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Multi-Sector Needs Assessment (Msna)

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Multi-Sector Needs Assessment (Msna) MULTI-SECTOR NEEDS ASSESSMENT MSNA | 2020 Yobe State (MSNA) KEY FINDINGS Nigeria CONTEXT METHODOLOGY North East Nigeria continues to experience This Yobe State factsheet presents composite enumerators then undertook the household significant humanitarian needs after over 11 analysis at the multi-sectoral and sectoral level survey on the phone with the respondents. years of conflict affecting the Lake Chad region. for six key sectors: Food Security & Livelihoods Where there was weak or no phone signal, the The 2020 Humanitarian Needs Overview (FSL), Water, Sanitation and Hygiene (WASH), household surveys were conducted face to face, (HNO) identified 7.9 million individuals in the Health, Shelter and Non-Food Items (SNFI), following strict COVID-19 protocols. three states of Borno, Adamawa and Yobe Education and Protection. This analysis includes (collectively, the “BAY” states) to be in need of the intersection of Living Standards Gaps Five LGAs in Borno State were not assessed humanitarian assistance.1 (LSGs), Capacity Gaps (CGs) and vulnerability. due to security concerns and are considered inaccessible to most humanitarian actors. To respond to persisting information gaps on Data collection took place between the 13th For the remaining 45 LGAs in the BAY states, humanitarian needs severity and to inform July and 21st August, with a total of 6,888 household surveys were conducted remotely response planning, United Nations Office for household surveys being conducted across the by phone with snowball sampling from contacts Coordination of Humanitarian Affairs (OCHA)’s BAY states. provided by past MSNA key informants. Inter-Sector Working Group (ISWG), with support from REACH, conducted a Multi-Sector OCHA identified 15 priority Local Government The findings presented in this factsheet are state- Needs Assessment (MSNA) in the BAY States. Areas (LGAs) where the need to address level aggregations that combine indicative and The MSNA aimed to identify and compare needs information gaps was highest. In these LGAs, representative data, meaning that all findings by sector and across sectors, across population two-stage cluster sampling was used in the presented in this factsheet are indicative only. groups affected by the protracted crisis and in physically accessible areas. The data at all accessible areas in the BAY states. the overall LGA level in these LGAs have a All relevant sectors contributed to the sector- confidence level of 95% and a margin of error specific indicators and the LSG methodology. The 2020 assessment methodology was of 10% or less for questions that were asked to LSGs are an analytical construct signifying adapted to the current COVID-19 health all households. unmet needs in any given sector, based on a emergency. A mixed methodology was adopted, severity score. The highest of these severity to avoid in-person data collection. In coordination with multiple implementation scores is taken as the Multi-Sectoral Needs partners, two data collection methods were Index (MSNI) score for the household. used in these priority LGAs. In places with stronger phone network, partner staff on the Please find a more detailed methodology section ground identified respondents using GPS and in Annex 1 of this factsheet. dialled into the REACH call centres. REACH Assessment sample Coverage map Households: 1,098 Yusufari - Non-Displaced: 437 Machina Yunusari Karasuwa Nguru !!(!(!(!( !(!(!(!( - IDP: 393 (!(!!( Bade Bursari - Returnee: 268 Geidam Bade LGAs 17 (out of 17) Jakusko Tarmua Demographics Nangere Fune Damaturu Potiskum Female (48%)1+19+17+11 Age Male2+17+21+12 (52%) 1% 60+ 2% Fika Gujba 19% 18-59 17% 17% 6-17 21% Gulani 11% 0-5 12% Single female-headed Average households: household size: (! Assessed with two-stage cluster sampling (representative findings) 10% 8.5 Unassessed areas in partially-accessible LGAs Assessed with purposive snowball sampling (indicative findings) State boundary Km LGA boundary 1 OCHA. Nigeria: 2020 Humanitarian Needs Overview. April 2020 0 50 100 1 MSNA | 2020 MULTI-SECTORAL NEEDS Yobe State Nigeria % of households with # of households with multi- multi-sectoral needs:1 86% sectoral needs:2 393,283 see Annex for details on methodology Multi-sectoral % of households per Multi-Sectoral Needs Index (MSNI) severity score: 2% Extreme + (severity score 4+) needs 50% Extreme (severity score 4) 35% Severe (severity score 3) 00+140+350+500+20 14% Stress (severity score 2) 0% No or minimal (severity score 1) % of households with multi-sectoral needs, per % of households per MSNI severity score, per population population group: group: 83+96+90+ 1 2 3 4 4+ Non-Displaced 83% IDP 96% Non-Displaced 0% 17% 38% 43% 1% Returnee 90% IDP 0% 4% 28% 65% 3% Returnee 0% 10% 17% 73% 1% % of households with severe or extreme needs (MSNI % of households with extreme needs (MSNI severity severity score of at least 3), per LGA: score of 4 and 4+), per LGA: Yusufari Yusufari 100% 55% Yunusari Yunusari Machina Machina 84% 56% 88% 59% Nguru Nguru Karasuwa Karasuwa 68% 91% 47% 67% Bade Bade 97% 47% Bursari Bursari 88% Geidam 62% Geidam 89% 50% Jakusko Jakusko 87% 67% Tarmua Tarmua 71% 58% Nangere Damaturu Nangere Fune Fune Damaturu 90% 95% 55% 98% 21% 32% Potiskum Potiskum 81% 54% LGA settlements where two-stage LGA settlements where two-stage cluster sampling took place cluster sampling took place % of households with severe or extreme Fika Gujba % of households with extreme needs (MSNI Fika Gujba needs (MSNI severity score of at least 3), 48% 96% severity score of 4 and 4+), per LGA 36% 88% per LGA High High Gulani Gulani 80% 35% Low Low ² ² Kms Kms 0 30 60 120 0 30 60 120 1 Multi-sectoral needs: proportion of households with an MSNI severity score of at least 3, based on the severity of LSGs identified in each household. 2 Figure obtained by applying the percentage on population figures from the Vaccination Tracking System (VTS) Dataset, March 2020 and International Organisation for Migration (IOM) Displacement Tracking Matrix (DTM) Round 31, February 2020 2 MSNA | 2020 MULTI-SECTORAL NEEDS Yobe State Nigeria % of households per number of sectoral LSG(s)1, per % of households with sectoral LSG(s), per population population group: group: 0 1 2 3 4 5 6 Non-Displaced 17% 28% 30% 19% 3% 2% 0% IDP 4% 21% 36% 23% 13% 3% 0% Non-Displaced Returnee 10% 30% 37% 15% 5% 0% 2% IDP 12% of households were found to have multi-sectoral Returnee needs and to be vulnerable.2 Most common distinct LSG profiles among households with multi-sectoral needs (made up of one or more LSGs). 8 The figure on the left shows the most common needs profiles, 7 7 to identify the most common “distinct combinations” of one or more LSGs amongst those in need. Each household has only one needs profile so the percentages cannot add up to more than 100%. 6 The figure below shows the proportion of households in need by type of LSGs, to identify the most commonly occuring LSGs amongst those in need. Each household can have needs in several sectors so the percentages can add up to more than 100%. 4 The tables below show these distinct needs profiles per 3 3 population group, and the intersections of sectoral needs, or the most common “pairs” of LSGs. 2 2 2 2 2 2 2 2 2 Among households with multi-sectoral needs, % of % in need per combination of sectors households with sectoral LSG(s): 41+43+38+30+29+54 Education 41% 0 Protection FSL 43% Shelter Health 38% Health Protection 30% Education FSL Shelter 29% WASH WASH 54% Most common distinct needs profiles (made up of one or more LSGs) among households with multi-sectoral needs, per population group: Non-Displaced IDP Returnee 1. WASH and Education 7% 1. WASH and Food Security 9% 1. WASH and Food Security 17% 2. WASH and Food Security 6% 2. WASH, Food Security and Shelter 8% 2. WASH and Education 10% 3. WASH and Health 3% 3. WASH and Education 7% 3. WASH and Health 5% Most common intersections of LSGs (made up of two LSGs), among households with multi-sectoral needs, per population group: Non-Displaced IDP Returnee 1. WASH and Education 18% 1. WASH and Food Security 34% 1. WASH and Food Security 30% 2. WASH and Food Security 16% 2. WASH and Shelter 27% 2. WASH and Education 24% 3. WASH and Health 14% 3. Food Security and Shelter 20% 3. WASH and Health 16% 1 Living Standard Gap (LSG): signifies an unmet need in a given sector, where the LSG severity score is 3 or higher. 2 See p.11 on pre-existing vulnerabilities for more information. The proportions of vulnerable households with multi-sectoral needs per population group were found to be: 11% non-displaced; 15% IDP; 14% returnee. 3 FOOD SECURITY & LIVELIHOODS (FSL) MSNA | 2020 Yobe State 1 LIVING STANDARDS GAP (LSG) Nigeria % of households with a # of households with a FSL LSG: 34% FSL LSG:2 193,276 see Annex for details on methodology % of households per FSL LSG severity score: 0% Extreme + (severity score 4+) LSG 0% Extreme (severity score 4) 33% Severe (severity score 3) 380+280+330+00+00 28% Stress (severity score 2) 38% No or minimal (severity score 1) % of households with a FSL LSG, per population % of households per FSL LSG severity score, per group: 30+45+37 population group: Non-Displaced 30% 1 2 3 4 4+ IDP 45% Non-Displaced 45% 25% 29% 0% 0% Returnee 37% IDP 22% 33% 45% 0% 0% The three main drivers of FSL LSGs were found to be: Returnee 26% 37% 36% 0% 0% - Household Hunger Scale of 2 or higher3 (27%) - Used less preferred fuel source when insufficient fuel4 (11%) 7% of households were found to have a FSL LSG and to - No sufficient access to fuel and/or not using improved fuel be vulnerable.5 source (3%) % of households with a FSL LSG, per LGA: Yusufari ² 66% Machina Yunusari 54% Nguru Karasuwa 48% 32% 8% Bade 31% Bursari 32% Geidam 25% Jakusko 13% Tarmua 23% Nangere LGA settlements where two-stage 19% cluster sampling took place Fune Damaturu 70% 33% Potiskum % of households with an FSL 23% LSG High Fika 4% Gujba 50% Low Gulani 34% Kms 0 45 90 180 1 Composite score made up of sufficient access to firewood/fuel in surrounding environment, most commonly used fuel type for cooking, coping strategies used for insufficient fuel, and household hunger scale.
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