3)15 (90.3 ()0) 157 1(15070 ()100) PMraorckeests 00 (0(0)) 14124 (29(09.07.)7) 0 ((0)) 0 (00) (0) 15 (195. 3()9.3)157 1(15070 ()100) MSoaurrkceet: KNBS, 2016. 0 (0) 142 (90.7) 0 (0) 0 (0) 15 (9.3) 157 (100) SoAucrccees:s KtNo BcrSe, d2i0t 1f6o.r Manufacturing and MSMEs firms According to the MSME 2016 survey, 95.6 per cent of MSMEs and all of those in manufacturing applied for credit. The major sources of credit for MSMEs are: commercial 5b.2an.1k0s (A68c.c6epsesr tcoe nctr),erdeilitg fioours Morgaannuisfaaticontus r(1in9.g6 apenrdc eMntS),ManEds mfiircrmo sfinance institutions (11.9 per cent) (figure 5.8). According to the MSME 2016 survey, 95.6 per cent of MSMEs and all of those in mFaignurfeac5t.u8r:iSnogu arcpepslioefdf ifnoarn creedit. The major sources of credit for MSMEs are: commercial banks (68.6%), religious organisations (19.6%), and micro finance institutions (11.9%) (figure 5.8). 43 Page 58 of 62 Percent Socio-economic status of Garissa County with COVID-19 Figure 5.8: Sources of finance Commercial Banks 68.6 Religious organisations 19.6 Commercial Banks 68.6 MReilcigrioouFsinoargnacneisaIntisotnitsutions 119.9.6 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 Micro Finance Institutions 11.9 Percent 0.0 10.0 20.0 30.0 M4S0M.0Es 50.0 60.0 70.0 80.0 Percent Source: KNBS, 2016 MSMEsSource: KNBS, 2016 RRSeeoccueerncnett: eKevNviBdidSe,en2nc0ce1e 6frforomm FFininAAcceessss 22001199 prporovivdidees sfufrutrhthere rininsisgights on sources of credit forbusinesses in Garissa County. Businesses commonly obtainhtcsr eodnit sforuomrcetsh oef ccornevdeitn tfioorn al bsRuoesucirencneetssseesvsuid ceinh caGesafrsoihsmosapF sCin(oA6uc7en.s2tsy.p2 0eB1ru9csiepnnreots)v.sideEessm cfeourmrgthimnergonisnlosyiug rohctbsetsaoionf sccorrueerddceiitts ffrooofrmcbr uetdshiiten efcosorsnevseinntiGoanraisl sa sCobouuusrincneetysss sienuscclihun daGesa smrihsosoabpislCe o(6umn7ot.y2n.%eBy)u.( sE2inm.e1sespreegsrinccogem snmot)uonr(lcfyiegsou bortefa ci5nr.e9cdr)ei.td iftorfr bomusitnheescsoensv ienn tGioanrailssa County insourcesCcoluundtye im suochnclubi alse smhode mobo pns (6ile emyo 7(.2n2e.y1 p%er(2.) c(efingt)u.rEem 5e.r9ging1 per cent) (f)ig. u sources of credit for businesses in Garissa Figure 5.9: Recent sources of credit re 5.9). FFiigurree5 .59:.9R:e cRenetcseonurtc essooufrccreedsit of credit Digital loans 100.0 Digital loans 100.0 T 26.5Taakkiinnggccreredidtiftrofrmomshosphop 6.3 6.3 26.5 67.2 67.2 S 100.0Shopkkeeeepperer 100.0 FFaamiillyy//NNeiegihgbhobuor 100.0 ur 100.0 EEmmp 100.0 pllooyyeerr 100.0 Government-education/agriculture 100.0 Government-education/agriculture 100.0 Group/Chama 100.0 Group/Chama 100.0 Shylocks/Money lenders 100.0 SMhFyIlocks/Money lenders 100.0 100.0 M 100.0SAFCICO 2.1 97.9 SMAoCbCilOe Banking 97.9 2.1 97.92.1 Personal loan/business/loan from a bank 100.0 Mobile Banking 97.92.1 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Personal loan/business/loan from a bank 100.0 Currently Use Used to Use Never Used 0.0 20.0 40.0 60.0 80.0 100.0 120.0 SSoouurrccee:: FininAcAecses,ss2,0 219019 Currently Use Used to Use Never Used Source: FinAcess, 2019 Page 59 of 62 44 Page 59 of 62 Manufacturing, Trade and MSMEs 5.2.11 Purpose of credit PPurrpose off crrediitt TTThhheee mmaaajojjoor rrpppuuurprrppooossseee fofforor rcrccererdedidtit ibtbyby MyMSMSMMSMEEssE siiss issshhsoohwwonnw ininn ififniggufuirrgeeu r55e..11050... 1GG0e.ennGeereraanllellyyr,a, lMMlyS,SMMMEESsMsf Eifirsmrmsfisr ms rrereeqqquuuiirirreee cccrrreeddiitt fffooorrr::: wwwooorrkrkikninignggc cacapapitpiatilatal(l3( 83(.83.83p.3ep%re)rc,e cnpetu)n,rtc)p,huaprscuehr acishneavseinenvtieonnrvtyeo nr(yt2o4(r2y%4)(,2p e4arnpcdee rnbtcu)e,sniantn)ed,ssa nd rbebufussriinbneeissshssmrreeeffnuutrrb b(i2issh1h.mm9%eenn)t.t ((2211.9.9ppeer rcecnetn)t.). FFFiigigguuurrreee5 55..11.1000:: :MM Maaiinanippnuu rprppuoosrsepeooofsfcecr eroedfdi tcitredit 45.0 45.0 40.0 38.3 40.0 38.3 35.0 35.0 30.0 30.0 25.0 24.0 25.0 24.0 21.9 20.0 21.9 MSMEs 20.0 15.0 MSMEs 11.9 15.0 10.0 11.9 150.0.0 4.0 50..00 4.0 0.0 Purchase Working Capital Refurbishing Non- Business Starting anotherIPnuvercnhtoarsye Working Capital Rbeufsuinrebsisshing NPuornp-oBseusiness Sbtuasritninesgsanother Inventory business Purpose business Source: KNBS, 2016 Source: KNBS, 2016 SCoounrcsetr:aKinNtBsSf,a2c0e1d6by manufacturing firms 5CT.o2hne.1s2kte ryCaiocnontnsssttfrraaacinietndstsfba yfcaemdceabdny ubmfyaa ncmutufaarncitnuugrfianfcgirtmeusrstainblgis hfimremntss include local competition (59.8per cent), lack of markets (12 per cent), lack of collateral for credit, power interruption, poor Tsheecukrietyy, caollnasttr9a.5inptserfacceendt (bfiygumrea5n.u1f1a)c.turing establishments include local competition (59.8Tpheer ckeenyt )c,olancsktroaifnmtsa rfkaectesd( 1b2y pmeranceunfat)c,tularcinkgo fesctoallbaltieshraml feonrtsc reindcitl,udpoe wloecrainl tceorrmuppteitointi,opno or (s5e9c.u8r%it)y,, laallcka to9f. 5mpaerrkectesn t(1(2fi%gu)r, ela5c.k1 1o).f collateral for credit, power interruption, poor seFciguurriety5, .a1l1l :atC 9on.5s tpraeirn ctsenfat c(efidgubyrem 5a.1n1u)f.acturing firms FFiigurree5 5.1.11:: CCoonnstsrtarinatisnftasc efadcbeydm bayn mufacnturfiancgtfuirrminsg firms poor security 9.5 poor security 9.5 Power interruption 9.5 Power interruption 9.5 Local competition 59.8 LLoaccaklocfommaprekteittsion 12.0 59.8 LLaacckkooff mcoallrakteetrsal for credit 9.5 12.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 Lack of collateral for credit 9.5 Source: KNBS, 2016 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 SSoouurrccee:: KKNNBBSS,, 22001166 Page 60 of 62 Page 60 of 62 45 PerPceernctent Socio-economic status of Garissa County with COVID-19 5b).3 Micircor, Som, aSllmanadlMl aedniudm MEnetedripurismes E(MnStMeErsp) rises (MSMEs) Garissa County has 5,458 establishments4 with 5,223 (95.7 per cent) being micro; 194 (3.6 Gpearricsesnat )Coaurentsym haall;s a5n,4d5482 e(s0ta.8blpisehr mceennt)tsa4 rweitmhe 5d,iu2m23e (n9t5er.7p%ris)e sbe(iKnNgB mS,ic2r0o1;6 1)9(4fi g(u3r.e6%) are s5m.1a2l)l.; and 42 (0.8%) are medium enterprises (KNBS, 2016) (figure 5.12). Fiigguurere5. 512.1:2D:is DtriibsuttrioinbuoftiMoSnM Eosf bMy SsizMeEs by size 0.8 3.6 Micro Small Medium 95.7 SSoouurrccee::K KNNBSB,S2,0 210616 5S.e3c.t1o r oSfeocpteorra toiof nobpyerMaStMioEns by MSMEs Most MSMEs in Garissa County operate in the wholesale and retail trade; repair of motor Mveohsictl eMs SaMndEms ointo Grcaycrliesssa( 8C0oupenrtyc eonpt)e,raatrets ,ine nthteer twaihnmoleenstalaen adnrde crreetaatiiol ntr(a5d.e2; preerpaceirn to)f, motor veedhuiccalteiosn a(n3d.1 mpeortcoerncty),claecsc o(m8m0%od)a, tiaorntsa,n denfood services (3 per cent), an(2.9 per cent) (figure 5.13). tertainment and recreatio dnm (a5n.u2f%ac)t,u reindgucation (3.1%), accommodation and food services (3%), and manufacturing (2.9%) (figure 5.13). Figguurere5. 513.1: 3S:e cStoercotfoorp oerfa otiopnebryatMioSMnE bs y MSMEs Arts, entertainment and recreation 5.2 Education 3.1 Public administration and defence; 1.9 Administrative and support service activities 0.3 Professional, scientific and technical activities 0.3 Financial and insurance activities 1.2 Information and communication 0.9 Accomodation and food services 3.0 Transportation and storage 1.0 Wholesale and retail trade; repair of motor vehicles and motorcycles. 80.0 Construction 0.3 Manufacturing 2.9 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 4 SoAufte Source: KNBS, 2016 rrceap: pKlyNinBg Sw,e 2ig0ht1s6 Page 61 of 62 5.3.2L ocLatoiocnaotfitohenb ousfi ntehsese bs ubystiynpesosf eprse mbyise tsype of premises MSMEs in Garissa County are largely located in commercial premises (34.4 per cent), building sites and road works (26.5 per cent), residential with special outfit (21.1 per cent), MSMaEnsd kiinos kGsa(1r2is.2spae rCcoenutn) (tfyig uarree5 .l1a4r).gely located in commercial premises (34.4%), building sites and road works (26.5%), residential with special outfit (21.1%), and kiosks (12.2%) (figurFeig 5ur.e145.)1.4 : Location of businesses by premises 4 After applying weights Residential without special outfit 1.5 Residential with special outfit 21.1 Building sites and road works 26.5 Jua kali sheds 0.3 46 Open ground without stand 0.3 Open ground with stand 1.2 Kiosk 12.2 Open market 0.3 Exhibition 0.2 Market stall 1.9 Commercial premises 34.4 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 Source: KNBS, 2016 Due to income disruptions occasioned by COVID-19, MSMEs in Garissa County faced difficulties in meeting their rental obligations considering quite a number are in commercial premises (34.4 per cent). According to the May 2020 KNBS COVID-19 survey 62.3 per cent of the non-farm businesses attributed non-payment of household rental obligations to reduced incomes/earnings while 37.7 per cent attributed the same to delayed Page 62 of 62 Arts, entertainment and recreation 5.2 Education 3.1 Public administration and defence; 1.9 Administrative and support service activities 0.3 Professional, scientific and technical activities 0.3 Financial and insurance activities 1.2 Information and communication 0.9 Accomodation and food services 3.0 Transportation and storage 1.0 Wholesale and retail trade; repair of motor vehicles and motorcycles. 80.0 Construction 0.3 Manufacturing 2.9 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 Source: KNBS, 2016 Location of the businesses by type of premises MSMEs in Garissa County are largely located in commercial premises (34.4 per cent), building sites and road works (26.5 per cent), residential with spMeacniuafal cotuurtifnigt, (T2ra1d.e1 apnde rMcSMenEts), and kiosks (12.2 per cent) (figure 5.14). FFiigguurree 55..1144::L Locoactaiotnioonf boufs binuesssinesesbsyepsr ebmyi spersemises Residential without special outfit 1.5 Residential with special outfit 21.1 Building sites and road works 26.5 Jua kali sheds 0.3 Open ground without stand 0.3 Open ground with stand 1.2 Kiosk 12.2 Open market 0.3 Exhibition 0.2 Market stall 1.9 Commercial premises 34.4 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 SSoouurrccee:: KKNBS, 2016 Due to income disruptions occasioned by COVID-19, MSMEs in Garissa County faced dDiffiueculttoiesin icno meetdinisgr uthpetiiorn rsenotaclc oasbiloignaetdionbsy coCnOsVidIDer-1in9g, qMuSitMe Ea snuinmbGearr aisrsea inC coumnmtyerfcaicaeld pdriefmficiusletsie (s3i4n.4m%e)e. tAincgcotrhdeiinr gr etnot tahl eo Mbliagya t2io0n2s0 cKoNnsBidSe CriOngVIqDui-t1e9 asunruvmeyb 6er2.a3r epeirn cceonmt mofe trhceia l nporne-mfaisrems b(3u4s.i4nepsesresc eanttr).ibAuctceodr dninong-tpoaythmeeMnta yof2 h0o2u0sKehNoBlSd CreOnVtIaDl -o1b9lisguartvioeyns6 t2o.3 repdeur cceedn t inocfomthes/neoanr-nfianrmgs wbhuislien e3s7s.7e speart ctreinbut atetdtribnuotne-dp athyme seanmt eo tfo hdoeulasyeehdo ildncoremnetasl/eoabrlniginatgiso.n Fsort o threodsuec iendvolivnecdo mine fsa/remar nbiunsgisneswsehsil,e 663.77 .p7er cpenr t actetrnitbuatettdr itbhuet esdamteh teo tesmampeoratroy ladyeolffayse/d closure of businesses while 33.3 per cent were affected by reduced incomes/earnings. 5.3.3 Distribution of MSMEs by gender and size Page 62 of 62 Table 5.4 shows the distribution of MSMEs in Garissa County by gender: 73 per cent are male owned, 20.9 per cent are female owned, while 6.1 per cent are jointly owned (male/ female). For Micro establishments, 73.1 per cent are male owned, 21.6 per cent are female owned, while 5.3 per cent are jointly owned. Male owners also dominate ownership among small sized establishments at 63.2 per cent, females own 6.8 per cent, and 30 per cent are jointly owned. Considering medium sized establishments, ownership is fully controlled by males (100%). Table 5.4: Distribution of MSMEs by gender and size - N (per cent) Gender A11 Micro Small Medium Male 3,982 (73) 3,818 (73.1) 123 (63.2) 42 (100) Female 1,142 (20.9) 1,129 (21.6) 13 (6.8) 0 (0) Joint 334 (6.1) 276 (5.3) 58 (30) 0 (0) Total 5,458 (100) 5,223 (5.3) 194 (100) 42 (100) Source: KNBS, 2016 In terms of employment, the micro sized establishments employ more people (61.4%) compared to small (23.2%), and medium (15.4%) (table 5.5). Micro firms employ 47.7 per cent male and 13.8 per cent female and small sized employ 18.2 per cent male and 5 per cent 47 Socio-economic status of Garissa County with COVID-19 female. Equally, more men are employed among medium establishments at 10.3 per cent while females include 5.1 per cent respectively. Overall, more men (76.1%) are employed by MSMEs in Garissa County than women (23.9%). Table 5.5: Employment by gender and Size - N (per cent) Gender Micro Small Medium Total Male 8,171 (47.7) 3,114 (18.2) 1,767 (10.3) 13,053 (76.1) Female 2,359 (13.8) 863 (5) 866 (5.1) 4,089 (23.9) Total 10,530 (61.4) 3,977 (23.2) 2,634 (15.4) 17,141 (100) Source: KNBS, 2016 5.3.4 Education levels of MSME owners Figure 5.15 indicates that majority of MSME owners in Garissa County have a secondary education (25.6%); primary education (16.5%), and mid-level college diploma or certificate (6.3%). It is very worrying though that 40.6 per cent of the MSMEs owners did not have a formal education. Figure 5.15: Education levels of MSME owners 2.2 7.2 None 6.3 Pre-primary Primary 40.6 Vocational Or Youth Polytechnic Secondary 25.6 Mid-Level College Diploma Or Certificate Degree 16.5 Post-graduate 0.9 0.6 Source: KNBS, 2016 Source: KNBS, 2016 Level of innovation by MSMEs 5T.3ab.l5e 5.6Leprveeseln otsf tihne nleovevlsaotfioinno bvayti oMn iSnMGaErissa County by MSMEs according to size. Overall, there were low levels of innovation across MSMEs with 3.2 per cent involved in Tparboldeu c5t.,61 p.1repseer nctesn tthfoer lpervoecelss so, fa inndn0o.v5apteior nce innt Ginamriasrskae tCinonuonvatytio bnyf oMr SmMicrEo-ss iazecdcording to size. enterprises. Regarding small-sized enterprises, 0.6 per cent engaged in product, 0.4 per Ocveenrtaplrlo, ctehsseraen dw0e.4rep elrocwe nltemvealrske ot fin innonvaotvioant.iWonith arcergoasrdss MtoSmMedEiusm wsiiztehd 3e.n2te prperirs ecse, nt involved in proonldyu0c.7t,p 1e.r1c epnetrw cereenitn vfoolvre pd rinocperosdsu, cat nindno 0va.t5io npse.r cent in market innovation for micro-sized enTatebrlep5r.i6s:eLse. vReleogfainrndoivnagti osnmbyalMl-SsMizEesd enterprises, 0.6 per cent engaged in product, 0.4 per cent process and 0.4 per cent market innovation. With regards to medium sized enterprises, only Micro Small MediumTyp 0e.o7f per cent were involved in product innovations. Refused Don' Refused Don'Innovat Tota to t No Yes to t No Ye Yeion No l answer know answer kno s s w 5,03 174 31 4 38 5,44 Product 0 (0) 0 9(0) (92.5 (3. 0 (0) 0 162 (0) (3) (0. (0. (0. 9 2) 6) 1) 7) (100) ) 5,15 61 5,44 Process 0 (0) 0 3 (1. 0 (0) 40 169 25 42 (0) (94.6 (80) (3. (0. (0. 0 9 1) 1) 4) 8) (0) (100) ) 5,18 29 169 25 42 5,44 Market 0 (0) 0 0(0) 4 (0. 0 (0) (0) (3. (0. (0. 0 9 (.1) 5) 1) 4) 8) (0) (100) Source: KNBS, 2016 E-commerce Participation in e-commerce by households in Garissa County is below the national average. About 1.6 per cent of the households participate in online e-commerce which is below a Page 64 of 62 Manufacturing, Trade and MSMEs Table 5.6: Level of innovation by MSMEs Micro Small Medium Type of Refused Don’t Refused Innovation to No Yes to Don’t Total know know No Yes No Yesanswer answer Product 0 (0) 0 (0) 5,039 174 0 (0) 0 (0) 162 31 4 38 5,449 (92.5) (3.2) (3) (0.6) (0.1) (0.7) (100) Process 0 (0) 0 (0) 5,153 61 (94.6) (1.1) 0 (0) 0 (0) 169 25 42 5,449 (3.1) (0.4) (0.8) 0 (0) (100) Market 0 (0) 0 (0) 5,184 29 0 (0) 0 (0) 169 25 42 0 (0) 5,449 (.1) (0.5) (3.1) (0.4) (0.8) (100) Source: KNBS, 2016 5.3.6 E-commerce Participation in e-commerce by households in Garissa County is below the national average. About 1.6 per cent of the households participate in online e-commerce which is below a national average of 4.3 per cent (KPHC 2019). In comparison, men participate more in online e-commerce (1.8%) than women (1.3%). With introduction of stay-at-home protocols due to COVID-19 online trade has been expected to thrive, little may be impacted in Garissa County since fewer households participate in the same. 5.3.7 Turnover tax Only 12 per cent of MSMEs in Garissa County (658) had a previous monthly turnover of above Ksh 83,333 which translates to Ksh 1 million a year. Ideally, this would be the establishments that are eligible for turnover tax with the new thresholds recently introduced vide the tax laws (Amendment) Act, 2020. The actual impact of this move may be difficult to estimate due to data challenges on actual revenue streams and the number of establishments that comply with the same. 5.3.8 Constraints faced by MSMEs The major constraints faced by MSMEs in Garissa County include local competition (14.6%), lack of markets (8.2%), power interruption (8.1%), and poor security (4.9%) (figure 5.16). 49 national average of 4.3 per cent (KPHC 2019). In comparison, men participate more in online e-commerce (1.8 per cent) than women (1.3 per cent). With introduction of stay-at- home protocols due to COVID-19 online trade has been expected to thrive, little may be impacted in Garissa County since fewer households participate in the same. Turnover tax Only 12 per cent of MSMEs in Garissa County (658) had a previous monthly turnover of above Ksh. 83,333 which translates to Ksh. 1 million a year. Ideally, this would be the establishments that are eligible for turnover tax with the new thresholds recently introduced vide the tax laws (Amendment) Act, 2020. The actual impact of this move may be difficult to estimate due to data challenges on actual revenue streams and the number of establishments that comply with the same. Socio-economic status of Garissa County with COVID-19 Constraints faced by MSMEs The major constraints faced by MSMEs in Garissa County include local competition (14.6 per cent), lack of markets (8.2 per cent), power interruption (8.1 per cent), and poor security (4.9 per cent) (figure 5.16). FFigiguurree5 5.1.61:6M: aMinacionns ctroainntsstfraaceind tbsy fMaScMeEds by MSMEs lack of space 2.5 poor security 4.9 Poor access to water supply 0.7 Inaccessibility to electricity 1.1 Power interruption 8.1 Local competition 14.6 poor roads/transport 0.4 Lack of markets 8.2 Other government Regulations 0.2 Taxes 0.9 Licenses 2.9 Interference from authorities 1.7 Lack of collateral for credit 1.9 None 51.3 Other (Specify) 0.6 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Percent Source: KNBS, 2016 Source: KNBS, 2016 A study on County Business Environment for MSEs (CBEM) identified other constraints faced Ab sytuMdSyM Eosn inCoGuarnistsya BCuousinntyesass :Efninvainrcoinalmaenndtt efcohrn iMcaSl Ecasp a(CciBtyE, Mma)r kiedtenentivfiireodn moetnhte,ra ncdonstraints fawceodrk sbiyte ManSdMreElas tiend Ginafrraissstrau cCtouruen(tKyI PaPs:R fiAn2a0n1c9i)a. lO annwd otrekcshitnesic, aMl ScEaspfaaccietyi,n madaerqkueatte enanvdironment, unequipped worksites, lack of public toilet facilities, lack designated areas for waste anddis pwoosarlk,spioteo ranroda dreilnafrtaesdt riuncftruarset,rfurecqtuuernet (KpoIwPePrRinAte 2r0ru1p9ti)o. nOs.nO wnotrekcshintiecsa,l McaSpEacsit fyaMceS iEnsadequate anadre uchnaerqauctieprpised bwyolorkwslietevesl,s loafckin noofv aptuiobnl,icla ctkoiolef t rafainciinlgitiaensd, alapcpkre ndteicseigshnipatperdo garraemams efor waste difsopr oasratils,a pnos,orf rraogamde inntafrtiaosntrduucetutroe,m frueltqipuliecnityt poofwpelary ienrtserwrhuoptoifofenrs.t Oranin itnegchannidcacla cpaapciatycity MSEs arbeu cildhianrga,catnedrislaecdk boyf lmowon lietovreinlsg oafn idnneovavlautaitoionn, loafcktr aoifn tinrgainpriogrammes. With the marketenvironment, MSEs face inadequate market for their local produncgts a; nstdif fapcopmrepnettiitcioenshaimpo pnrgogramme fotrh eamrtsieslavenss;, farnadgmunefnatirattiroand eduprea cttois ems uwlthipiclhicimtya noiffe sptlatyherorsu gwh;hoc oonfftrearc ttreanifnoirncegm aenndt, capacity bucoiludnitnegrf,e aitnindg ,laduckm poifn gm(osunbitsotarnindgar dangdo oedvsa) launadtimonis roefp rtersaeintiantgio npr(othgrroaumghmweesi.g hWt,itphri cteh,e market eninvgirreodniemnte)n. tM, SMEsSEalss ofafcaec einbaodtteleqnueactkes mrealartkedett foo;ri ntsheeciurr litoyc;aml pulrtoipdleulcictes;n csetisffa cnodmpepremtiittsio; n among numerous procedures for obtaining licenses; and shortage of raw materials. themselves; and unfair trade practises which manifest through; contract enforcement, counterfeiting, dumping (substandard goods) and misrepresentation P(athgreo6u5gho wf 6ei2ght, price, ingredient). MSEs also face bottlenecks related to; insecurity; multiple licences and permits; numerous procedures for obtaining licenses; and shortage of raw materials. These findings are supported by a study on Assessment of the Investment Climate in Kenya by World Bank (2009) which attempted to identify the impediments of productivity growth among Kenyan firms. The findings showed that the business environment in Kenya is characterised by poor infrastructure, poor governance, insecurity, and complex bureaucratic administrative and regulatory systems. 5.4 Effects of COVID-19 on household non-farm and farm businesses Figure 5.17 provides key highlights on the effects of COVID-19 on household non-farm and farm businesses in Garissa County. 100 per cent of the respondents report a decrease in their business activities due to the pandemic meaning they were all affected. Equally 100 50 These findings are supported by a study on Assessment of the Investment Climate in Kenya by World Bank (2009) which attempted to identify the impediments of productivity growth among Kenyan firms. The findings showed that the business environment in Kenya Misanufacturing, Trade and MSMEs characterised by poor infrastructure, poor governance, insecurity, and complex bureaucratic administrative and regulatory systems. Effects of COVID-19 on household non-farm and farm businesses Figure 5.17 provides key highlights on the effects of COVID-19 on household non-farm and farm businesses in Garissa County. 100 per cent of the respondents report a decrease in ptheerir cbeunsint eossf atchtievi trieessdpuoe ntodtehne tpsa nhdaemviec hmaeadn inag dtheecyrweearseea lilna ftfehcteeidr. iEnqucaollym1e0 0due to COVID-19. This is apneran ii cnentnddicai ocf the respondents have had a decrease in their income due to COVID-19. This istioantitohant CthOVaItD -C19OiVs IaDlre-a1dy9 hiasv inaglraeanedgya tihveavtoilnl ogn ath enengona-tfairvme atnodllf aormn the non-farm and farm bbussininesesessseevse nevtheonug hththoeusgituha ttiohneis ssittilul eavtoilvoing .is still evolving. FFiigguruer5.e1 75: E.1ff7ec:t sEofffCeOVcItDs-1 o9 fon ChOousVehIoDld-n1o9n-f aormn ahndofuarmsebhusoinledsse ns on-farm and farm businesses Increased Decreased Not affected 100.0 Source: KNBS, COVID_19 Survey 2020 Source: KNBS, COVID-19 Survey 2020 Labour dynamics During the period considered in KNBS, COVID_19 Survey 2020 data collection, respondents 5re.p5or ted La daecbreaoseuofr8 dhoyursninathme miecansworking hours for household non-farm and farm businesses in Garissa County which implies a deterioration in economic activities between the interview periods (figure 5.18). This could be as a result of agriculture, service and Dmuanruifnacgt utrhineg pacetirviitoieds ccoonsnidseirdinegrtehedy isnig nKifNicaBntSly,f CormOVthIeDm-a1in9s tSayuorfvtehey C2o0un2ty0. data collection, respondents reported a decrease of 8 hours in the mean working hours for household non-farm and farm Figure 5.18: Labour dynamics on household non-farm and farm businesses businesses in Garissa County which implies a deterioration in economic activities between the interview periods (figure 5.18). This could be as a result of agriculture, service and manufacturing activities considering they significantly form the main stay of the County. Figure 5.18: Labour dynamics on household non-farm and farm businesses 66.0 64.0 Page 66 of 6264.0 62.0 60.0 58.0 56.0 56.0 54.0 52.0 Mean normal working hours per week preceding the Mean hours worked in the last 7 days interview Source: KNBS, COVID-19 Survey 2020 Source: KNBS, COVID-19 Survey 2020 Further, the wholesale and retail trade sector lost 10 hours in usual and actual hours worked Fiun rathweeerk,. tThheis wishaonliensdaiclaeto arnodf t rheetaadivle trrseadefefe scetscotonrt hleosset r1v0ice hsoeuctrosr oinf G uasriussaal Caonudnt yactual hours worked due to the pandemic which could imply loss of productivity, output and employment. inE qau awllye,ethke. mThaniusf aisct uarnin ginsdecitcoar tloosrt 6ofh otuhres. adverse effects on the service sector of Garissa County due to the pandemic which could imply loss of productivity, output and employment. EKqeuyaMlleys,s tahge sm: anufacturing sector lost 6 hours. a) The key sectors that drive the Garissa County economy include: Agriculture, services and Manufacturing. Hence, support should be targeted to these sectors to ensure re- engineering of the County economy. b) The key constraints faced by manufacturing firms in the County include: local competition, lack of markets, lack of collateral for credit, power interruption, and poor security. Similarly, the major constraints faced by MSMEs in Garissa County include: local competition, lack of markets, power5in1terruption, and poor security. c) COVID-19 presents opportunities that could be harnessed like development and support of innovations to address the pandemic. These include production of essential goods such as; masks, Personal Protective Equipment (PPEs), and sanitizers, disinfectants, canned foods, immunity boosting products, hospital beds and ventilators. d) Training and capacity building are important in assisting MSMEs to surmount the shocks faced during the pandemic but also allow for re-emergence. e) In terms of re-engineering, there is need to consider establishing support measures to re-vitalize and re-open businesses that collapsed during the crisis within the county. 5.2 Opportunities of COVID-19 in Industrial Recovery and Growth The following are some of the opportunities created by COVID-19 in trade, manufacturing and the MSMEs sector: i) Agro - processing for value addition with important areas of focus include livestock production, skins and hides processing, and honey production. ii) The textile and wearing apparel sectors can be enhanced to provide PPEs for use within the County and potentially for the export market. Page 67 of 62 Socio-economic status of Garissa County with COVID-19 5.6 Key Messages: a) The key sectors that drive the Garissa County economy include: Agriculture, services and Manufacturing. Hence, support should be targeted to these sectors to ensure re- engineering of the County economy. b) The key constraints faced by manufacturing firms in the County include: local competition, lack of markets, lack of collateral for credit, power interruption, and poor security. Similarly, the major constraints faced by MSMEs in Garissa County include: local competition, lack of markets, power interruption, and poor security. c) COVID-19 presents opportunities that could be harnessed like development and support of innovations to address the pandemic. These include production of essential goods such as; masks, Personal Protective Equipment (PPEs), and sanitizers, disinfectants, canned foods, immunity boosting products, hospital beds and ventilators. d) Training and capacity building are important in assisting MSMEs to surmount the shocks faced during the pandemic but also allow for re-emergence. e) In terms of re-engineering, there is need to consider establishing support measures to re-vitalize and re-open businesses that collapsed during the crisis within the county. 5.7 Opportunities of COVID-19 in Industrial Recovery and Growth The following are some of the opportunities created by COVID-19 in trade, manufacturing and the MSMEs sector: i) Agro - processing for value addition with important areas of focus include livestock production, skins and hides processing, and honey production. ii) The textile and wearing apparel sectors can be enhanced to provide PPEs for use within the County and potentially for the export market. iii) Exploration and processing of minerals such as gypsum, alluvial sand, conglomerate rock, quartz pebbles, and oil. 5.8 Recommendations To support trade, manufacturing and the MSMEs sector, the County will: i) Establish an emergency rescue package for businesses and traders hard-hit by the effects of COVID-19 in the short term. The emergency Fund, supported by development partners and other stakeholders, will be used to identify and support the most vulnerable businesses and entrepreneurs affected by COVID-19. Related, the County will inject some stimulus to cushion the businesses and traders through affordable credit, waiver of some County taxes, cess, and other charges. 52 Manufacturing, Trade and MSMEs ii) COVID-19 has increased demand for locally produced goods in the County, and especially Personal Protective Equipment (PPEs), sanitisers, hospital beds and ventilators. It is an opportunity to spur innovation and promote manufacturing and industry development and generation of jobs for the youth. iii) Establishments in the county will adopt to the new pandemic guidelines including rearranging floor plans to allow for social distancing. iv) Leverage and exploit its metropolitan areas status (Wajir-Garissa-Mandera) to enhance manufacturing, which is part of the Vision 2030 aspirations. v) Mainstream the National Urban Development Policy to spur its industrial development. vi) Establish and equip the Technical, Vocational Education and Training (TVET) as outlined in MTP III. vii) Fast track construction of a new sewerage scheme. viii) Enhance Livestock marketing value addition and processing. ix) Set up, equip, and operationalise a Gypsum Products Manufacturing Plant in Garissa as per MTP III aspirations. x) Address insecurity to spur the growth of industries in the County. xi) Fastrack development of County Industrial Development Policy to facilitate investment of industries in the County. 53 Socio-economic status of Garissa County with COVID-19 6. Infrastructure 6.1 Transport and roads In response to the COVID-19 pandemic, the County responded by delaying the i6mpleImnfernatsattriounc toufr esome of the projects that are likely to exhaust the budget to next fi6n.a1nciTarl ayneasrp. oSrotmaen odf rthoeasdes projects include construction of roads and TVETs. As a result, tIhnis breusdpgoent sweast roealtlhoecatCedO VtoI Dp-u1b9licp haenadltehm. ic, the County responded by delaying the implementation of some of the projects that are likely to exhaust the budget to next financial year. Some of these projects include construction of roads and TVETs. As a result, 6th.1is.1b udCghetawraasctreeraillsotciactse doft othpeu bsleicchtoeral th. MCahjaoraitcyt eorf ishtoicuseohfotldhse oswecnt oCrar ownership is at 4.1 per cent, a bicycle (3.5%) and a mMoatjorcitycloef (h3o.2u%se)h aonldds (oKwNnBCSa, r20ow19n)e. r sThhipe ims aitn4 m.1epaners coef nttr,anasbpiocrytc lues(e3d. 5inp etrhece Cnot)unantyd a ims wotaolrkciyncgle at( 32.62.p3e2r pcern tc)enatn, dfo(lKloNwBeSd, b2y0 1b9ic)y. cleT h(beomdaabinodma)e a2n0s.71o fpetrra ncesnpot,r tpruisveadte icnart he aCt o1u8n.7ty5 ipsewr acleknint,g Tautk2 T6.u3k2 1p2e.6r8c epnetr, cfoelnlot,w PeSdVb my baticaytuclse a(tb 1o2d.a5b6o pdear) c2e0n.7t,1 apnedr mceontto,rbpirkivea te 4c.a7r1 paetr 1c8e.n7t5 figpuerre c6e.n1,t ,wThuilke 7T6u.7k9 1p2e.r6 8cenpte rof ctehnet ,poPpSuVlamtioanta htuasd natot 1c2h.a5n6gepde rthcee mnta, ina nd mmeoatnosrb oike 4.71 per cent figure 6.1, while 76.79 per cent of the population had not changedthe mainf tmraenasnpsoortf t(rKaNnsBpSo,r t20(K2N0BbS)., O20n2 a0vbe)r.aOgen, arveesirdaegnet,sr etrsaidveenl t2s.6tr5a vkeillo2m.6e5tekrsil otmo ethteerisr to wthoerikrpwlaocrek aptl aacne aavteraangea cvoesrta ogfe Kcsohs t15o6f.1K9s. hFo1r5 t6h.e1 9c.omFomr utthee toc oscmhmooult,e retsoidsecnhtoso slp, ernedsi doenn ts asvpeernadgeo Knsahv 4er0a2g.e44K s(KhI4H0B2.S4,4 20(K1I5H/B16S),. 2015/16). FFiigguurree6 6.1.1::M MaianinM eManesaonfsT oraf nTsrpaonrtsport 30 25 20 15 10 5 0 Source: KNBS COVID-19 Impact Survey 2020 Source: KNBS COVID-19 Impact Survey 2020 The KNBS COVID-19 Impact Survey 2020 revealed that 44.8 per cent of the population Trhepe oKrtNedBSa CcOhaVnIgDe-1i9n Itmhepaccots tSuorfvterya v2e0l/2c0o mremvueatele.dT htheate x4p4e.8nd piteurr eceonnt otrfa tnhsep oprotpduelactrieoans ed rbeypo2r2t.e0d6 ap cehracnegnet ifnro tmheK csohst2 o7f2 tbraevfoelr/ecFoembmruuatrey. 2T0h2e0 etxopeKnsdhit2u1r2e ionnM traayn2s0p2o0rt fdoercareoansewd ay btyri p2.2.0T6h epemr caein tc fhraonmg eKs(h5 32.7427 pbefrocre nFte)birnuatrrayn 2s0po2r0t tcoo Kstshw 2a1s2a intt rMibauyte 2d02to0 ifnocrr ae aosneedwfaayr es tfroipr .P TShVe, mBoadinaB cohdaangaen d(5T3u.4k7T%uk) .in transport cost was attributed to increased fares for PSV, BFoigduarBeo6d.a2 :anCdh aTnugkeTiunkC. ost of Main Means of Transport 54 Page 69 of 62 WALKING BICYCLE(B OWN BICYC MOTORBIKE TUK-T M UKATATU (PSV) BUS (PSV) EMPLO P YR EIV RATE Vehicle OTHER Infrastructure Figure 6.2: Change in Cost of Main Means of Transport DECREASED DUE TO USE OF CHEAPER MEANS OF TRANSPORT DECREASED DUE TO LOWER FREQUENCY OF TRAVEL DECREASED DUE TO USE OF CHEAPER MEANS OF TRANSPORT DECREASED DUE LOWER FUEL COST (Private car) DECREASED DUE TO LOWER FREQUENCY OF TRAVEL INCREASED DUE TO CHANGE OF RESIDENCE/JOB DECREASED DUE LOWER FUEL COST (Private car) INCREASED DUE TO CHANGE FROM PSV-MATATU TO TAXI INCREASED DUE TO CHANGE OF RESIDENCE/JOB INCREASED DUE TO CHANGE FROM PSV TO PRIVATE INCREASED DUE TO CHANGE FROM PSV-MATATU TO TAXI INCREASED FARE (PSV, BODA BODA,TUK TUK ETC.) INCREASED DUE TO CHANGE FROM PSV TO PRIVATE 0 10 20 30 40 50 60 INCREASED FARE (PSV, BODA BODA,TUK TUK ETC.) Source: KNBS COVID-19 Impact Survey 2020-wave 2 SourceR:e sKidNenBtsS hCaOd VchIaDn-g1e9d Itmhepiratcrat vSeul pravteteyr n2s0w2i00th-w10a.v119e0 p2er c2e0nt of t3h0e popu40lation 5tr0aveling60 ResidelSenosutssrc oheft:aedKnN ,cBwhShaiCnleOgV9eI.d3D 7t-1hp9eeiIrrm ctperanactvtetSrauvrevelleyd20w2it0h-wthaeves2ame frequency but with some difficulty,and 11.23 per cent were unable tlo ptraatvteelr.nHso wweivther ,1050.1.298 ppeerr cceenntt oofft htheep oppouplautiloantidoind ntroatveling less ofRctheasnnid,g ewenhtshielheira d9tr.ac3vh7ea lnppgeaertdt ectrehnne.itr ttrravveel lpleadtt ewrnisthw tithhe1 s0a.1m9 ep efrrecqenuteonfctyh ebupto pwuilathtio snotmraeve dliniffig culty, and 11lesF.2ig3 s opfetern c,ure 6.3:e while Cnht we 9r.e3 7unpearbcleen ttot trraavevleleld. Hwoitwh ethveers,a 5m0e.2fr8eq pueern ccyenbtu tofw tithhes pomopeudliafftiicounlty d, id not changaen tdh1e1ir.2 t3rapveer acnege in Travel Patternsl pnatttweerrne.unable to travel. However, 50.28 per cent of the population did notchange their travel pattern. FNigOurFeig 6ur.e36: .C3:hCahnangge iinnT TrarvaelvPealt tPeranstterns YES - OTHER (SPECIFY) NO YES - UNABLE TO TRAVEL YES - OTHER (SPECIFY) YES - TRAVEL LESS OFTEN BUT EASIER THAN BEFORE YES - UNABLE TO TRAVEL YES - TRAVEL LESS OFTEN AND WITH MORE DIFFICULTY YES - TRAVEL LESS OFTEN BUT EASIER THAN BEFORE YES - TRAVEL LESS OFTEN YES - TRAVEL LESS OFTEN AND WITH MORE DIFFICULTY YES - TRAVEL SAME FREQUENCY BUT WITH SOME DIFFICULTY YES - TRAVEL LESS OFTEN YES - EASIER TO TRAVEL YES - TRAVEL SAME FREQUENCY BUT WITH SOME DIFFICULTY 0 10 20 30 40 50 60 YES - EASIER TO TRAVEL Source: KNBS COVID-19 Impact Survey 2020-wave 2 The pandemic has affected delivery of goods an0d serv1ic0es for2306 per 3c0ent of4h0ouseh5o0lds. 60 Source: KNBS COVID-19 Impact Survey 2020-wave 2 Source: FTihge KNBS urpea6n.d4e:m COi VID-19 ImpactPrcohpaosrtiaofnfeoctfeRdedsiedleivne Strsyurvey 202WofhgooseodSseravn0-waveicdesDerevliicve 2esryfohra3s6bepeenr cAefnfetcotef dhouseholds. The pandemic has affected delivery of goods and services for 36 per cent of households. Figure 6.4: Proportion of Residents Whose Service Delivery has been Affected Page 70 of 62 Page 70 of 62 55 Socio-economic status of Garissa County with COVID-19 Figure 6.4: Proportion of Residents Whose Service Delivery has been Affected 36% YES NO 64% 3366%% YYEESS NNOO 6644%% Source: KNBS COVID-19 Impact Survey 2020-wave 2 Source: KNBS COVID-19 Impact Survey 2020-wave 2 Potential fo6r.1r.e2v enPuoetecnotlileacl tfiorn revenue collection The CouSnSotoyuurTwcrhceaee:s: KCaKNolNlBouBScnSaCttyCOe OdVwVIaaDIsD-t 1-oa19tl9aloIlmIcomapftpaeKacdscth tSaSu2 utr4ovr5vet,aey9ly 12o230f0,2 920K30-s3w-hwaf arv2ove4me522,t9h1e3,R9o3a3d frMoamin ttehnea nRcoeadLe MvyaFinutnednance Levy towards roaFdumnadi ntotewnaarndcse rionatdh me Faiinnatennciaanl c2e0 1in7 /t1h8e F(OinCaOnBc,ia2l0 21091)7. /18 (OCOB, 2019). PPootetenntitaial lfoforrrreevveennuueeccoolllelecctitoionn Road network in Garissa County The couTnThtyhee6hCaC.o1sou.un3ant yttyowRtwaolasasoafdalll5 olnoc,4caea3ttet4wed.d9oa3artkKoto tiliatonalml oGoefftaKrKserhsihs2os24fa45c 5,Cl9a,91os13su3i,f9n,i9e3td3y3frroforaomdmtnhtehetewRRoorakad.dMTMhaaienintpetaennvaeandncceCeLoLeuevnvytyyFFuunndd Road nettotwowowararkdrdcssorvoreoaradsdm6m.a5ain1inteKtenMnasan,nccweehiniinleththteheeFFinpinaaanvncecidaial Nl22a00t1i17o7/n1/a18l8r(oO(OaCdCOsOBBc,o,2v20e01r1993).)1..37 KMs. Out of the total pavReRodoaTardohdanend ecetonwtuewnotwotryrkok rhikniansoG fGaa 3atro7risit.a8ssal8 aoCKfC oM5ou,su4n,3nt84yt3y.9.935 Kpielormcentrtesis oifn cglaososdificeodn rdoitaidon n,e1tw0.o9r3k.p Tehr ec epnatved County in fair cToThnhedeRictocioooaunudnn tanytynehdthawas5os.ar1akt2 otcotopatvael elrorofscf 5e65,n4.,5t43134i n4.k9.m93p3o,K oKwilriohlomicmloeeen ttrtdheriesetsi ooponfaf.cvcleaTldashs eNsifiifaeuietdnidoprnoaroaavadle ddrnonearetodwtawsod ocrkronk.v.eTetTrhw he3oe1pr.kpa3av7iven ekddmtChC.oe ou Ounntuytty of the county cRoRovoaeatdrodsntan1ele5t wpt8wao5ovr.k5rekd9c corKovoMveaersdsr s(n6c6e.o5.t5u1w1noKtKryMkMsr oso, ,faw wd3hs7hil).ie8lea8tnht hkdeemp1pa,1 av81ve93ed..d97N15Na paKtiteoMiorns nacael(lNnrortaoa tiadisod sinsnca coglovorveooeradr3d 3c1s1o.)3.,n37do7fKitKMitoMhsnis.s,., 1O10Ou.upt9teo3rof pftehthre ecent in cent is intototgatoaflaolpidpra avccveooednndddroriiottaiiaododnnn, nea3etnw7tdwo po5rekr.1kr2oocf pef3en37rt7. 8c.fa8e8nirKtKM aiMnnssd, p,8o683o03.r9. 9p5c5eoprnpedcereirctniceotennitn.t iTsipshioneion grugoncoopodnadvdceciotodnion drndiotiitaaoidosnn ,nd,1ee10tp0w.i9.co93te3rkpdp eieirnnr ctcehenent tcounty figure 1 i(niKnRfacfBaior,ivr2ce0coros1n nd91di)5t.ii8toio5nn.5a9an ndkdm55 .1(.c12o2uppneetryrc rceoenantdtisni)n appnoodor 1r1cc1oo9nn.d7di1tii tokionmn. . T(TNhheaetuiounnnpapalav vreoeddadrorsoa)a,d donf netethwtiwso,or k1rk pineinrt hctheeent is in Figure 6c.5coo:uunRgntoytoaycdco oCvcveoernsrds1it15i5o88n55.,5M .539i97xK -KpCMMelsarss (scc(iecofnoiueutnd ntfyatRyiorror aoaadanddNsds) e)6atwa0nnd opdr1ek1r 1c19e9.n7.7t1 1iKnKM Mpsos(oN(rNa actiotoinonndaalitlriooroanad dass)s,) ,dooef fpthitchisties, ,d1 1ipnpe erfirgure 1 cceennttisisininggoooddccoonndditiitoionn, ,3377ppeerrcceennttfafairiraanndd6600ppeerrcceennttininppooorrccoonndditiitoionnaassddeeppicicteteddinin fifgiguur(eKreR11B(K(, KR2RB0B,1,922)0.01 199).). FFigiguFi Pave urereg6u6.5.r5:e:R R6oo.a5add: CR d Cooonndadidtiito iConnoMnMixdix-Ci-tClialoassn Unpaved sif iiMfeieddixRR-oCoaadldaNsNesetiwtfiwoeordkrk Road Network 10.93% 5.12% 2%1% PPaavveedd UUnnppaavveedd 1100.9.933%%55.1.122%% 22%%11%% Good Good37% Fair Fair Poor Poor60% U/C GGooodd 83.95% GGooodd 3377%% FaFairir FaFairir PPooor r PPooor r6600%% UU/C/C 8833.9.955%% Source: KNBS COVID-19 Impact Survey, 2020 The unclassified road network in the County covers 2691.76KMs, with 649.33KMs of narrow roads, tShSoaouturScriosceu,e::rKrcKoNeNaB:dB SKSNCwCOBiOtVhSVI DICaD-O1-1rV9e9IIsDmIemr-pv1pa9eac ctIotmSfSupurbavrevectetyw y,S,e2u2e0r0n2v20e04y, -2902m0eters, while there is a total of 2042.43TKThMheSeuounfnccnlaleaswssifiirfeoiedaddsThe unclassirfioreo .adad drnoneaetdwtw onorekrtkwinionrthkthe ienC Cotohuuenn tCytyocuconovvetyer srcso22v66e99r1s1. 7.27666K9KM1Ms.7s,6,w wkitimhth664499.3.33KKMMssooffnnaarroroww Constrariornoatadsdss,f,atchtheaatdt isis, , roroaadd wwitihth aa reresseervrvee ooff bbeetwtweeenn 44 -9-9 mmeetetersrs, , wwhhiliel ,e wthtihteher er6e4is9is.3aa3t kototmatal ol ofo fnfarrow 2200442r2o.4.a43d3KsKM, MtShSoaotf fnisne,e wrworaordoaa dwdss.it.h a reserve of between 4 - 9 meters, while there is a total of 2042.43 km of new roads. CCoonnsstrtraainintstsfafacceedd Page 71 of 62 PPaaggee7711ooff6622 56 Infrastructure 6.1.4 Constraints faced The Rural Access Index (RAI) measures the proportion of the rural population who live within 2 km of an all-season road5. The county has a RAI of 24 per cent which is below the National Average of 70 per cent, indicating that access to transport in rural areas is below average (KRB,2019). This has negative implications with regard to sectors that rely on accessibility such as agriculture, trade and overall development. The road condition mix of the unpaved network at 60 per cent is a constraint to development. 6.2 Opportunities of COVID-19 in the Transport sector With reference to the 8-point stimulus programme by the National Government6 and resources allocated to road development and maintenance, the County has the opportunity to strategically improve the road network for economic development, while creating jobs for youth, women and vulnerable groups as espoused in the Roads 2000 programme7 on labour based road development approaches. The Roads 10,000 programme being implemented nationally by the Roads Subsector actors, and specifically, the Low Volume Sealed Roads (LVSR) approach8 offers a strategic and cost-effective approach to improve rural accessibility in the County. Residents predominantly rely on matatu PSV transport and walking; this is an opportunity during the pandemic period as this mode reduces the risk of infections that would arise from use of motorized public transport9. 6.2.1 Emerging Issues • Poor road conditions for unpaved network • Reliance on PSV transport requires enforcement of COVID-19 mitigation measures 6.2.2 Recommendations i) Sensitize PSV and boda boda operators on COVID-19 prevention measures and assist vehicle owners in retrofitting vehicle designs for social distance, hygiene and ventilation. ii) Identify a core rural road network for prioritization to improve the rural access index (RAI) from the current 24 per cent with a target to match the national average of 70.0 per cent. iii) Expand the county capability for telecommuting and teleworking and develop relevant policies in support of the same. 5 RAI defined : https://datacatalog.worldbank.org/dataset/rural-access-index-rai 6 GoK eight point stimulus programme https://www.president.go.ke/2020/05/23/the-seventh-presidential-ad- dress-on-the-coronavirus-pandemic-the-8-point-economic-stimulus-programme-saturday-23rd-may-2020/ 7 Roads 2000 programme http://krb.go.ke/our-downloads/roadsper cent202000per cent20strategicper cent- 20plan.pdf 8 LVSR /Roads 10,000 programme https://www.kerra.go.ke/index.php/lvsr 9 Non-Motorized Transport strategy https://www.weforum.org/agenda/2020/05/cities-support-people-walk- ing-and-cycling-work/ 57 Socio-economic status of Garissa County with COVID-19 iv) Identify county significant infrastructure projects for implementation under a stimulus programme to support economic recovery from the effects of the pandemic. For these, apply labor based and local resource-based approaches for road development and maintenance, where technically and economically feasible, in line with the Roads 2000 national policy10. v) Improve and expand infrastructure for Non-Motorized Transport (NMT) in urban areas and along roads with heavy -highspeed traffic to promote sustainable mobility options and enhance road safety for all road users. This is in line with the Integrated National Transport Policy 2009 and the Sustainable Development Goals11. vi) Re-develop bus parks and termini to address crowding and social distancing concerns stipulated in the public health guidelines. vii) Focus on increasing the share of unpaved roads in good and fair condition to above 62 per cent which is the national average. For the unpaved road network, focus on adopting the Low Volume Sealed Roads (LVSR) technology for greater network coverage cost effectively. viii) Adopt climate smart road engineering designs to safeguard road and bridge infrastructure from floods and to harvest storm water for irrigation and productive use. Use the Kenya Urban Support Programme funding to build storm water management systems in urban areas. 6.3 Information and Communication Technology The County has been expanding especially using e-platform and IFMIS however some of these projects has slowed down because of low connectivity but overall, they have improved in ICT. The county can now hold meetings using ICT. The county has also improved its ICT software and communication platforms, for example, it is making use of ZOOM and WhatsApp applications. One overall challenge is delay in ICT infrastructure like IFMIS and OSR application, the budget was reallocated to COVID-19 related issues. 6.3.1 Characteristics of the sector The analysis of the 2019 KPHC reveals that only 6.3 per cent of the conventional households in the county ‘own’ internet with 2.6 per cent owning a desktop, computer laptop or tablet. Internet access, ICT device ownership and TV ownership is particularly critical not only for access of COVID-19 information, but as well as supporting remote learning by the pupils as well as remote working (Figure 6.6). 10 Roads 2000 programme http://krb.go.ke/our-downloads/roadsper cent202000per cent20strategicper cent- 20plan.pdf 11 Sustainable Mobility for All: https://sum4all.org/implementing-sdgs 58 options and enhance road safety for all road users. This is in line with the Integrated National Transport Policy 2009 and the Sustainable Development Goals11. vi) Re-develop bus parks and termini to address crowding and social distancing concerns stipulated in the public health guidelines. vii) Focus on increasing the share of unpaved roads in good and fair condition to above 62 per cent which is the national average. For the unpaved road network, focus on adopting the Low Volume Sealed Roads (LVSR) technology for greater network coverage cost effectively. viii)Adopt climate smart road engineering designs to safeguard road and bridge infrastructure from floods and to harvest storm water for irrigation and productive use. Use the Kenya Urban Support Programme funding to build storm water management systems in urban areas. 1.1 Information and Communication Technology The County has been expanding especially using e-platform and IFMIS however some of these projects has slowed down because of low connectivity but overall, they have improved in ICT. The county can now hold meetings using ICT. The county has also improved its ICT software and communication platforms, for example, it is making use of ZOOM and WhatsApp applications. One overall challenge is delay in ICT infrastructure like IFMIS and OSR application, the budget was reallocated to COVID-19 related issues. Characteristics of the sector The analysis of the 2019 KPHC reveals that only 6.3 per cent of the conventional houIsnefrhaostldruscture in the county 'own' internet with 2.6 per cent owning a desktop, computer laptop or tablet. Internet access, ICT device ownership and TV ownership is particularly critical not only for access of COVID-19 information, but as well as supporting remote learning by the pupils as well as remote working (Figure 6.6). Figure 6.6: Per centage Distribution of Conventional Households by Ownership ofF iIgCuTre A6.s6s:ePtesr centage Distribution of Conventional Households by Ownership of ICT Assets 60 50 40 30 20 Garissa 10 Kenya 0 Source: ICT Data 2020 Source: ICT Data 2020 On11 lSiunseta sinhabolpe pMionbgili tiysf onroAtl l:phrtetpvsa:/l/esnumt 4inal lt.ohreg/ Cimopulenmteyn.t in1g.6-s dpgesr cent of the conventional households searched and bought goods/services online. There exists gender disparity in online shopping with more men (1.8%) than women (1.3%) undertaking online Psahgoepp7i3ngo. f 62 The perception of that the individual does not need to use the internet, lack of knowledge and skills on internet are the leading reasons that the people of in the County don’t have Online shopping is not prevalent in the County. 1.6 per cent of the conventional households internet consneeacrcthieodna (nKd HboIuBghSt)g.o Oodtsh/seerrv kicesy ofnalcinteo. rTsh einrecelxuisdtse gtehned elradciksp oarfi tiyninteornnlineet/snhoeptpwinogrk in the area, and thew ihthigmho rceomsetn o(f1 .s8eprevricceen ta)nthda neqwuomipemn (e1n.3tp (eFr icgenutr)eu n6d.e7r)ta. king online shopping. The perception of that the individual does not need to use the internet, lack of knowledge Approximateanlyd s1k0ill0s opneirn tceernnett aorfe tthhee leinadtiengrnreeats ounssethat the people of in the County don’t haveinternet connection (KHIBS). Other key factorsrisn cilnud ethtehe cloacuknotfyi nrteerlnye to/nne tmwoorkbiinlet hpehone for connectivitya, rweai,tahn da tmheahrigghincoaslt pofospeurvliacetiaonnd eoqfu Nipmoennet (rFeiglyurien6g. 7o)n. mobile broad band that uses a sim card for Acpopnronxiemcattievlyit1y0.0 per cent of the internet users in the county rely on mobile phone forconnectivity, with a marginal population of None relying on mobile broad band that uses a sim card for connectivity. Figure 6.7:F iRguerea6s.7o:nRsea fsoonrs fLoraLcakck ooffI nItnertneert Cnoennt eCctoionnnection EASONS UIPMENT IS TOO HIGH VICE IS TOO HIGH AVAILABLE BUT DOES NOT MEET HOUSEHOLD NEED (E.G.SPEED, QUALITY RNET ELSEWHER T/ NETWORK IN THE AREA OWLEDGE OR SKILLS TO USE THE INTERNET D TO USE INTERNET .00 .00 .00 .00 0 0 0 0 0 00 00 00 0 0 .0 0.0 0.0 0.00 0 0 0 .0 0.0 0,0 ,0 ,0 ,0 ,0 ,0 0 ,00 ,00 ,00 2 40 60 80 00 20 40 0 01 1 1 16 18 Source: KNBS, 2016. KIHBS 2015/16 Source: KNBS, 2016. KIHBS 2015/16 Figure 6.8: Type of Internet Connection 59 Page 74 of 62 Intern C eo tmputer/Laptop/Tablet Stand alone Radio Functional Television Analogue Television Socio-economic status of Garissa County with COVID-19 Figure 6.8: Type of Internet Connection FIXFIEXDEDWWIRIERDEDBRBORAODABDABNADND TETRERRERSETSRTIRAILAFLIXFIEXDED MMOBOIBLEILBERBORAODABDABNADND(U(SUESSES SFIMSIXIMECDACWRADRIR)DE)D BROADBAND MTMEORBORIBLEEISLTPERHPIAOHLNOFENIXEED MOBILE BROADBAND (USES 10100%0% SIM CARD) MOBILE PHONE 100% SoSuorucrec:e:KNKNBSB,S2, 021061.6K. IKHIHBSBS2021051/51/616 Sourrccee::K KNNBSB,S2,0 21061.6K.I KHBIHS B20S1 250/1165/16 ApApArpoprxopixmriomaxtaiemtleyaly3te03l.0y3 .33p0ep.r3er cpecenertn ctoefonftth toehfe pthopepo uppluoalptaioutinloantaigaoegnde ad3ge3ydey a3er aysresaanardsn daanbadob voaevbeoovwoewn onawamn moab omibleoilebpihpleoh nopenheone wwhihcihchisislolwowererthtahnanthtehenantaiotinoanlaal vaevreargaegeofof474.73.3peprercecnetn.tA. pAprporxoixmimataetleyly6464peprercecnetntofofthtehe pepoeAwpoplphepliercionhixn tiimhste haloetcewoclyueornu3 ttn0yh.t3yahnaph veatehrveeca enamnatmotoiboofibnlteihaleelm ampovonoepenruyaelgyasetusi obounsfb c4sarc7gipr.ei3tpdi otpi3noenryc eoccameornmspta.pa rAnaedrpdepadwrbowiotxhvitiehmoonoawlntynely1lya61 66mp4eop prbeierclerec nceptenhntohtnt aheotaf tthe hahsawpsaehaomicpmholbeois ibilenliol emtwhmeoern ocetnohyeuaybnabttynah knheikannivgnaegtp iaolpa nmltaafotlofrabomvirlemesr amusgbuoesbncsorecfiypr4i tps7iout.in3bons(pcKe(rHrKipHIcBteIiSnBotSn2. 0c2A1o0p5m1p/5r1po/6xa1i)r6me)dat welyith6 4onpleyr 1c6e nptero fcethnet that pheaosp ale minobthilee cmouonnteyyh baavenkainmgo pbillaetfmoormne ysusbusbcsrcirpipttiioonn (cKomHpIBarSe d20w1it5h/1o6n)ly. 16 per cent that FiFgiughruaerse6a.69m.:9o:MbMoileboibmleiloeMnMeoynoenbyeanyTkrTianrnagsnpfselfarestrfosSruSmbusbscusrcbiprsitcpirotiipnotniaoandn(dKMHMoIboBibSleil2eM0Mo1n5o/en1ye6yB) aBnakniknigngPlPaltafotfromrm Figure 6.9: Mobile Money Transfers Subscription and Mobile Money Banking MMoboFPibilgleiauletrmefmoo6rno.9men:yeMytortabrnialesnfseMfreornseusybusTbcsrracipnristpifoteinorsnKSHuKbHIBsIcSBrSiptMioMonboaiblneildeMobmilmeonoMenoyenyey BbaabnnkakinikngignPglatfoprmlpaltafotfromrm 2021051/51/616 SuSbusbcsrcipritpiotinonKHKHIBISBS2021051/51/616 Mobile money transfer subscription KHIBS Mobile money banking platform 2M01o5b/1il6e money transfer subscription SuMboscbriilpet imonoKnHeyIB bSan20k1in5g/1 p6latform Subscription KHIBS 2015/16 KHIBS 2015/16 161%6% 363%6% 16% YEYSES YEYSES 36% NONO NONO 646%4% YES YES NO NO 64% 848%4% 84% Source: KNBS (2016), KIHBS (2015/16) SoSuoGrucreecn:e:dKNKeNBr SBaS(n2(d021 0y61o)6,u)K,tIKhHIHBSBS(2(021051/51/61)6) Source: KNBS (2016), KIHBS (2015/16) The county experience gender divide in use of internet and ICT devices as well as mobile GGenemdnoednreerayna sdnudybosycuortuihptthions. Both internet and ICT device use is higher among the male with G13e.n2d peerr acnednty oofu tthhe men and 11.0 per cent of the women using internet, while 5.2 per cent ThTehecocuonutnytyexepxepreierinecnecegegnednedrerdidvivdiedeininusueseofofinitnetrenrentetanadndICITCTdedveivciecsesasaswwelel lal sasmmoboibleile mmonTooenhf yeethysceuos buumsnbcetsrycnipr eitapxinotpindoes nr3.ise..Bn8ocB etpohetghrien cnitneedtnreenrtr enodteifvta tindahdened IiwnCIoTCumTsdeeednvoei fvcuieicsneitunesugrens DeeisteisashknihgtdiohgpIehCr/eTLraamdapemotvnooicgpne/gstThtaehsbemlwemate laledl leeawvswiitcmhiethos1 b3(1iKl.3e2P.2HC m20o1n9e)y. Wsubhsilceri tphtieo nuss.aBgoet ihs binetleornwe tthaen ndaItCioTndael vaivceeruasgeesis, thhige hceoruanmtyo rnegcothredemda ale siwmitihla1r3 g.e2nder disparity with the national averages in internet and ICT usage. PPaPaggaeege777555ooffo6f62622 60 Infrastructure 6.4 Opportunities of COVID-19 in ICT Potential to use ICT infrastructure and services in public primary schools for community access to ICT. 6.4.1 Emerging Issues Emerging technology such as satellite and airborne transmitters for internet connectivity 6.4.2 Recommendations i) Support programmes in partnership with the private sector that will enable households acquire ICT assets such as smart phones and laptops and increase mobile phone ownership from 42.5 per cent to 100 per cent in line with the global agenda for Universal Access to Mobile Telephony12 ii) Harness the power of technology and use innovative solutions to bridge the gender digital divide and promote technology adoption in daily socio-economic activities. iii) Collaborate with the Communications Authority and telecom service providers to utilize the Universal Service Fund13 as a “last resort” in providing ICT access in remote areas where market forces fail to expand access. iv) The IT personnel in public primary schools can be deployed to support the development of ICT competence and skills among the public. v) Enhance internet connectivity to public buildings and key trade centres to boost e-commerce especially for MSMEs in trade and business. The NOFBI programme can be expanded to the sub-county administrative units to further enable deployment of e-governance solutions. Develop an ICT based document management system for appropriate records and documentation management as outlined in the County Integrated Development Plan (CIDP) 2018-2022. vi) Make ICT a standalone sector for planning and budget allocation. This is aimed at giving strategic prominence to planning, budgeting and investment in ICT. vii) Review and implement ICT policies and procedures to manage ICT as provided in the CIDP and mitigate the cyber threats. Collaborate with the national Computer Incident Response Team (CIRT) and the Communications Authority (CA) towards managing cyber threats, disasters, and pandemics. This is because enhanced use of ICT is known to raise threats and risks related to cyber-crime and misinformation. 12 Universal access to mobile telephony: http://www.itu.int/itunews/manager/display.asp?lang=en&year=2007 &issue=07&ipage=universal-telephony 13 Universal Service Fund: https://ca.go.ke/industry/universal-access/purpose-of-the-fund/ 61 Socio-economic status of Garissa County with COVID-19 7. Housing and Urban Development Majority of households are headed by men (79.18%) compared to women (20.82%) in the County (KIHBS, 2015/16). There are four urban centers in the County with a total population of 51.9 per cent males and 48.0 per cent females. The urban land area covers 176 square kilometers with a population density of 1199 persons per sq.km Table 7.1: Distribution of Population by Urban Centers by Gender GARISSA MASALANI 43,642 23,662 19,979 GMAajRorIitSySoAf housIeJhAolRdsAare headed by men (791.11,87p9e2r cent) compare7d,2to48women (20.82per4,544 GceAnRt)IiSnStAhe CouDntAyD(KAIAHBBS, 2015/16). There 1a1r,e52fo5ur urban centers6,i5n3t2he County with a4,993 total population of 51.9per cent males and 48.0 per cent females. The urban land area GcoAvRerIsS1S7A6 squaBreUkRiloAm eEteArSs Twith a population6d,e4n9s6ity of 1199 person3s,5p3e0r sq.km 2,965 SoTuabrlcee7:. 1K:NDBistSri,b 2ut0io1n9o- fKPeonpuylaat iPonopbuy lUartbiaonnC aenntde rHs boyuGsienngde Cr ensus GARISSA MASALANI 43,642 23,662 19,979 GARISSA IJARA 11,792 7,248 4,544 7.G1A RISCSAharacDtAeDrAAisBtics of the se11c,5t2o5r 6,532 4,993 GARISSA BURA EAST 6,496 3,530 2,965 ThSoeu hrcoeu: sKiNnBgS t,e2n0u19r-e Kiesn pyraePdoopmulaintioannatlnyd oHwonuseinr goCccenuspuised at 87.4 per cent, with 12.6 per cent of the households under rental tenure. Individuals are the primary providers of rental housing 2.1 Characteristics of the sector atT h7e4h.7o uspinegr tceenunrte, isfoplrleodwomedin abnytl yNowatnieornoaclc uGpioedveartn8m7.e4npte r(c6e.n2t%, w);it ha1n2d.6 Cpeorucnetnyt oGf overnment (5t.h4e%h)o;u Fseohro ltdhsousned werhroe notwalnte hnuorme.eIsn,d 8iv4id.u8a plsearr ecetnhet cporinmsatrryupcrtoevdid tehrse ohforuensteasl whohuislien g11.7 per cent puatrc7h4.a7sepder tcheen th,ofoulsloew aenddb y3.N5a ptioenra cl eGnotv einrnhmeernitte(d6 .t2hpeeirrc henotm);easn d(KCNouBnSty, 2G0ov1e9r)n.m ent (5.4per cent); For those who own homes, 84.8 per cent constructed the houses while 11.7 Fpigerucreent p7u.r1c:h aDseidstthreibhouutsieoannd o3.f5 pheor ucesnet hinohelrditsed Rtheeinr htionmges/ (KPNrBoS,v2id01e9d). with the main dFwigeulrlein7.g1 :uDnisitr ibuyt ioPnrofvihdouesreholds Renting/ Provided with the main dwelling unit by Provider FBO/NGO/Church/Temple/Mosgue Individual Private company Parastatal County Government Government 0 10 20 30 40 50 60 70 80 Source: KNBS, 2019 -Kenya Population and Housing Census SoHuorucsein: gKQNuBaSli,t y2019 -Kenya Population and Housing Census On average, the main dwellings of houses in the County have 1.50 habitable rooms against an average household size of 4.23 persons in a household, translating to approximately 2.82 people per room. According to the UN-Habitat, overcrowding occurs when there are more than three people per room14. In terms of housing quality (building material), 37.96 per 62 14Household crowding measure: https://www.ncbi.nlm.nih.gov/books/NBK535289/table/ch3.tab2/#:~:text=Overcrowdingper cent20occursper cent20ifper cent20thereper cent20are,perper cent20habitableper cent20roomper cent20(88).&text=Crowdingper cent20occursper cent20ifper cent20thereper cent20is,per cent2Drooms)per cent20(89). Page 77 of 62 Housing and Urban Development 7.1.1 Housing Quality On average, the main dwellings of houses in the County have 1.50 habitable rooms against acne natvoefrahgoues hesouarseehconldst rsuiczte douf s4in.2g3fi npisehresdonmsa itner ia lshfooursweahlolsl,df,lo torraannsdlartoionfgin gtoc oampparorexdimately 2t.o826 2p.0e4oppleer pceern rtocoomns.t rAucccteodrduisningg toru tdhime eUnNta-rHy ambaittearti,a losv(eKrIcHrBoSw,d2in01g5 o/1c6c)u.rsM awjohreitny tohfere are mhoourese thhoaldns t(h5r3e.e0 ppeerocpelnet )pehra vroeoimron14.s hIene ttserfmors roofo fhinogu,sGinrags qs/uRaeleitdys (wbaulilsld(i2n9g. 2mpeartecreinatl)), 37.96 and Earth/Sand floors (68.2per cent) (KNBS, 2019). per cent of houses are constructed using finished materials for walls, floor and roofing compared to 62.04 per cent constructed using rudimentary materials (KIHBS, 2015/16). MRaejnotrPaymentOn avietrya goef, hreonutsael hhoouldses h(o5ld3s.0s%pe)n hdaavpep riorxoinm astheelyetKsS Hfo.r1 r0o7o22finogn, rGenrtawssit/hRaeemdisn iwmaulmls o(f29.2%) aKncSedHn Et.5oa0fr0thhoa/unSsdeastnhadere flmcooaonrsstr u(6ct8e.d2u%si)n g(KfiNnisBhSe,d 2m0a1t9er)i.a ls for walls, floor and roofing comparedto 62.04 per cent conxismtruumctedofuKsSinHg. r6u0d0im00en(tKarNyBmS,at2e0r2ia0lsb)(.KTIHhBeSc, o2u0n1t5y/1re6)c.orMdaejdoraityreonft to inhcooumseehorladtsio(5o3f.0_p_epr ecrencet)nthawvheicihronis swhietehtins ftohre raococfienpgt,abGlreastsh/rReesehdosldwoaflls30(2p9e.2rpceerncte(nKtN) BS, 72a.01n1.d22E/ 1a3rtR)h./eSnantd Pflaooyrms (e68n.2tper cent) (KNBS, 2019). OWRnie tahnvttehPreaayamdveenntt of COVID-19 pandemic, households’ ability to pay rent has been affected, wOitnha4v2er.0a ggee,, rreent8 pernctea al lh hoouseholds spend approximately Ksh 10,722 on rent with a minimum of nt oufstehheolpdospsupleantidonapinpdroicxaimtinatgeliynaKbSiHlit.y1t0o72p2ayonrernetntown itthhea amgirneimedumdaotef for KAKsphSrH il5.52000002 0aa,ncdo mthpeea rmeadaxixmimumumof oKfS HK.s6h0 6000,0(0KN0B (SK, N20B2S0b, )2. 0T2h0e bc)o.u Wntyitrhe ctohred eaddavernent totfo COVID-19 painncdomeme irca,t iohoofu_se_hpoelr to 2 dcse’ n 7t .03abwilhiitc per cent of the po yh tiso wpitahyin rtehneta hcc pulation that were able t aesp tbaebleent harffesehcotleddo, fw30ithpe or pcaeyntre(KnNt BoSn, the a2g0r1e2/d13d)a.te and 61.21 per cent wh aid rent on agre d d te before COVI D4-219.0p8a npdeerm cice.nt of the population indicating inability to pay rent on the agreed date for April 2020, compared to FW27ig ith the ad .0u3re p7e.r2 :ceP v nr eonptoortfioCnOVID-1t of the pofoRpeus 9idpeanntdsePmaiyci,nhgoRuesenhtopldesr’Taebrimlitys otof Cpoayntrreanctt has been affected, with 42.08 per cent of the polaptuiloatnio tnhiantd iwcaetrineg aibnaleb itlioty ptaoyp raeynrte notno tnhteh aegargereeded ddaattee afnord 61.21 per ceAnptril 2020, co70 who paid m rpeanretd otno a2g7r.0e3edp edracteen bt eoffotrhee CpoOpVulIaDtio-n19t hpaatnwdeeremaibcl.e to pay rent on the agreed date and 61.21 per cent who paid rent on agreed date before COVID-19 pandemic. FFigi6g0uurree7 7.2.:2P:r oPproortpioonrotfiRoensi doefn tRs ePasyiidngenRetnst PpearyTienrgm sRoef nCot nptrearct Terms of Contract 5700 60 40 50 30 40 2300 1200 10 0 0 YES,ALWAYS YES,SOMETIMES NO DON’T KNOW YES,ALWAYS YES,SOMETIMES NO DON’T KNOW SSoouurrccee:: KKNNBBSS CCOOVVIIDD--1199IImmppaaccttSSuurvrevyey20220020wwavaeve2 2 Source: KNBS COVID-19 Impact Survey 2020 wave 2 FFFiiggiguuurrreee77 .7.33.::3HH: aaHss ayyoosuu yrrohhououursse ehhhoooludldsppeaaihdidothtlheder perneatniftdofr otArhpAerpi lrr2iel0n2200t2 fo0onortnh Aethpaegrriaelge 2rde0edd2at0dea oten the agreed date UNABLE TO PAY/WILL NOT BE ABLE TO PAY UNABLE TO PAY/WILL NOT BE ABLE TO PAY TO PAY,ON TIME TO PAY,ON TIME PAID,NOT FULLY PPAAIIDD,NOONTTFIMULELY 0 5 10 15 20 25 30 35 40 45 PAID ON TIME Source: KNBS COVID-19 Impact Survey 2020 wave 2 0 5 10 15 20 25 P3a0ge 7385 of 6402 45 SSoouurrccee:: KKNNBBSSC OCVOIVD-I1D9-1Im9 pIamctpSaucrtv Seuy r2v0e2y0 2w0a2ve0 2wave 2 14 Household crowding measure: https://www.ncbi.nlm.nih.gov/books/NBK535289/tPaablgee/ch738. of 62 tab2/#:~:text=Overcrowdingper cent20occursper cent20ifper cent20thereper cent20are,perper cent20hab- itableper cent20roomper cent20(88).&text=Crowdingper cent20occursper cent20ifper cent20thereper cent20is,per cent2Drooms)per cent20(89). 63 Socio-economic status of Garissa County with COVID-19 The main reason that has made households unable to pay rent was attributed to reduced iTnThhceeommmeaasiinn /rereeaaarssnooinnngthtsha,a trtehhpaasosrmtmeadae dbehyo h5uo9sue.3she4ohl dposledrus ncuaenbnlaetb olteof ttphoaeyp pareoynprtuewlnatatsiwoaantst.r Tiabthuttreei bdiunttaeobdirletidotyu rcteeodd upcaeyd rent wiinnaccsoo mmateetssri/b/eeuaatrrenndinin gtgoss, ,trhereep poCorOtretVdedIbDyb-y15995. 93p.4a3n4pdepreemcreicncet bnoytf o9thf1e.t8hp2eo pppueolrpa tucioelannt.ito Tonhf. etThihneea pbioinlipatybuiltlaoittypioatnoy. preanyt rent wwaass aattttrriibbuutteeddttootthheeCCOOVVIDID-1-919papnadnedmemic ibcyb9y19.812.8p2erpceerncteonfttohfetphoeppuolaptiuolna.FFiigguu tion. rere7 .74.:4R:e aRseonassfoonr nso ftoBre inngoAt bBleetionPga Ay Rbelnet to Pay Rent Figure 7.4: Reasons for not Being Able to Pay Rent OTHER OTHER DELAYED INCOME/EARNINGS DELAYED INCOME/EARNINGS REDUCED INCOME/EARNINGS RE Series 1PERDMUCAENDENINTCLOAYMOEF/FE/ACLRONSINURGESOF BUSINESS Series 1 PTEEMRMPOARNAERNYTLLAAYYOOFFF/FC/CLOLOSUSUREREOFOBFUBSUINSEINSSESS TEMPORARY LAYOFF/CLOSURE OF BUSINESS0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Source: KNBS COVID-19 Impact Survey 2020 wave 2 SSMoaujrocriety: KoNfNBthBSeSC hCOoOVuIsVDeIh-D1o9l-d1sI9m( I8pm9a.c5ptpaSecrutr cSveeunyrt)v2ed0yi2d 02n0wo2ta0vree wc2eaivveea 2waiver or relief on payment of Mreaanjjtoorrfiritotyym ooftfh ttheheelah nhodoulousredh,owldisth(819.3.55ppeer rcecnent)t dreidponrotitngreacepivaertaialwwaaiviveerroarnrdeli0e.f66onpepraycmenetnt of rreenptorftrinogmathfeulllawnadilvoe sre.hTooldso v(e8rc9o.5m%e )t hdeide nffoect trsecoef ivCeo rao nwaavivireurs oorn rpealiyemf eonnt poanymrenetn,t of rent fmroamjo rtihtye 1la4n.8d4lopredr, wridth, 1withcent of.3h5 p1e.3r 5 perousehcoeldnst rreecennpeot rgrottieinpoatge dart pinag arenrttialp waratial wterms,ivwerh aanivde r0a.6nd 0.66 per centreporting a full waiver. To overcome the effects of Corona viruilse 3o1n.5p5 6 per cent aypmerencetnot no rfeporting rent, amh foaujlosler wihtyoaldi1vs4ed.r8i.d 4Tnopo etortvaeckreecnoatnmoyefm thehoaeus sueerffeheso.cldtAssp porrfeo nCxeiomgroaottneialayt ev1di3r.ru1es8n otpnetre prcmaeynsmt, uewsnehdtil eopne3r 1sroe.5n5atl, psmaevrainjcogersnitty o14.84 pteorp caey rent. f househnot lodsf hdoidunseoht otaldkes raennyemgoetaisautereds .reAnptp treorxmimsa,t welyhi1le3 .3118.5p5e rpceern cteunste odf pheorusosnehalosldavsi ndgids not ttFaoikgpeua raeyn7rye. 5nm:t.Meaesausurreess. TAapkpernobxyimHoauteselyh o1l3d.1to8 Mpietirg acteenCt OuVsIeDd- 1p9erEsffoenctasl osnavRienngts to pay rent. FFiigguurere7 .75.:5M: eMaseuarsesurTeakse TnabkyeHno busye HhooldutsoeMhiotilgda tteoC MOVitIDig-a19teE CffeOcVtsIoDn-R19en Etffects on Rent OTHERS NONE REORIENTATION OF HOOTUHSEERHSOLD SPENDING TO SOLD HOUSNEHOONLED ASSETS REBOORRIREONWTAINTGIOMNOONFEHYOFRUOSEMHBOALNDKSSP/MENODBIINLEG TO USSEODLD H POLATFMY PEURSSOE OHRMNOALLDSAVSSINEGTSS BORROWING MONEY FROM BANKS/MOBILE RELIED ON DONATIONSPLFARTOFMORFRMIENDS/WEL WISHERS UDSEFDEMRRYEDPEPRASYOMNEANLT SDAVTIENGS RELIED ONREDLOONCATIEODNTSOFTRHOEMRUFRAIELNHDOSM/WE EL WISHERS MOVEDDTEOFAERFREIEDNPDASY/RMEELANTIVDEASTHEOUSE RMELOVCEADTETDO TAOCHTHEAEPREURRHAOLUHSOE ME SUMCOCEVSESDFUTLOLYARFERNIEENGODTSI/ARTEELDATRIEVNETSTHEORMUSSE MOVED TO A CHEAPER HOUSE 0 5 10 15 20 25 30 35 SourcSUe:CCKENSBSFSUCLLOYVRIEDN-E1G9OITmIApTaEcDt RSEuNrTveTyER2M02S0 wave 2 0 5 10 15 20 25 30 35 SWoiuthrcere:gKaNrdBStoCOprVimIDa-r1y9eInmerpgayctsoSurcve yfo2r02co0owkianvge, 291.8 per cent of households rely on Suonucrlecaen: sKoNurBceSs CoOf eVnIeDrg-y19fo Irmcopoakcint gSusurcvheyas 2f0ir2ew0 owoda,vpea 2raffin and charcoal, which could adversely affect respiratory health of women and children. Wiitth rregarrdd ttoo prrimimarayrye neenregrygys osuorucercefo rfocro cookoinkgi,ng9,1 .981.p8e rpecre nctenoft ohfo uhsoeuhsoeldhsolrdesly roenly on uu2n.2cleaOnp spoourrrtcuceenssit ooifef senineerhrggoyyuf sfooirnrcg cooaoonkkidnignugrsb usacunhchda esavsfei rfileorwepowmooedon,dtp,a prafrfainffiann dancdh acrhcaoracl,owalh, iwchhiccohu lcdould Partnersh aaddvveerrsseelly ipafwfeitcht NreastpioirnaatloGryovheeranlmthenotf awnod Private Sectoy affect respiratory health of wmoemn eann danchdi lcd rrefonr. home improvement (roof, floor and walls) under the Big Four Agenda. hildren. 2.2 Opportunities in housing and urban development Partnership with National Government and Private Sector for home improvement (roof, floor 7a.n2d waOlls)pupndoer thuenBigtiFeosur iAng ehndoau. sing and urban develoPpagme 7e9notf 62 Partnership with National Government and Private Sector for home improvement (roof, floor and walls) under the Big Four Agenda. Page 79 of 62 64 Housing and Urban Development 7.3 Emerging Issues Majority of the households (89.5%) did not receive a waiver or relief on payment of rent from the landlord, despite inability to pay 7.4 Recommendations i) Develop and implement an addressing system with complete, correct and unique address data in line with the National Addressing System. To be used pandemic and disaster surveillance and emergency response. ii) Fastrack implementation of the affordable housing programme in partnership with the private sector targeting urban centers. iii) Develop a policy to promote home ownership to address the problem of rent distress during times of emergency. iv) Avail appropriate building technology for use by the public in house construction and improvement in every subcounty, that responds to local cultural and environmental circumstances. v) Identify and designate urban centers for upgrade pursuant to provisions of the Urban Areas and Cities (amendment) Act, 2019. vi) Develop and implement urban planning and design instruments that support sustainable management and use of natural resources and land in line with the New Urban Agenda and as mitigative measure to future pandemics and disasters. vii) Adopt programmes aimed at an increasing household access to clean energy sources and technologies for cooking to mitigate against exposure to respiratory diseases. 65 Socio-economic status of Garissa County with COVID-19 8. Tourism 8.1 Characteristic of the sector The key tourism attractions from Garissa County are wildlife, heritage and culture (rich Somali traditional culture) and hospitality. The proximity of the county to the tourist coastal town of Lamu makes it ideal for linkage through a tourist circuit. The County does not have classified (star-rated) hotels15. However, there are 5 major hotels with a bed capacity of 450. The county has 6 wildlife conservation areas namely, Garissa Giraffe sanctuary, Ishaqbin Community Conservancy, Waso Conservancy, Arawale National Reserve, Rahole National Reserve and Boni National Reserve. There is need to enhance the exploitation and utilization of these facilities fully. Tourism contributes 0.4 per cent to overall GCP of Garissa reflecting on the need to prioritize development of the sector. The number of domestic and foreign tourists who visit the tourist sites in the county is not documented. There is need to develop a tourist action plan to enhance exploitation of existing tourism opportunities including desert tourism (camel-back expeditions, camping and dessert rallying). 8.2 Opportunities of COVID-19 in Tourism Sector i) Improving sanitation aspects in tourism attraction sites. ii) Refurbishment of accommodation facilities iii) Promoting domestic tourism 8.3 Emerging Issues Sanitation as a key component in ensuring business continuity in the tourism sub-sector; 8.4 Recommendations i) Mapping all the sites with tourism potential in the county; coming up with a tourism sector development master plan. ii) Tourism product diversification and marketing; niche products such as annual cultural festivals, annual camel derby and animal sanctuaries. iii) Setting up a cultural documentation centre; tourism information centre. 15 Tourism Regulatory Authority, Classified Establishments Register, 2019 66 Tourism iv) Developing a tourist circuit connecting Garissa and Lamu; rehabilitating road infrastructure in the region to enhance accessibility by tourist. v) Ensuring high sanitation standard in the hotel facilities to deter spread of COVID-19 in line with the national guidelines for reopening of the hospitality sector. 67 Socio-economic status of Garissa County with COVID-19 9. Health 9.1 Characteristics of the sector Garissa County has 205 health facilities. Out of these, 68 are level two facilities, seven are level four, 85 are private clinics, 13 level three private hospitals, 4 are private Nursing Homes, one is private Hospital, 21 are level three facilities and one is a level five facility based in Garissa Town. There are also three Non-Governmental Organization dispensaries and two mission health facilities. Good health care services are mostly in the urban areas. The average distance to the nearest health facility is 25km. Most of the health facilities are along the river and urban centres where there are settlements. Table 9.1: Health provision Year 2017 2018 2019/20 Health facility density Primary health facilities 120 180 Hospitals 9 20 Number of health facilities 129 200 Health facility density 2.2 2.9 Bed density Hospital beds 827 857 No. of Beds per 10,000 population 13 13 Human resource density Total workforce 861 1,429 Human Resources for Health (Technical) 751 817 Number per 10,000 population 7.5 7.0 Source: MOH, 2021 In 2019/2020, the number of health facilities in the county were 200 which comprised of 180 primary health facilities and 20 hospitals. This was an improvement from a total of 129 health facilities in the previous year, 2018. The number of beds per 10,000 population is 13 against the WHO recommendation of 30 beds per 10, 000 population. The health facilities and personnel serve a growing population of 841,353 people according 2019 census. In 2019, total health workforce was approximately 1,429 representing 7 health workers per 10,000 population which is below the WHO target of 23 health workers per 10,000. 68 Health Table 9.2: Percentage Distribution of the Population that reported Sickness/ Injury by Type of Health Provider in the County (per cent) Type of Health Provider Percentage Distribution of the Population Government hospital 11.7 Government health centre 18.4 Government dispensary 32.6 Faith Based (church, Mission) Hospital / Clinic 0.0 Community Health 0.0 Private hospital / clinic 36.7 Nursing/ Maternity Home 0.0 Pharmacy/ chemist 0.0 Community health worker 0.0 Shop/ Kiosk 0.0 Traditional healer 0.0 Faith healer 0.6 Herbalist 0.0 Other 0.0 Number of Individuals (‘000) 24 Source: KIHBS 2015/2016 Table 9.2 presents the distribution of population reported to have been sick or injured and the type of health provider they visited. Majority of the County residents who reported illness visited private hospitals (36.7%) followed by those who visited government health dispensaries (32.6%), government health centres at 31.1 and Government hospital (11.7%). 9.1.1 Population with health insurance cover The percentage distribution of the population with health insurance cover by type of insurance provider is presented in Table 9.3. In general, 2.7 per cent of the county population had some form of health insurance cover. The National Hospital Insurance Fund (NHIF) was the leading health insurance provider reported by 89.5 per cent of the population. Employer contributory insurance cover was reported by 15.4 per cent of the population, private non-contributory insurance cover was reported by 0.9 per cent of the population. 69 Socio-economic status of Garissa County with COVID-19 Table 9.3: Percentage Distribution of the County’s Population with Health Insurance Cover by Type of Health Insurance Provider (per cent) Source of Health Insurance Percentage Distribution of the Population (per cent) Population (‘000) 432 Share of population with health insurance (per cent) 2.7 NHIF 89.5 Private-Contributory 0.0 Private-Non-Contributory 0.9 Employer-Contributory 15.4 Employer-Non-Contributory 0.0 Other 0.0 Number of Individuals (‘000) 12 Source: KIHBS 2015/16 9.1.2 Place of delivery In the 2015/16 KIHBS, women in Garissa County were asked the place where children aged 5 years and below were delivered. Table 9.4 shows the percentage distribution of children by place of delivery, in the county. About 54 per cent of children were delivered at home which is higher than the national percentage of 31.3 per cent. The proportion of children born in hospitals, health centres, dispensary/clinics was 33.5 per cent, 7.9 per cent, and 1.5 per cent respectively. Table 9.4: Proportion of Children aged 0-59 Months by Place of Delivery (per cent) Place of Delivery Proportion of Children aged 0-59 Months by place of delivery (per cent) Hospital 33.5 Health Centre 7.9 Clinic/ Dispensary 1.5 Maternity Home 0.5 At Home 54.0 Other 0.0 Not stated 2.5 Number of Individuals (‘000) 63 Source: KIHBS 2015/16 9.1.3 Immunization for children The 2015/16 KIHBS covered data on measles immunization for children below 5 years at; 9 months (Measles I) and at 18 months (Measles II). The information was collected from vaccination cards where they were available while mother’s recall was used where the card 70 Health was not available. Table 9.5 presents information on the proportion of children immunized (from vaccination cards) against measles. The analysis focused on children aged 12-23 months (or one year). The county had 2.6 per cent of the children aged 12-23 months were fully immunized against measles at 9 months. Table 9.5: Proportion of Children aged 0-59 Months Immunized Against Measles Proportion of Children Vaccination Card Yes Seen 10.7 Yes, Not Seen 38.1 No 48.5 Not stated 2.7 Measles Vaccination Measles I (At 9 months Card) 2.6 Measles II (At 18 months Card) 0.0 Measles II (Mother/ Guardian memory) 59.7 Either (card or memory) 62.3 Number of Individuals (‘000) 63 Source: KIHBS 2015/16 9.1.4 Health outputs The number of trained health personnel is also very low with the doctor population ratio being currently 1:41,538 while the nurse population ratio is 1:2,453. The WHO recommended Doctor and Nurse Population ratio is 1:10,000 for doctors and 1:1,000 for Nurses. This shows that, there is need for recruiting more Doctors and Nurses in the county. The department of Health Garissa County has a personnel strength of 1,483 people consisting of 877 males and 606 females. There are 57 Doctors and 388 Nurses in the County. The five most prevalent diseases in Garissa County are Upper Respiratory Tract Infections, Urinary Tract Infection, Diarrhea diseases, Diseases of the skin and Pneumonia; with a prevalence of 30.9 per cent, 15.2 per cent, and 9.5 per cent, 7.4 per cent and 6.7 per cent respectively. HIV and AIDS general prevalence rate is low at 1 per cent as compared to the 5.6 per cent at the national level, however the adult prevalence rate is at 2.1 per cent as compared to 6.04 per cent at the national level. This however is a sharp increase from zero per cent recorded during the Kenya Demographic Health Survey of 2003. This rise can be attributed, among other reasons, to the fact that only 10 per cent of the population has comprehensive knowledge on HIV prevention as per the Multiple Indicator Cluster Survey (MICS) of 2007 The prevalence of wasting in Garissa County among children 6-59 months is 11.4 per cent (weight for height of less than -2 SD). On the other hand, the prevalence underweight is 13.1 per cent in the county. The prevalence of stunting in the county is 15.6 per cent (KDHS, 2014). These can be attributed to continued food insecurity in the region with a majority 71 Socio-economic status of Garissa County with COVID-19 of the population relying on food assistance, which is vegetable oil, pulses and cereals/rice. The proportion of children under five at a risk of malnutrition based on mid-upper-arm- circumference (MUAC, 2007). The vaccination coverage in Garissa County is 58 per cent. This is attributed to the inaccessibility of the area, long distances to health facilities and poor road network. The maternal health care in the county has improved in the recent past having attained antenatal and post-natal coverage of 48 per cent. The number of mothers delivering at health facilities stand at 40 per cent and those delivering at home is 63 per cent. The county Maternal Mortality Rate (MMR) is at 646/100,000, Infant mortality stood to 33/1000 live births and under-5 mortality was 44/1000 live births (KDHS,2014). There is need to put in place programmes and upscale, the existing initiative geared towards improving maternal health care in the county. Table 9.6: Health indicators in Garissa County Key Health Indicators County Estimates Maternal and Child Services Skilled delivery (per cent) 39.8 Children born at home 62.7 Fully immunized child 57.9 Child Mortality Infant mortality (*/1000) 33 Under-5 mortality (*/1000) 44 Neo-natal mortality (*/1000) 24 Nutrition Status Stunted children (per cent) 15.6 Wasted children (per cent) 11.4 Underweight children (per cent) 13.1 HIV (per cent) HIV adult prevalence (per cent) 2.1 Children with HIV(No.) 0 ART adult coverage (per cent) 55 ART children coverage (per cent) 13 Source: KDHS, 2014; DHIS 2018 9.2 Effects of COVID-19 Following the directive by His Excellency the President to lockdown the Country to curb the spread of the virus, Garissa County prepared for the pandemic by securing and preparing quarantine centers. The existing COVID-19 cases within the Garissa Township have been monitored by the County pursuant to the Ministry of Health guidelines, also in collaboration with UNHCR who have tracked cases within the Refugee Camps. 72 Health As of June 2020, the County did not have a COVID-19 testing center thus all the samples were taken to Wajir or Nairobi for testing. However, they preferred sending the samples for testing to Nairobi since the infrastructure is better and faster. The County collaborated with NGOs such as the Red Cross to test the temperatures of individuals who enter and leave the County. In collaboration with partners, the county has managed to supply masks to every ward and in public places and has obtained sprayers to disinfect markets. Further, the county has set up washing hand booths at strategic places like hospitals and markets, public office and public areas, where the county has provided water tanks, soaps and sanitizers. The county has also put effort in ensuring there is enough supply of water as well as reviving water points and continuous takes prompt measures to address water challenges where required. In June 2020, Kenya National Bureaus of Statistics conducted a survey of COVID-19. The results showed share of the population that had doctor or healthcare provider testing or confirming to them the status in regards COVID-19 was estimated at 8.4 per cent in 2020 (COVID-19, Wave 2 survey). This small number shows that there is a large population of people in the county who have not yet been tested for COVID-19. Further, only 2 per cent of the population indicated that at least one household member had failed to seek health services and 75 per cent of the population indicated they will be willing to be tested if there was mass testing for COVID-19. Therefore, a lot of awareness need to be created among the county population. Figure 9.1: COVID-19 Testing, 2020 100.0 8.4 2.0 80.0 60.0 74.7 91.6 98.0 40.0 20.0 25.3 0.0 Share of the population that had doctor Share of population that indicated that Share of the population that will be or healthcare provider test them for at least one household member had willing to be tested if there was to be COVID 19 failed to seek health services during mass testing for COVID 19 COVID19 period No Yes Source: COVID-19 Wave 2 (June 2020) SToeuerncaeg:e CpOreVgInDan-1c9ie sW, Saevxeu a2l (aJnudneG e2n0d2e0r )Based Violence (SGBV) are some of the health Tiesseuneasgaef fpecrteinggnathneciyeosu, tShsexinuaGla arinssda GCoeunndtey.r TBhaesecldo sVurieoloefnscceh o(SolGs Bdue to COVID-19 hasnot been any good news, the social impact on the children who are nowV)a tarheo msoemhaes obfe ethne health ishsuugees, tahffeegcitrilncgh iltdheh aysobuetehns aifnfe Gctaerdi,stshais Choausnsteye.n Tohnee cinlotseunrgei rolsf bsecihnogovlisc tdimuse otfot eCeOnaVgIeD-19 has nporte gbneaenc iaens yth gisooisda nlaermwisn,g t.hOet hsoercicahla ilmlenpgaecst eoxnp etrhien cehdildbryetnh ewyhoou tahrsei ncoluwd east Sheoxmuaell yhas been hturagnes,m thitete gdirdli scehaisldes h, aesa brlyeemn aarffriaegcetes,d,D trhuigs, haansd seseunbs otannec eina tbeuns eg.irTlsh ebseeinpgr ovbicletmims sa oref teenage contributed by parental negligence, negative cultural practices, and poverty. They have led ptroegscnhaonocl iderso pthouist, iesa arllyarmmairnriagg. eOst,hdeera tchhsa, lalnedngmeesn etaxlpilelnreiesns.ced by the youths includes Sexually transmitted diseases, early marriages, Drug, and substance abuse. These problems are cOonthterribhuetaeltdh bpyro pbalermenstaaflf encetignlgigyeonucths are Malaria, abortion, abortion dug and substanceabuse (DSA), malaria, mental health,e,m naelnguattriivtieo ncusletxuuraallly ptrraacntsimceitste, danindf epcotivonesrtysu. cThhaesy have led toH IsVchaonodl dAIrDoSp.ouSot,m eearolfy cmonatrrribiaugtiensg, dfaecatothrss,i nacnludd me eidnletnael sisll,nleascsk. of health education, negative cultures as highlighted above, parental negligence and lack of guidance, peer Optrheessru hree,alitllhite prarcoyblaenmds haigffhecptoinvger ytyouletvhesl sa.reT hMe arleasruilats, aobfotrhteiosen, parbooblretmiosn adreugm aenndta sl ubstance aibllnuesses ,(DsuSiAcid),e m, saclhaoroial , dmroepnotuat,l hloewaltehc,o nmoamlnicuatrnidtiosonc siaelxpuraoldlyu cttrivaintys,mloiwttesde lifn-efsetceteiomn, s such as HsItiVgm aan,da nAdIDprSe.m Satoumree doefa tchos.ntTrhiebruetfoinreg, faacctitoonrsn einedclutodeb eidtaleknenestso, plarecvke notf shuecahltfhro meducation, occurring. This can be achieved through parental guidance, economic empowerment, sex education, employment creation among the youths, early school enrolment and guidance and counselling. Lack of adequate health infrastructural facilities7a3cross the county, negatively impact on access and equity in the availability of essential health care aimed at promoting a healthy population that will effectively participate in the development of the nation. Those unable to access the health services are sometimes rendered economically unproductive. In cases where the sick person is the breadwinner, the family may become impoverished. This has led to high cases of dependency. Inaccessibility to health facility has also led to high mortality rates. The average distance to the nearest health facility is 25 Km. There are incidences of health facilities that are not being utilized especially those constructed under the various funding programmes. This is because they lack necessary equipment and are understaffed. Further, there are inadequate public education programmes to encourage Kenyans to change their lifestyles in ways that will improve the health status of individuals, families and communities. The county is undertaking awareness to dissuade the fears among the public most of whom had stopped going to the hospital thus cutting the revenue stream. The local Page 86 of 62 Socio-economic status of Garissa County with COVID-19 negative cultures as highlighted above, parental negligence and lack of guidance, peer pressure, illiteracy and high poverty levels. The results of these problems are mental illness, suicide, school dropout, low economic and social productivity, low self-esteem, stigma, and premature deaths. Therefore, action need to be taken to prevent such from occurring. This can be achieved through parental guidance, economic empowerment, sex education, employment creation among the youths, early school enrolment and guidance and counselling. Lack of adequate health infrastructural facilities across the county, negatively impact on access and equity in the availability of essential health care aimed at promoting a healthy population that will effectively participate in the development of the nation. Those unable to access the health services are sometimes rendered economically unproductive. In cases where the sick person is the breadwinner, the family may become impoverished. This has led to high cases of dependency. Inaccessibility to health facility has also led to high mortality rates. The average distance to the nearest health facility is 25 km. There are incidences of health facilities that are not being utilized especially those constructed under the various funding programmes. This is because they lack necessary equipment and are understaffed. Further, there are inadequate public education programmes to encourage Kenyans to change their lifestyles in ways that will improve the health status of individuals, families and communities. The county is undertaking awareness to dissuade the fears among the public most of whom had stopped going to the hospital thus cutting the revenue stream. The local productions of masks have provided opportunity for revenue creation. The county was also experiencing challenges in meeting her local revenue collection. The county has been experiencing downward trend in revenue collection due to weak systems in place for collecting revenue. However, with more sensitization about COVID-19, people will resume looking for health services from the hospitals and other health centers. This will increase revenue collection in the county. Main raw materials in the health sector are the services offered by health professionals and other employees. Medicine and drugs are also key materials. County is also producing masks, which are in high demand during this COVID-19 period. Access and provision of these materials were affected by the outbreak and spread of the virus, resulting to higher demand relative to the supply. Medical services in Garissa County are inadequate in terms of the number of health facilities and the services provided to the local populace. The county has a total of 126 health facilities comprising of 71 (68 public and three private) level two facilities, seven level four facilities, 19 level three facilities, one level five and five mission health facilities. The health facilities are distributed all over the county. The doctor patient ratio is 1:41,538. People are forced to travel long distances to access health services (average distance to the nearest health facility 35 km). This coupled with poor road network, many of them prefer to forgo treatment. Though the county has been putting a lot of efforts in fighting the pandemic, there other several challenges that have been slowing the fight. Lack of finances- the county had not envisaged a health pandemic of this magnitude hence overreliance on the national government for support. I addition, local revenue collection is bound to happen since 74 Health many economic activities had been disrupted by the country lock down and curfew. Many commodities, which were being sold outside the county, had been affected as well. The county is also likely to face protracted labor disputes especially with medical officers who might demand more risk allowances during this pandemic period. The county is also struggling with the health sector after devolution. There were enough structures to handle the responsibilities given to the county government. There are no enough health workers to serve the large population in the county. Also, there is a problem of procurement of medicine and other drugs as the counties are not allowed to procure for drugs themselves but are forced to buy from KEMSA. This sometimes results into delays in delivery of the needed drugs. The county also does not have adequate bed capacity to handle all her patients. It is in the wake of COVID-19 outbreak that the county has rushed against time to establish more ICU beds. The sector has linkages with the Education, ICT, WASH and Agriculture sectors. There is a direct proportionality between education and health. The high the education level of members of the county, the healthier they are. High level of education reduces instances of disease outbreaks due to ignorance. This particularly reduces health diseases such as sexually transmitted among the youths and adults. Advancement in ICT also helps improve health sector. This is because with ICT, it is easy to scan for diseases and manage the treatment. With advancement in ICT, it is possible to do diagnosis to patients and treat them promptly. A good example is the scan for pregnant mothers and cancer patients. Some countries such as Rwanda, drones are being used to deliver bloods. This is helping in mortality rate reduction. Good water and sewerage facilities also contributes greatly to reduction of diseases such as cholera, typhoid and other waterborne. This is because my maintaining good hygiene such as washing hands after visiting toilets, washing fruits before eating and boiling/treating drinking water. Good disposal of waste by avoiding open defecation and using toilets also helps reduce spread of diseases spread through human waste. Agriculture sector also plays a key role in ensuring that people get balanced diet and good nutrition. This reduces cases of malnutrition and stunted growth among children due to lack of certain nutrients and vitamins. Agriculture also serves as a source of revenue and employment mostly for the females. This reduces cases of family conflicts and stresses, hence reducing mental diseases. 9.3 Opportunities of COVID-19 in Health Sector There is an enhanced collaboration within Frontier FCDC counties, which has resulted into training of the health officers and all the frontline staffs. This collaboration has also seen enhanced intercountry screening and testing centralized at the Coast general hospital. Additionally, due to reduced social contacts many meetings have been taking place virtually. This has provided an opportunity for the development of ICT. This has saved the county money, which could have used in the movement from place to another, conference hall fee as well as accommodation for her staff. This has also promoted of ICT and other communication channels within the county hence speedy transfer of information. The pandemic has also led to utilization of local capacity in production of masks and PPEs. This has promoted growth of local industries, hence creating employment. It has 75 Socio-economic status of Garissa County with COVID-19 also challenged the county government hence exposing the health sector since it lacked enough ICU beds. More attention is now being given to the sector leading to improved health services. The county has also received a number of donations in terms of bed and PPEs which have contribute to general improvement of the health sector in general. 9.4 Emerging Issues The COVID-19 pandemic has increased the demand for isolation centres, admission beds, ICU and HDU beds. It has also overstretched the existing health facilities. Additionally, with spread of pandemic across counties it has created fear among the residents and some of them have opted not to visit the hospital in fear of contracting the virus. The outbreak of the virus has caused the county to reprioritize its health sector priorities and some preventative and promotive health services such: malaria control; expanded programmes on immunization; integrated management of childhood illness; and control and prevention of environmentally communicable diseases have been affected to some extent. 9.5 Recommendations In line with the health status in the county, some of the recommendations that need attention include the following: i) The county should create awareness on availability and importance of free maternity services and address other constraints to access of maternal health services in the county to address risk of contracting COVID-19 in event of visiting any health facility. ii) To reduce high burden of both communicable and non-communicable disease, the county should revamp its Community Health Strategy. This is a community based promotive and preventive health services. To make this more effective, the County should engage Community Health Volunteers (CHVs) and equip them with the relevant resources and skills. iii) The county needs to consistently allocate resources towards nutrition specific and sensitive programmes in the various sectors by establishing specific budget lines for nutrition support initiatives. iv) More sensitization about negative effects of FGM and Early marriages need to be carried out by the county government in collaboration with national government and other change agents. v) The county should revamp, expand, modernize and equip health facilities and recruit additional public health officers and Community health workers to strengthen preventive and primary health systems. vi) The county should invest in research and development to spur innovation in health sector including in the area of service provision and medicine. 76 Health vii) The county should also implement a comprehensive human resource health management system including undertaking training needs assessments to ensure skilled and motivated health care workers are equitably deployed. viii) Promote and support public and community health including the installation of hand washing facilities in homes and institutions such as schools, workplaces and health care facilities within Garissa County. ix) Address the mental health needs including those of the health workforce, mental illnesses from depression, especially in response to shut-downs, economic downturns, uncustomary care and burial of affected relatives. 77 Socio-economic status of Garissa County with COVID-19 10. Education and Training 10.1 Characteristics of the sector The county has 131 primary schools with a total enrolment rate of 41,474 consisting of 24,939 boys and 16,535 girls. The enrolment rate is low in the county. The primary school net enrolment rate is 23.5 per cent while the completion rate is 62.7 per cent. The transition rate stands at 58.3 per cent. This is due to the nomadic lifestyle of the people and early marriages among the girl children. The county has 18 secondary schools with a total enrolment of 6,580 students with 4,774 boys and 1,806 girls. This represents four per cent of the secondary school age population. The secondary school net enrolment rate is 3.50 per cent and the completion rate is 77 per cent. Garissa County has 184 Early Childhood Development Education (ECDE) Centres with a total enrolment of 24,091 consisting of 13,285 boys and 10,806 girlsThe pre-school net enrolment rate is 9.6 per cent and the completion rate is 89.34 per cent while the retention rate is 11 per cent. This is due to the nomadic lifestyle of the people. In addition to formal schooling there are also Madarasa where young children are taught religious studies. Public and private university campuses are being set up in the town. These include the Kenyatta University and Al Mustaqbal University. There is one Science and Technology Institute, North Eastern Technical Training Institute, one Kenya Medical Training College and one Teachers Training College all located in Garissa town. The county also has three youth polytechnics; one each in Bura East, Dadaab and Garissa. In addition, there are six private accredited colleges and four non-accredited colleges in Garissa. About 80 per cent of public primary schools in Garissa County have been installed with ICT infrastructure and devices under the Digital Literacy Programme (DLP) (ICT Authority, 2019). The infrastructures include learner digital devices (LDD), teacher digital devices (TDD) and the Digital Content Server and Wireless Router (DCSWR). 10.1.1 Gross Attendance Ratio (GAR) and Net Attendance Ratio (NAR) The Gross Attendance Rate (GAR) for pre-primary school was 12.3 per cent while that of primary school and secondary school was 59.1 and 43.9 per cent respectively in 2015/16 (Table 10.1). Gross Attendance Ratio (GAR) represents the total number of persons attending school regardless of their age, expressed as a percentage of the official school age population for a specific level of education. The GAR for pre-primary school was higher for males, 12.5 per cent, compared to that for females, 12 per cent. The GAR for primary school was higher for males, 64.8 per cent, compared to that for females, 52.9 per cent. The GAR for secondary school was higher for males, 52.4 per cent, compared to that for females, 35.6 per cent. Net Attendance Ratio (NAR) is the total number of persons in the official school 78 Education and Training age group attending a specific education level to the total population in that age group. Table 10.1 shows that total NAR for pre-primary, primary and secondary school was 4.4 per cent, 37.8 per cent and 17.2 per cent, respectively. Table 10.1: Gross Attendance Ratio and Net Attendance Ratio by Educational Level in Garissa County Education Level Gender Gross Attendance Net Attendance Ratio Ratio Pre-Primary School Male 12.5 1.9 Female 12 6.8 Total 12.3 4.4 Primary School Male 64.8 41.8 Female 52.9 33.5 Total 59.1 37.8 Secondary School Male 52.4 15.3 Female 35.6 19.0 Total 43.9 17.2 Source: KIHBS 2015/16 10.1.2 Basic education gross and net enrolment rate The preprimary gross enrolment rate in the county was 12.3 per cent in 2018 and while the net enrolment rate was 4.4 per cent (table 10.2). The Gross Primary and Secondary enrolment rates stood at 59.1 per cent and 43.9 per cent respectively in 2018 while the Net enrolment rates (NER) were 37.8 per cent and 17.2 per cent for primary school and secondary school respectively during the same period. The huge difference between primary and secondary school enrolment is due to primary to secondary school dropouts. Free primary education policy has substantially increased school enrollment rates. The success and sustainability depend on teachers’ perception, motivation, and proper implementation of the policy in the classroom. Table 10.2:Gross and net enrolment rate (per cent), 2018 Preprimary Total Gross Enrollment rate (GER)(per cent) 12.3 Net Enrollment rate (NER)(per cent) 4.4 Gender parity index .8 Primary Gross Enrollment rate (GER)(per cent) 59.1 Net Enrollment rate (NER)(per cent) 37.8 Gender parity index .8 Secondary 79 Socio-economic status of Garissa County with COVID-19 Gross Enrollment rate (GER)(per cent) 43.9 Net Enrollment rate (NER)(per cent) 17.2 Gender parity index .8 Source: Education statistical booklets 2014-2018 10.1.3 Literacy The analysis of literacy is based on respondents’ self-assessment as no reading and writing tests were administered during the data collection. Further it was assumed that anybody with secondary level of schooling and above could read and write. The percentage distribution of population aged 15 years and above by ability to read and write is presented in Table 10.3. The proportion of literate population in the county was 41.7 per cent with the male population being more literate (53.6%) compared to their female counterparts (30.3%). Table 10.3: Percentage Distribution of Population aged 15 Years and above by Ability to Read and Write (per cent) Ability to Read and Write Percentage Distribution (per cent) Overall county Literate 41.7 Illiterate 56.8 Not Stated 1.4 Number of Individuals (‘000) 203 Male Literate 53.6 Illiterate 45.7 Not Stated 0.8 Number of Individuals (‘000) 100 Female Literate 30.3 Illiterate 67.6 Not Stated 2.1 Number of Individuals (‘000) 104 Source: KIHBS 2015/16 10.1.4 Educational Attainment The distribution of population aged 3 years and above by educational qualification attained is presented in Table 10.4. Approximately 63.5 per cent of the population do not have any educational qualification. This is high than the national percentage of 49.7. Only 0.7 per cent of the population has attained university degree. The proportion of the population with CPE/ KCPE qualification is 21.1 per cent and that of KCE/ KCSE qualification is 7.1 per cent. 80 Education and Training Table 10.4: Percentage Distribution of Population by Highest Educational Qualification Highest Educational Qualification Percentage Distribution of Population None 63.5 CPE/ KCPE 21.1 KAPE 0 KJSE 0 KCE/ KCSE 7.1 KACE/ EAACE 0 Certificate 1.8 Diploma 1.7 Degree 0.7 Basic/post literacy certificate 0.3 Other 0.7 Not Stated 3 Number of individuals (‘000) 150 Source: KIHBS 2015/16 Percentage distribution of Garissa County residents aged 3 years and above who had ever attended school by the highest level reached, and sex is presented in table 10.5. The proportion of males who had reached primary school level was 59.6 per cent while that of females was 67.4 per cent. for all persons who reported to have attended school, 6.3 per cent of males and 9.7 per cent females had reached pre-primary school level in the County. There was a high disparity between the proportion of persons who had reached university education level, with male recording a higher percentage than female at 2.5 per cent and 0.1 per cent, respectively. Table 10.5: Percentage Distribution of Residents 3 Years and above who had ever Attended School by Highest Level Reached, and Sex for Garissa County (per cent) Educational Level Gender Percentage Distribution of Population 3 Years and above Pre-primary Male 6.3 Female 9.7 Primary Male 59.6 Female 67.4 Post primary Male 0.7 vocational Female 0 Secondary Male 20.1 Female 13.6 81 Socio-economic status of Garissa County with COVID-19 College (Middle-level) Male 3.3 Female 2.3 University Male 2.5 Female 0.1 Madrassa / Duksi Male 5.2 Female 4.4 Other Male 0 Female 0 Not Stated Male 2.2 Female 2.6 Number of Individuals Male 89 (‘000) Female 61 Source: KIHBS 2015/16 The closing down of schools has worsened the situation. Cases of Female Genital Mutilation have increased tremendously, including child marriage, defilement and domestic violence. In collaboration, the county government together with the Anti-FGM Board had beefed community vigilance. There also cases of drug and substance abuse, depression and school dropout. Several factors are attributed to the number of students declining as the pupils transit from primary to secondary. They include Early marriages mostly among the girls, teenage pregnancies where girls drop out of school after becoming pregnant for the few of ridicule by colleagues, Lack of school fee especially if one is admitted in a boarding school, Drug and Substance abuse, school absenteeism by teachers and pupils and indiscipline among some pupils leading to expulsion. These challenges have been contributed by many factors such poor parenting which leaving children unguided, poverty which pushes girls to be married at early age, negative cultural practices such as FGM and forced early marriages, peer pressure and easy dugs accessibility. To address the issues, there is need to create awareness against drug and substance abuse, offer guidance and counselling to students, introduce free and compulsory secondary education, discourage negative cultural practices that affects school attendance and ensure there is no teacher absenteeism There are 229 teachers hence a teacher pupil ratio of 1:105. There are 672 teachers giving a teacher pupil ratio stands at 1:61. The teacher student ratio stands at 1: 36. Private schools could not sustain the salary for their employees, both teaching and support staffs (casuals) staff. Public schools have also faced challenges in making payment for the other expenses such as electricity and security bills. This because the national government had not released the money to the schools. Apart from the other expenses, public schools cannot pay teachers who were hired on contracts and were under BOGs. There are three main players as far as education is concerned. We have parents, teachers and students. Other stakeholders include county and national governments as well as the donors. They play a critical role in ensuring that the education is supported, and learners are learning smoothly. Their interaction brings about success in the education sector. There are several constraints in the education sector. The main one right now is COVID-19 which led to closing of schools. This has disrupted education calendar posing a great 82 Education and Training challenge to both county and national government. The national government announced that the education calendar 2020 a waste. Closure of all schools has led to loss to learning time and teaching time. The school infrastructure in the County is not only limited but also is of poor quality. High Illiteracy level is another issue of concern as not all county persons can read and write. Lack of parental guidance and early marriages are other challenges being experienced. There is also lack of enough ICT infrastructure in the county making it difficult for the online learning to take place. 10.1.5 ICT in education The county has also low internet access (6.3 percent) which constrain online learning across the County. Furthermore, only 2.6 per cent of the households had access to ICT equipment such as laptops and computers. This makes it difficult for the pupils and other students to benefit from national learning programme which had been started by the government. Even if the programme was to be done through radio, it would be difficult since only 47.8 per cent of the county population has a radio. Figure 10.1: Access to ICT in Households and Schools (%) Source: Kenya Population and Housing Census (KPHS, 2019). Agriculture provides food for the school going children. Therefore, it plays a key role in ensuring that the school going children get food of the required quality and quantity. It is always children who are in the right health status who are able to concentrate and learn in classes. Therefore, good health ensures continuity of learning among the pupils and students. It is in schools where children are taught about good health hygiene which contributes in reduced diseases spread. ICT plays a key role especially now that schools have been closed down and people are advocating for online classes. Good internet connectivity, possession of laptop/desktop computer, iPad, TV, and radio would greatly facilitate the online learning. 10.2 Opportunities of COVID-19 in Education and Training The demand for PPEs such as masks in the County has led to local production by VTCs hence creating employment and income for youth. It will however be important to address issues of standards and quality of the local produced PPEs. COVID-19 pandemic has also provided opportunity for the county government to forge partnerships to ensure enough 83 Socio-economic status of Garissa County with COVID-19 network coverage across all the sub-counties and counties in the Central region. There is also the opportunity of exploring online classes. This if effective, can save time spent on travelling from home to schools to teach. Teachers will be able to reach at the comfort of their seats. This can reduce the cases of lateness and absenteeism. Learning from homes will also reduce accidents and injuries among pupils at school. It will also reduce indiscipline and drug abuse as parents will be able to closely monitor their children at home. The disease has also created an opportunity for creativity among students who are involved in making of ventilators and researching on vaccines. 10.3 Emerging Issues The County with support from stakeholders will need to continue to invest in early childhood development through infrastructural development to allow for adequate social distancing when schools reopen; deployment of ECDE teachers, provision of sanitation facilities and enhanced school feeding programme. To achieve these objectives, the county will require to partner with the national government and private sector to enhance ECDE and vocation training through infrastructural development as well as equipment of all ECDE, primary, secondary and vocational training, and University branches in the County with adequate WASH and adequate learning spaces upon reopening. High cases of school dropout especially transition from primary to secondary level of education. There is also the issue of drug and substance abuse among the students which need to addressed has it has great impact on education. There is the issue of low ICT development in the county. Recruitment of school going children into terror groups. 10.4 Recommendations i) The County with support from stakeholders should continue to invest in early childhood development through infrastructural development to allow for adequate social distancing when schools reopen; deployment of ECDE teachers and provision of sanitation facilities. ii) The county should involve communities to mobilize learners when schools will be reopening process and while deepening implementation of COVID-19 mitigation measures. The county will combine community participation and large-scale direct communication campaigns to parents, and where possible, increase attendance options to accommodate all children, including those with highest risk of dropping out, also promote back to school campaign and community outreach to ensure that no child is being dropped out of school due to COVID-19 emergency. iii) The County should prioritize projects that improve school water, sanitation and hygiene facilities and management in order to reduce future effect of similar or related outbreak while promoting public health in learning institutions. iv) The county should promote remedial/catch up lessons for learners who might have lagged behind also schools to utilize ICT platforms and have a depository of teaching and learning materials that learners could use at their own time and while at home. 84 Education and Training v) The county should provide financial or in-kind support, such as school feeding, to help families overcome the increased costs of attending school, also provide psychosocial support to teachers and learners. vi) Concerted efforts will also be required to fight drug and substance abuse among the youths in the county. This can be done through counseling and ensuring that they are not idle especially this period when learning institutions are locked. vii) Government needs to come in and support private institutions which are facing threat of closure due to losses as a result of closing school indefinitely. This can involve giving grants and loans to the private schools. 85 Socio-economic status of Garissa County with COVID-19 11. Social Protection 11.1 Characteristics of the sector 11.1.1 Sources of vulnerabilities in the County According to the KNBS census 2019, Garissa County has a population of 841,352 of which 1.7 per cent are the elderly and 0.7 per cent are people living with disabilities which is among the lowest in the country. The overall poverty rates in the county stand at 66per cent which is higher than the national average of 36.1 per cent. The county’s food poverty levels are at 66per cent and 46 per cent of the total population is multidimensionally poor. Further, about 16 per cent of the children population is stunted. The impact of the COVID-19 to the county’s economy cannot be gainsaid. 11.1.2 Severe shocks to the households Severe shocks have had negative impact to the household’s economic and social welfare of county residents. Table 11.1 presents the proportion of households by the first severe shock in the county. The major shock in the county was droughts or floods which affected 41.7 per cent of the households followed by Severe water shortage, dearth of livestock and large rise in price of food which affected 21 percent,12.8 per cent and 11.1 per cent of the households in the county, respectively. Death of family Members and Loss of salaried employment or non- payment of salary were also other major shocks in the county affecting 8 per cent and 2.5 per cent, respectively. Table 11.1: The proportion of households by the First Severe Shock in the County The proportion of First Severe Shock households (per cent) Droughts or Floods 41.7 Crop disease or crop pests 0 Livestock died 12.8 Livestock were stolen 0.7 Household business failure, nonagricultural 0 Loss of salaried employment or non-payment of salary 2.5 86 Social Protection End of regular assistance, aid, or remittances from outside the household 0 Large fall in sale prices for crops 0 Large rise in price of food 11.1 Large rise in agricultural input prices - Severe water shortage 21 Birth in the household 1 Death of household head - Death of working member of household 1 Death of other family Member 8 Break-up of the household - Bread winner jailed - Fire 1 Robbery / Burglary / Assault - Carjacking - Dwelling damaged, destroyed - Eviction - Ethnic/ Clan Clashes - Conflict - HIV/ AIDS Other 4 Number of households with Shock 22,000 Source: KIHBS 2015/16 11.1.3 Distribution of Social Assistance Beneficiaries Households in the county received various forms of social assistance or transfers or gift either in form of a good, service, financial asset or other asset by an individual, household or institution. Transfers constitute income that the household receives without working for it and augments household income by improving its welfare. Cash transfers include assistance in form of currency or transferable deposits such as cheque and money orders. The proportion of households that received cash transfers by source, household headship, residence and county is presented in Table 11.2. Overall, 6 per cent of the households received cash transfers. A higher proportion of households received transfers from within the country (93%), mainly from individuals (93%) while external transfers constituted 13 per cent. 87 Socio-economic status of Garissa County with COVID-19 Table 11.2: The proportion of households that received cash transfers by source, and household headship Beneficiaries Total Number of Households 78,000 Households receiving transfers (per cent) 6 From Inside Kenya Individual 69,043 Non Profit Institution - National Government 5,798 County Government - Corporate Sector - Inside Kenya 74,840 Outside Kenya 10,350 Total 79,149 Number of households that received 5,000 transfers Source: KIHBS 2015/16 The county has tried to reduce by half the proportion of people living on less than a dollar a day. The absolute poverty level in Garissa County currently stands at 50 per cent. This can be attributed to the harsh climatic condition coupled with the high dependence on relief food supplies. In the recent past however, there has been a massive expansion of irrigation farming along the river Tana. The government has also come up with various interventions such as the Youth and Women Enterprise Funds, Njaa Marufuku Kenya, Cash Transfers for the elderly, Orphans and Vulnerable Children (OVC) program among others. There is also several Non-Governmental Organizations offering a variety of cash transfers for social security safety nets. This has seen a large proportion of the population receiving these cash transfers. The county has partnered with several individuals and organization like Red Cross, KNHRC, UNICEF, WHO who have donated food and other materials to the vulnerable groups. So far, the county has supported about 7,000 households with food hampers, water, and water tanks. More households need to be covered. Some of the recipients of free masks offered by the county government include children’s homes, prisoners, and refugee camps. Youth engagements activities were halted thus affecting counter-extremism fora, sports, and agri-business. Also, religious teachers who engage youth in Madrasas have been rendered jobless. Youth constitutes about 28.5 per cent of the total population. The county’s youthful population is therefore large, and more resources should be allocated towards activities and programmes that will benefit the youth. These include setting up of more vocational institutions, technical institutions, and putting in place policies that promote job creation for the youth. The social and economic effects of the COVID-19 pandemic increased households’ susceptibility to Gender Based Violence (GBV) in the county. Response measures taken to contain the COVID-19 pandemic, such as movement restrictions, lockdown, and curfew hours, have led to loss of income, isolation, high levels of stress and anxiety exposing 88 Social Protection household members to psychological, economic, sexual violence and physical harm as couples spend more time in close contact. Other challenges affecting the youth include unemployment and drug use, especially alcohol and substance abuse. Livestock Markets were closed which mostly serve as places of trade. Most people in this market are females. This has therefore affected their welfare in terms of finances and access to food and other goods. This has an impact of lowering their living standards. Livestock markets were closed making it hard for people to sell their livestock which serves as a main source of income. This has therefore reduced their income with some operating at losses. Shops and Kiosks, social centers such as club and bars, hotels have been affected by the curfew and social distance requirements thus reducing the amount of income that they get. Unemployment rate in the county has increased due to close of many businesses and learning institutions. This has led to the decline in living standards and family conflicts due to limited sources of income. Most of the social protection operations were undertaken through non-contributory transfers in cash for the elderly, OVCs and PWDS. In some instances, in kind transfers which include school feeding programmes were also used to reach a wider audience and age group. The county revenue collection declined because of outbreak of COVID-19. The border points were closed hence no people were allowed to leave the county through them to other counties. This has affected most businesses which serve as a source of income for many families. Resumption of services and free movement across borders and opening of markets will enable the county to collect bore revenue, hence boosting her targets. The main source of revenue to implement social protection activities in the county were mostly government budgetary allocations and donor contribution to OVCs, PWDs, and the elderly. The county government has been complementing the work of the national government on taking care of the OVCs. The county government aims at protecting children from abuse, neglect, and discrimination in accordance with the Children’s Act, 2001, and the Education Act, 2012. Loss of jobs and business opportunities led to an increase in poverty and declining of people welfare. With loss of jobs and businesses, most youths were involved in the activities such as crimes, prostitution, and other social evils. Job losses also increased suffering among county residents. In addition, decreased county revenue made it hard for the county to cater for the needy cases and mostly those affected by COVID-19. In addition, unemployment and recruitment to the terror groups posed a great danger to the youths in the county. Social protection is directly linked to the health sector. When people’s social welfare is good, that is people have good health insurance, they can be able to access health services in case of sickness. When people welfare is affected by loss of employment and closing of businesses, they are more likely to suffer from diseases such as stress and depression. ICT also plays a key role in terms of information dissemination through media such as radio, television, mobile phones e.tc. Communication is key especially for the people in business as one need to place order for goods or services. ICT is also involved in record keeping of those people in schemes such as NHIF and NSSF as well as other insurances. Additionally, social protection is directly related to education. The more one is educated the more is informed of existing welfare schemes. Educated people also are aware of the 89 Socio-economic status of Garissa County with COVID-19 need for and importance of engaging in social protection programmes such as insurance and investment for future to benefit after retirements. With good education, one can understand government role in ensuring good life for its citizens. Agriculture is the main source of revenue in the country and most of the counties. Garissa county is not an exception. Majority of people are involved in livestock keeping and farming. This provides people with source of food as well as revenue which is used to improve their welfare. Agricultural sector also creates employment among many county residents who would otherwise have been jobless. Trade and industry play an important role bettering life of the residents. This is where majority of people derive their livelihood from especially those engaging SMEs. The profits and savings obtained from business is used in feeding the family members as well as insuring them in future. 11.2 Opportunities of COVID-19 in social protection COVID-19 exposed lack of preparedness among counties in terms of responding to the emergencies such as COVID-19 pandemic. It provided an opportunity to measure how county governments are prepared to handle the devolved functions. Health being a devolved function, it has really exposed the counties as many of them lack required health facilities such as ICU beds and enough medical personnel. The virus has also given an opportunity to develop social protection programs to cushion the vulnerable groups in the community in case of outbreak of other diseases. 11.3 Emerging Issues Due to social distancing and curfew hours, GBV victims had limited contact with family and friends who would act as the first contact persons during violence. Survivors also experienced challenges accessing healthcare services, counselling services and access shelters. These challenges underscore the need for deliberate measures at the county level to prevent and support GBV survivors in times of emergencies as experienced with the pandemic. Further, the pandemic has exposed the level of lack of comprehensive social protection at the county level. 11.4 Recommendations COVID-19 pandemic created effects with immediate and long-term economic consequences for children, PWDs, elderly and their families. In an effort to strengthen social protection response in face of a similar pandemic, the Garissa County government should: i) Form economic block partnership to ensure borders are manned and enhance cross border screening especially among long distance drivers. This will drastically slow the spread of the virus. ii) Conduct mass civic education among the people on COVID-19 prevention measures, how to handle an infected person and avoidance of stigmatization of the affected person. 90 Social Protection iii) Enroll more county residents in welfare programmes such as NHIF which will ensure that they access medical treatment in case of falling sick. iv) Give tax exemption for the SMES who have suffered losses in their business as result of diseases outbreak. v) Create a kit where they can collaborate with local banks in offering loans to the SMEs to restart and boost their businesses. vi) Provide food and other basic wants for the elderly since their movement have been reduced as they are at great risk of contracting the virus. Therefore, their life has been affected and cannot afford to feed themselves anymore. vii) Have programmes to incorporate youths in development are needed. This will ensure they do not get involved in drug and substance abuse and other crimes. More employment opportunities to be created for the youths. This will ensure they do not remain idle hence joining terror groups. Garissa County has a population distribution of more male (54.6%) than female (45.4%). The Kenya Health Information System (KHIS, 2020) reported 1,417 cases of teenage pregnancies between January and May 2020. While this is a drop from 1,992 cases compared to a similar period in 2019, there is need to ensure zero tolerance to such cases since they are associated with high rates of school dropouts, stigma, increased mental health concerns, postpartum depression and suicidal ideation. The May 2020 KNBS COVID_19 survey indicates that 14.9 per cent of the respondents in the County had witnessed or heard of any form of domestic violence. According to the Healthcare Assistance Kenya (HAK) 2020, the county recorded 2 cases of GBV in April 2020. To address the gender related challenges, the County will: i) Strengthen enforcement of laws related to teenage pregnancies especially where adults are involved. ii) Prioritize elimination of gender stereotypes, transforming gender norms and revoke discriminatory practises for effective realization of the rights of women and girls. iii) Community training and sensitization programmes targeting teenage boys and girls to deal with increased cases of teenage pregnancies. iv) Identify and train champions (individual actors) including using elders active in combating GBV and who can carry advocacy messages and contribute strongly to changing harmful and retrogressive practices. v) Launch hotlines/helplines using toll-free calls and SMS numbers for gender-based violence victims. This will assist GBV victims access support and guidance to include psycho-social support, counselling and health care. vi) Collaboration between the county, state agencies, and other partners to strengthen capacities of various stakeholders including, political leadership within the county, women’s groups, religious leaders, and community leaders to combat harmful practices that breed GBV. vii) Designate gender safe spaces to provide accommodation GBV survivors 91 Socio-economic status of Garissa County with COVID-19 12. Human Resources 12.1 Characteristics of the Sector 12.1.1 Sources of employment in the County Pastoralism, agriculture, and trade sub-sectors are the main sources of employment in the county. This population sells livestock, livestock products, vegetables and fruits, through retail and wholesale business operations in the county. Other sources of employment are government departments, Non-Governmental Organizations, donor agencies and business organizations. Most of these wage earners are in formal employment. About three per cent of the total population is self-employed and they engage in milk vending, jua kali, hawking and livestock selling among others economic activities. Youths’ unemployment rate remains high in the county which has contributed to increase in insecurity and terrorism in the county. Table 12.1: Distribution of Population Age 5 Years and above by Activity Status, and Sex in the County Male Female Total Population 397,437 326,443 723,880 Working 142,610 110,683 253,293 Seeking Work/ No Work Available 101,275 71,721 172,996 Persons outside the Labour Force 153,459 143,980 297,439 Not Stated 93 59 152 per cent Working 58.5 60.7 59.4 per cent Seeking Work/ No Work Available 41.5 39.3 40.6 Source: KNBS 2019 Distribution of Population Age 5 Years and above by Activity Status, and Sex in the County is shown in Table 12.1 above. An assessment on the county labour force indicates the County population aged 15-64 years (labour force) was estimated at 60,650 people of whom 27,604 people were working and 33,046 were seeking work but work was not available representing an unemployment rate of 54.5 per cent (Kenya Population and Housing Census 2019). 12.2 Effects of COVID-19 With the loss of jobs in the Small and Medium Enterprises the livelihood of people working in these sectors were directly or indirectly affected, particularly youths as the sector employs most of the young population. In addition, the reduction in operation hours and restriction on movement in and outside Nairobi negatively impacted on the transport sector 92 Human Resources with many relying on it rendered jobless. The loss of jobs in the matatu and boda-boda industry had directly impacted on the lives of the youth as some residents avoided public means of transport in fear of contracting the virus. In addition, the lockdowns in Mombasa and Nairobi counties had a negative impact on long distance drivers in these sectors. The impacts of the pandemic were also felt on the service sectors as it affected workers in both private and public sector. Several people working in restaurants and bars were rendered jobless due closure as ordered by the government. The unemployment has increased during the period of COVID-19, according to May 2020 KNBS COVID-19 Survey, 19.9 per cent of the county labour force worked at least for 1 hour for pay; 38.2 per cent had never worked, and 41.9 per cent worked in the informal sector. However,4.2 per cent of employees did not attend to work due to COVID-19 with other 79.2 per cent of employees working without any pay. On average, workers in the County lost 13.4 hours per week due to COVID-19 During the pandemic, about 6.5 per cent of workers in the county were casual workers 29.2 per cent were regular workers (full time), 6.7 per cent employees were working as part time. However, about 28.7 per cent of workers reported decrease in income while 5.3 per cent of people reported to have experienced increased income. These could be the people working in the health sector who are supplying medical equipment such as masks and PPEs. About 6.7 per cent of workers indicated to have benefited from government tax exemptions which indicates about 93 per cent did not benefit from National government tax relief for low- income-earning persons, a reduction in the top Pay-As-You-Earn (PAYE) rate, and other changes such as cash transfers, credit relief, lower VAT, and a corporate tax cut. Figure 12.1: Effects of COVID-19, 2020 a) Effect of COVID-19 on Jobs b) Effect of COVID-19 on Incomes Source: May 2020 KNBS COVID-19 Survey According to the May 2020 KNBS COVID-19 Survey workers in professional, scientific, and technical activities recorded the highest number of hours lost per week (25.5 hours) followed by workers in education and information and communication who lost 24.0 hours, 22.0 hours per week, respectively (Figure 12.2). Workers in financial and insurance activities lost 20.0 hours in a week while workers in administrative and support service activities lost 12.6 hours in a week. Workers in human health and social work activities services lost 8.0 hours in a week, while workers in construction and manufacturing lost 9.5 and 6.0 hours in a week, respectively. 93 Socio-economic status of Garissa County with COVID-19 Figure 12.2: Difference between usual hours worked and actual hours worked during COVID-19 period Source: May 2020 COVID-19 Survey Further, 29.0 per cent of workers in Garissa County recorded decreased income; 76.9 per cent recorded working as unpaid workers; and 4.2 per cent never attended to work due to COVID-19 related activities. In private sector schools, teachers and other workers lost their incomes. Some other businesses such as bars, hotels, market centres were totally closed, leading to reduced business activities. Some workers in the transport sector had also been rendered jobless due to restrictions of moving in and out of Nairobi and Mombasa counties. On average, the county lost 13.4 hours worked in a week and the hours lost in the leading economic activities of the county like service sector (16.0 hours) and agriculture sector (8.6 hours) will negatively affect the county economy. 12.3 Opportunities of COVID-19 in human resource sector The county government have been provided with the opportunity to use digital platforms to enable remote access to jobs for their employees where the Human Resource Management will have an essential role to play in navigation of the situation caused by the pandemic. There have been notable efforts by the county government to invest more money in training health workers. The county government now has an opportunity to recalibrate its employees and develop strategies (mid- and post-pandemic strategies) to adapt to the evolving reality. ICT was very significant and had enabled the county programs to run smoothly since the pandemic and provided an opportunity for exploitation for adequate internet coverage especially to the education sector. The pandemic has provided opportunity for county government to invest more money in training health workers. The economic block can serve as a market for the locally produced goods, hence creating more employments. 94 Human Resources The county government has created opportunities for the youths so that they can get some income especially during this period of COVID-19. For example, county launched the Kazi Mtaani National Hygiene Programme (NHP) initiative to give youths a source of income. The countrywide programme being implemented jointly by the national and the county governments will benefit some 3,000 youths from Garissa. 12.4 Emerging issues The COVID-19 pandemic has expedited the speed at which different firms and businesses within the county are changing their pay programmes through pay reductions and incentive resets. The county governor and his deputy experienced a 30 per cent pay cut. In addition, the County executives took a 20 per cent pay cut while county chief officers took 15 per cent pay cut. There has been reframing of the way the county government segment its workforces to include essential and frontline workers especially in health sector. As it continues, the county will consider long-term strategies to determine which changes will be temporary versus those that will be permanent. With the widespread stay-at-home orders, most of county employers are adjusting operations and shifting workforces online, all of which have affected overall employee well- being. The county is not well prepared in terms of response to health-related risks such as the current COVID-19. Opportunities within the regional economic block needs to be exploited to enhance economic competitive advantage. There are emerging talents among the youths which can tapped to benefit the county especially this time of COVID-19 such as making of ICU bed, masks and PPEs. There is an increase in unemployment rate. 12.5 Recommendations i) Promote implementation of a stronger labour market interventions and policy reforms that drive employment creation. The County shall deepen technical education, training and skills development; and invest in livestock sector in the County. ii) Promote investment and entrepreneurship through provision of loans, the county Government will improve access to finance for small and medium enterprises through lending institutions. iii) Formulate measures aimed at encouraging employment creation through corporate social responsibility (CSR), including expanding the national internship programs and promoting Information Technology (IT) enabled jobs. iv) Leverage on private sector programmes such as the Kenya Private Sector Alliance (KEPSA) Foundation KIJANI movement to create green jobs for the unemployed. 95 Socio-economic status of Garissa County with COVID-19 v) Tap into national government programs like Ajira Digital Training Program (ADTP) to enable young people access work opportunities available online and provide them with the right tools, awareness, infrastructure, skills, training, mentorship and access to dignified work that can earn them a decent income. vi) Provide support to Micro, Small and Medium scale Enterprises (MSMEs) through creation of enabling business environment, provision of market information and infrastructure, improving transport systems and provision of affordable energy. In addition, build capacity in areas related to marketing, operations, finance, and human resource development to enhance the chances of survival of SMEs. vii) Invest in ICT and online job opportunities. Access to ICT will contribute to the County’s economic growth by reducing transaction costs, increasing business efficiency, improving education standards and ensuring accountability and transparency in usage of public funds. The County in collaboration with business partners will establish innovation hubs with internet connectivity for use by locals to interface and do business with others across the world, hence increasing their income. 96 13. Conclusion and Key Recommendations 13.1 Conclusion 13.1.1 Fiscal Policy, planning and budgeting The OSR to total revenue averaged 1.22 per cent between FY 2013/14 and FY 2020/21, contributing the least amount of County revenues. County expenditure has over the years been rising as the county escalates its efforts in provision of services to its residents. Total county expenditure has grown significantly since FY 2013/14. In FY 2014/15 the county reported Ksh 460.0 million in pending bills. This increased to Ksh 980.1 million in FY 2017/18 with development spending related pending bills accounting for 872.0 per cent of this. In FY 2018/19 pending bills slowed to Ksh 619.6 million before shooting up to Ksh 877.0 million in FY 2019/20. 13.1.2 Agriculture, livestock and fisheries The Agri-food analysis highlights the sector was negatively affected by COVID-19 in terms of labour supply, trade and marketing operations, food supply and the resulting effects on food prices. At the peak of the COVID-19 pandemic period, the County also suffered from desert locusts, floods and livestock diseases. The County’s agricultural productivity is also affected by: - variable and extreme weather events Poor and inadequate infrastructure; water scarcity; low agro-processing and value addition opportunities; dependence on rainfed agriculture; low access to quality and affordable inputs; low commercialization levels and marketing opportunities; low access to major off-farm services including extension, climate and market information, and credit services; pests and livestock diseases; and farm losses and post-harvest waste. This adversely affects the productivity of the sector and impairs marketing and consequently places livelihoods and food security at risk especially in times of emergencies. The analysis calls for strategies to enhance productivity, profitability, and resilience of the sector for improved livelihoods. 13.1.3 Water sanitation and hygiene The county relies more on surface water as well as water from dug wells and piped water for rural households. Similarly, ssanitation, coverage remain low in the county, with majority of households having no toilet facilities, thus helping themselves in the bush, there is also low access to piped sewer. The county has an opportunity to increase sanitation coverage by connecting households to sewer as well as to piped water to increase its additional revenue collection from sanitation and water services. 97 Socio-economic status of Garissa County with COVID-19 13.1.4 Manufacturing, trade and MSMEs Garissa County’s Manufacturing, Trade and MSMEs momentum was disrupted by the COVID-19 pandemic as the containment measures associated with COVID-19 pandemic took a heavy toll on the sector. In sustaining growth and building resilience in this sector, it is important to strengthen trade and production capacity of MSMEs and especially those involved in manufacturing in the County by exploiting opportunities afforded by the pandemic such as production of masks, PPEs, hospital beds, ventilators, reagents, gloves, and sanitizers. 13.1.5 Infrastructure, Housing and Urban Development The main means of transport used in the County is walking at 26.32 per cent, followed by bicycle (bodaboda). The paved County road network covers 6.51 km, while the paved National roads cover 31.37 km. Out of the total paved road network of 37.88 km, 83.95 per cent is in good condition, 10.93 per cent in fair condition and 5.12 per cent in poor condition. The status of ICT access and use in the county is low, especially among households. The perception of that the individual does not need to use the internet, lack of knowledge and skills on internet are the leading reasons that the people of in the County do not have internet connection. Majority of the households (89.5%) did not receive a waiver or relief on payment of rent from the landlord, despite inability to pay due to the pandemic. The housing tenure is predominantly owner occupied at 87.4 per cent, with 12.6 per cent of the households under rental tenure. 13.1.6 Tourism The key tourism attractions from Garissa County are wildlife, heritage and culture (rich Somali traditional culture) and hospitality. The proximity of the county to the tourist coastal town of Lamu makes it ideal for linkage through a tourist circuit. The County does not have classified (star-rated) hotels. However, there are 5 major hotels with a bed capacity of 450. The county has 6 wildlife conservation areas namely, Garissa Giraffe sanctuary, Ishaqbin Community Conservancy, Waso Conservancy, Arawale National Reserve, Rahole National Reserve and Boni National Reserve. 13.1.7 Health Under the health sector, there is need for more awareness on immunization so that mothers can ensure their children get immunized. Implement a comprehensive human resource health management system including undertaking training needs assessments and information system to ensure skilled and motivated health care workers, equitable deployed across all sub-counties. This is in addition to paying the salaries in time to avoid cases of strikes and low staff morale. Recruit additional of public health officers and community health workers to strengthen preventive and public health systems. COVID-19 has worsened the situation as far as youths and women are concerned. These are the groups of people that have been facing several challenges even before the outbreak of the COVID-19. FGM and Gender based violence cases have increased with the lock down. Youths who are entrepreneurs have also been affected losing jobs and businesses due to the lockdown. Other problems facing youths includes Teenage pregnancies, malnutrition, STI/ HIV and Aids, poor environment, drug and substance abuse and malnutrition 98 Conclusion and Key Recommendations 13.1.8 Education and Training The County with support from stakeholders would continue to invest in early childhood development through infrastructural development to allow for adequate social distancing; deployment of ECDE teachers and provision of sanitation facilities. The county to provide financial or in-kind support, such as school feeding, to help families overcome the increased costs of attending school and provide psychosocial support to teachers and learners during and after the pandemic. 13.1.9 Social Protection It will be important for the County to build linkages with other Ministries, and with NGOs that work with vulnerable groups to strengthen families, deliver assistive devices, reduce barriers to access and provide vocational training. Undertake research to get a better understanding of the actual situation of disability and chronic illness in the County, and to map existing initiatives on social protection. 13.1.10 Human Resource The county will enhance investments and mechanisms for up skilling and reskilling, deepening technical skills as well as ICT skills; and retraining employees on how to work from home, where applicable. The county government will also protect workers in the informal economy by pursuing innovative policies to reach them quickly through a combination of non-contributory and contributory social security schemes and facilitating their transition to the formal economy in the longer term. 13.2 Key Recommendations 13.2.1 Fiscal policy, planning and budgeting To ensure continued recovery, the county must now move quickly to tackle the problem of pending bills, mobilize more finances from OSR to increase the available revenues for budgetary operations, seek for more funding in form of grants from development partners to cater for the critical development projects in the county and ensure that the ongoing projects are completed before launching new project and clear any pending bills and arrears owed to suppliers. 13.2.2 Agriculture, Livestock and Fisheries To successfully build resilience and enhance growth of the agriculture sector, the County will: explore partnerships to develop agro-processing and value addition capacities at the County; expansion of water harvesting projects and sustainable irrigation; scale up conservation agriculture, post-harvest management, plant and keep drought-tolerant crops and livestock breeds; link farmers to diverse product markets; strengthen the County’s institutional capacity in disaster surveillance and management; enhance farmers access to critical agricultural inputs and services and build their technical capacity to act on information obtained; provision of storage and cooling facilities; natural resource management; and strengthen agricultural cooperatives to enhance marketing. 99 Socio-economic status of Garissa County with COVID-19 13.2.3 Water sanitation and hygiene To build resilience and mitigate the effect of COVID-19, the county will; increase water supply in households, institutions, and public places through drilling of boreholes, dams, and access to piped water in all the sub-counties. Promote the use of safe and improved toilets in schools, health care facilities, workplaces, and public places by connecting households to piped sewer. Support households in building low-cost sanitation. Promote handwashing as a measure to contain the spread of COVID-19. 13.2.4 Manufacturing, Trade and MSMEs In sustaining growth in the Manufacturing, Trade and MSMEs sector, the County will: Establish an emergency rescue package for businesses and traders hard-hit by the effects of COVID-19 in the short term. The emergency Fund, supported by development partners and other stakeholders, will be used to identify and support the most vulnerable businesses and entrepreneurs affected by COVID-19. Related, the County will inject some stimulus to cushion the businesses and traders through affordable credit; waiver of some County taxes, cess, and other charges; COVID-19 has increased demand for locally produced goods in the County, and especially Personal Protective Equipment (PPEs), sanitisers, hospital beds and ventilators. It is an opportunity to spur innovation and promote manufacturing and industry development and generation of jobs for the youth; Establishments in the county will adopt to the new pandemic guidelines including rearranging floor plans to allow for social distancing; Leverage and exploit its metropolitan areas status (Wajir-Garissa-Mandera) to enhance manufacturing, which is part of the Vision 2030 aspirations; Mainstream the National Urban Development Policy to spur its industrial development; Establish and equip the Technical, Vocational Education and Training (TVET) as outlined in MTP III; Fast track construction of a new sewerage scheme; Enhance Livestock marketing value addition and processing; Set up, equip, and operationalise a Gypsum Products Manufacturing Plant in Garissa as per MTP III aspirations; Address insecurity to spur the growth of industries in the County; and Fastrack development of County Industrial Development Policy to facilitate investment of industries in the County. 13.2.5 Infrastructure, housing and urban development In addressing the prevailing challenges, the county will Identify a core rural road network for prioritization to improve the rural access index (RAI) from the current 24 per cent with a target to match the national average of 70.0 per cent; Collaborate with the Communications Authority and telecom service providers to utilize the Universal Service Fund as a “last resort” in providing ICT access in remote areas where market forces fail to expand access; and avail appropriate building technology for use by the public in house construction and improvement in every subcounty, that responds to local cultural and environmental circumstances. 13.2.6 Tourism The number of domestic and foreign tourists who visit the tourist sites in the county is not documented. There is need to develop a tourist action plan to enhance exploitation of existing tourism opportunities including desert tourism (camel-back expeditions, camping 100 Conclusion and Key Recommendations and dessert rallying). The county government will map all the sites with tourism potential in the county; come up with a tourism sector development master plan and set up a cultural documentation centre; tourism information centre. 13.2.7 Health For a resilient health sector, there is need for more awareness on immunization so that mothers can ensure their children get immunized. Implement a comprehensive human resource health management system including undertaking training needs assessments and information system to ensure skilled and motivated health care workers, equitable deployed across all sub-counties. This is in addition to paying the salaries in time to avoid cases of strikes and low staff morale. Recruit additional of public health officers and community health workers to strengthen preventive and public health systems. 13.2.8 Education and training The County with support from stakeholders will need to continue to invest in early childhood development through infrastructural development to allow for adequate social distancing when schools reopen; deployment of ECDE teachers and provision of sanitation facilities. The county would put up measures that encourage learners to complete all levels of education. 13.2.9 Social Protection COVID-19 pandemic created immediate and long-term economic consequences for vulnerable groups including children, PWDs, elderly and their families. In an effort to strengthen social protection response in face of a similar pandemic, the county government will need to provide basic income security, especially for persons whose jobs or livelihoods have been disrupted by the pandemic. Build linkages with other Ministries, and with NGOs that work with people with disabilities to strengthen families, deliver assistive devices, reduce barriers to access and provide vocational training. 13.2.10 Human resources The COVID-19 pandemic has expedited the speed at which different firms and businesses within the county are changing their pay programmes through pay reductions and incentive resets. It will be important for the County to promote implementation of a stronger labour market interventions especially those working tea sector which is a major employer in Garissa County and policy reforms that drive employment creation. The County shall deepen technical education, training and skills development. 101 Kenya Institute for Public Policy Research and Analysis Bishops Garden Towers, Bishops Road P.O. Box 56445-00200, Nairobi, Kenya Tel: +254 20 4936000; +254 20 2719933/4 Fax: +254 20 2719951 Email: admin@kippra.or.ke Website: http://www.kippra.org