WAJIR EAST SUB COUNTY, KENYA. 20 th September to 3 rd October 2013 Caroline Njeri KIMERE Inés ZUZA SANTACILIA

WAJIR EAST SUB COUNTY, KENYA 20 th September to 3 rd October 2013 Caroline Njeri KIMERE Inés ZUZA SANTACILIA

ACKNOWLEDGEMENTS Save the Children International (SCI) and Coverage Monitoring Network extends its deep gratitude to all those who have contributed to this study including: the authorities in Wajir East Sub County, North Eastern Region in Kenya and to all the health personnel and village residents for your hospitality and cooperation. Very special thanks to the mothers and caregivers of severe acute malnourished children who willingly participated in the study and provided the information needed. Thanks to the SCI team in Wajir East, the North Eastern Province and Nairobi. To the Nutrition M&E Specialist (Caroline Njeri KIMERE) for her support coordinating the SQUEAC at field level; to the Health and Nutrition PM (Rahab KIMANI) and to the Nutrition Specialist (Irene SOI) for their collaboration and support. Thanks to the Nutrition Coordinator in Wajir East (Adan ABDILLE) for his support. And thanks to all SCI staff involved in the SQEUAC investigation for their collaboration. I thank as well Ministry of Health (MoH) for their support and commitment especially the County Nutrition Coordinator (Nuria Ibrahim ABDI). And the Mandera Central Sub County Nutrition Officer (Patrick M KAMUNDI) I wish to thank Islamic Relief Kenya for their participation and collaboration in the SQUEAC. This study would not have been possible without the hard work and commitment of everyone involved. Lastly, thank you to the Humanitarian Aid and Civil Protection Department of the European Commission and the Department for International Development (DFID) for financing this project. 2

EXECUTIVE SUMMARY Wajir East sub county is one of the 4 sub counties in the larger Wajir County in the North Eastern Region of Kenya. The current estimated population living in this area is 226,086 1 Save the Children International (SCI) has been running a programme to contribute to the reduction of morbidity and mortality related to acute malnutrition and to improve nutrition practices in Wajir east Sub County since 2009 to date responding to the emergency nutrition needs. Under this arrangement there are 37 OTP sites in the Sub County based at both the health facilities and outreach sites (areas without a health facility) and one stabilization center integrated in the pediatric ward at the Wajir Sub County Hospital. Additionally SCI supports the Ministry of Health in providing monthly incentives and capacity building for 99 community health workers (CHWs). Regarding the nutritional situation, the Global Acute Malnutrition and Severe Acute Malnutrition rates for Wajir East were 10.5 % (7.9-13.9 95% C.I.) and of 1.6% (0.8-3.1 95% C.I.) respectively as reported in a SMART nutrition survey conducted in May 2013. The coverage assessment was conducted to evaluate access and coverage of the Community based Management of Acute Malnutrition programme for children ages 6 to 59 months with SAM. It conducted between September 18th and 4 th October 2013 and it was the fourth Coverage survey to be conducted in Wajir East. It was conducted at the end of the Haggai dry season. Year 2006 (March) 2010 (March) 2011 (March) 2011 (December) Assessment SCAS SQUEAC SQUEAC SQUEAC Coverage results Point: 30,0% (95% IC: 17.8-42.2) Point: 63.7% (95% IC: 46.6-78.5) Point: 62.7% (95% IC: 49.0-75.5) Point 1) Central division 48.3% (95% IC: 33.5-63.5) 2) Other divisions : 67.6% (95% IC: 55.1-78.0) The Semi Quantitative Evaluation of Access and Coverage (SQUEAC) methodology was used,. The coverage investigation conducted in Wajir East Sub County: point coverage is 54.6% (95% IC: 40.6% - 67.6%). It is above the SPHERE standards for a rural area (>50%). But there are no significant changes since 2010 in terms of coverage. The table below presents the main barriers on which the programme must act to improve coverage as well as specific recommendations how to do so: 1 Current estimates from the District Data Officer- Wajir town Based on 2009 Census 3

Barriers Migration/ Nomadism( animals looking for water and pasture) Competing priorities disrupting OTP Services (Campaigns, trainings, meetings) Shortage and staff turnover at OTP sites Distance to health facilities/ OTP site Late seeking behavior (Sheikh, food) Boosters Good inter-linkage between community and health facilities (by CHWs follow up) Awareness of OTP and MUAC by caretakers and the community Good mobilization (Acceptance of program) Good integration at health facilities in services provided (Allows SAM Screening) Referrals from CHWs Collaboration and referral from TBA Recommendations 1 Increase access of nomadic population to the programme 2 Strengthen Joint planning with MOH and other partners 3 Advocacy on human resources importance 4 Increase community mobilization / sensitization 5 Increase quality of the OTP follow up 4

CONTENTS 1. INTRODUCTION... 7 1.1 CONTEXT... 7 1.2 Results of previous SQUEACs in Wajir East.... 11 2. OBJECTIVES... 13 3. METHODOLOGY... 14 3.1. GENERAL OVERVIEW... 14 3.2. STAGES... 15 Stage 1: Identification of potential areas of high and low coverage and access barriers... 15 Stage 2: Confirms the location of areas of high and low coverage... 17 Stage 3: Wide area survey conducted to estimate overall coverage.... 18 3.3. ORGANIZATION OF THE EVALUATION... 20 3.3.1 CMN technical support... 20 3.3.2 Team training, logistic organization and evaluation development... 21 3.4. LIMITATIONS... 21 4. RESULTS... 22 4.1. STAGE 1... 22 4.1.1. Recommendations follow up of SQUEAC December 2011... 22 4.1.2. Quantitative data analysis... 24 4.1.3. Qualitative data analysis... 31 4.2. STAGE 2... 33 2 The prior... 35 3 The likelihood... 36 4 The posterior... 37 5. DISCUSION... 39 6. RECOMMENDATIONS... 41 Annex 1 : Survey questionnaire for current SAM children NOT in the program... 45 Annex 2: Wajir East SQUEAC plan, September October 2013... 46 Annex 3 : SQUEAC Survey team... 47 Annex 4 : Terminology in Somali (S) and Borana (B) used to describe malnutrition and RUTF.... 48 Annex 5: Weighted BBQ, Wajir East SQUEAC, September-October 2013... 49 5

ABBREVIATIONS ARI ASALS BBQ CI CMAM CMN ECHO FGD FP GAM HC HF IMAM INGO IRK LoS MAM MEAL MoH MUAC OCHA OS OTP PLW RUTF SAM SC SCI SFP SQUEAC TBA UNDP UNICEF WFP WHO Acute Respiratory Infections Arid &. Semi-Arid Lands Barriers, Boosters and Questions Credible Interval Community Management of Acute malnutrition Coverage Monitoring Network European Commission - Humanitarian Aid & Civil Protection Focus Group Discussion Family Planning Global Acute Malnutrition Health Centers Health Facility Integrated Management of Acute Malnutrition International Non-Governmental Organisation Islamic Relief Kenya Length of Stay Moderate Acute Malnutrition Monitoring, Evaluation, Accountability and Learning Ministry of Health Mid-Upper Arm Circumference Office for the Coordination of Humanitarian Affairs Outreach Site Outpatient Therapeutic Programme Pregnant and lactating women Ready to Use Therapeutic Food Severe Acute Malnutrition Stabilization Centre Save the Children International Supplementary Feeding Program Semi Quantitative Evaluation of Access and Coverage Traditional Birth Attendants United Nation Development Programme United Nations Children s Fund World Food Program World Health Organisation 6

1. INTRODUCTION 1.1 CONTEXT 4.1.1. Overview of the area Wajir East sub County is one of the 4 sub-counties within the larger Wajir County; Wajir County is part of former North Eastern Province of Kenya (Figure 1). The Sub County currently comprises of 6 divisions namely Wajir Bor, Tarbaj, Kutulo, Central, Mansa and Khorof harar. It measures approximately 14,471 km², is classified as arid and is characterized by long dry spells and short rainy seasons. Figure 1: Kenya and Wajir county map 2 Wajir town is the Sub County headquarters and is the largest urban town in Wajir County. The population is predominantly Muslim and of Somali ethnicity, and is divided into clans, with community elders being in charge of daily affairs. Fai is the predominant clan and other clans include Masare, Garre, Degodia, Murule, Ogaden and Ajuran. The survey area covered all six divisions of the Sub County. The current estimated population living in this area is 226,086 3 1.1. Geography, current climatic conditions and food security Wajir East Sub County is a featureless plain, which is prone to flooding during the rainy season. The Sub County has some seasonal swamps and perennial river beds/drainage lines ( laghas ) that flow in the rainy season. These serve as dry season grazing zones and also allow some cultivation when it 2 Available at URL: http://en.wikipedia.org/ [visited December 2013] 3 Current estimates from the District Data Officer- Wajir town Based on 2009 Census 7

rains. The area receives bimodal rains with the onset of the long rains in April. The months succeeding the long rains, June to September, are very dry but vegetation continues to thrive because the lower temperatures reduce the rate of evaporation. However the rains have become increasingly unpredictable and erratic. Persistent incidences of drought and their increasing unpredictability in the region in recent years have continued to threaten the livelihoods of many pastoralists subjecting them to food insecurity (due to the short recovery phase between droughts), high malnutrition rates (above the emergency thresholds of 15%) and increased disease burden. In 2011, the Sub County, including the rest of the Arid &. Semi-Arid Lands (ASALS) suffered severe drought conditions, which further eroded the already diminishing livelihoods causing critical food insecurity, lack of water and high malnutrition rates. From October 2011 to date however, the sub-county has been receiving near average rainfall during all the rainy seasons (both short and long) leading to an improvement of the Global acute malnutrition (GAM) levels reducing from above the emergency thresholds to 10.5% in May 2013. 1.2. Livelihoods Wajir East Sub County 70% of the population solely depends on livestock for their livelihood. The main form of land use is nomadic pastoralism which is seen as the most efficient method of exploiting the rangelands hence pastoral activities are practiced all over the Sub County. Most of the area covers the Pastoral Camel Zone (Eastern Bush land) where predominantly camel herding occurs. Small pockets of agro-pastoral activity are found in Tarbaj and Wajir Bor divisions. The crops cultivated include maize, sorghum, beans, cowpeas (kunde) 4, tomatoes, sweet pepper and pawpaw. In addition, small-scale irrigated horticulture is emerging in peri-urban areas (kitchen gardens) with crops such as watermelon, pawpaw, lemons and vegetables thriving 5. 4.1.2. Nutritional situation Regarding the nutritional situation, Save the Children (SCI) has been conducting nutritional SMART surveys 6 in Wajir East Sub-County since 2009 to date. Figure 2 below shows the results of these nutritional surveys. GAM rates had surpassed the WHO alert threshold for a state of emergency (>15%) until 2012 but in 2013 the levels seems to be dropping. 4 Sub County Steering Group Combined Report for Wajir North, East, West and South Sub Countys-Rapid Assessment and Sectoral Report on the Impact of the Short Rains in the Sub County- January 2009 5 Ministry of Agriculture- Wajir East Food and Crop Situation Report-April 2009 6 2006 WHO standards 8

Figure 2: Results of nutrition surveys in Wajir East Sub-County, KENYA. 2009-2013. In Country, malnutrition rates have been chronically at emergency levels. These high rates of malnutrition can be attributed to poor health conditions, sub-optimal maternal and child feeding, care practices, and food insecurity. This has been compounded by high rates of poverty and illiteracy, marginalization, recurrent environmental shocks (floods and droughts) and displaced populations adding an additional strain to already weak health systems and communities 7. 4.1.3. Health access in Wajir East Sub County Services are delivered both at the sixteen outreach sites, which are closer to community level and deliver primary health care unity and at all the twenty one Health Centers (HC), which are located within the Sub County. There is also one stabilization center in Sub County hospital in Wajir Town. Ministry of Health (MOH) with support from SCI supports Community Health Workers (CHWs) through provision of monthly incentives and training. CHWs are team of community-level volunteers engaged in screening and mobilizing children under 5 and pregnant and lactating women. They detect cases of some diseases (including malnutrition and diarrhea) and refer them to the health facilities. The community has chosen them with the participation of the MoH and save the children following the laid down MOH standards. They are equipped with a CHW kit and manage fever and mild diarrhoea and the community level while conducting screening and referral for malnutrition cases. The cases then are referred to either outreach sites or health facilities where they are managed by nurses. 7 SMART survey report 2013, Kenya Demographic Health Survey 2008 9

4.1.4. Nutrition services and SCI support in Wajir East Sub County Since July 2009 SCI has been in operation in the Sub County offering Integrate Management of Acute Malnutrition (IMAM) services. This was done through direct implementation with SCI providing services parallel to the government. Before, from 2004 to 2008 it was Merlin who providing this support. This however was changed in August 2012 where a new implementation strategy was agreed upon by the entire nutrition sector under the leadership of the division of nutrition from the MOH. The strategy was to provide a package of services shown to have the greatest impact on malnutrition and strengthen the system to provide them (so that partners did not provide services but supported the MOH to provide the services). In Wajir East Sub County there are 37 Outpatient Therapeutic Programmes (OTP) for the treatment of SAM cases (21 HF based and 16 in outreach sites). And one Stabilization Center (SC) based in Wajir East Hospital for the SAM cases with complications. Figure 3: Temporally line of the nutrition support in Wajir East Sub-County and the coverage assessments, KENYA. 2004-2013. In this light, through ECHO/DFID funded grants, SCI supports the MOH logistically, with human resources, and technically in HINI implementation in the Sub County. Through this support these services are being provided in the 21 health facilities,16 outreach sites across the Sub County and SC. In logistics, it involves transferring of health and nutrition supplies either from SC or from the main Wajir Sub County hospital to the rest of 21 health facilities within Sub County. 5 nurses have also been seconded to MOH and distributed in various health facilities in the district. Besides that a monthly incentive of Ksh 3000 is provided to the 99 CHWs in the Sub-County. Capacity building has been provided to the health workers through classroom training and monthly OJT to all the implementing staff pertaining to HINI activities and weekly site supervision/monitoring to enhance programme quality and adherence to programme protocol. The MOH has a guideline for management of Acute malnutrition written in June 2009 but it is currently under review. From the guideline, the admission criteria for OTP is MUAC <115mm (with length >65cm), and/or WHZ <3 Z score and/or bilateral pitting edema following the WHO guidelines for 2006. Both at Health Facilities and outreach sites, the activities are implemented by nurse or health officer supported by community health workers. 10

UNICEF provides the Ready to Use Therapeutic Food (RUTF) and anthropometric tools. Medicines for SAM treatment are provided through the Kenya Medical Services together with the other routine drugs. For Moderate Acute Malnutrition Management (MAM), MOH manages the cases with World Food Programme (WFP) providing the rations needed through the Supplementary Feeding Programme (SFP). 1.2 Results of previous SQUEACs in Wajir East. In order to assess and improve programme performance in terms of access and coverage, four coverage assessments have been carried out. Using the Centric Systematic Area Sampling (CSAS) in 2006 and the Semi-quantitative evaluation of access and coverage (SQUEAC) methodology in 2010, March and December 2011. Table 1 show a summary of the main results of these coverage assessments. 11

Table 1: Results of coverage assessments, 2006-2012, Wajir East Sub County, North Eastern Province in Kenya*. Year 2006 (March) 2010 (March) 2011 (March) 2011 (December) Assessment SCAS SQUEAC SQUEAC SQUEAC Zone / OTP sites Wajir East Sub County Wajir East Sub County Wajir East Sub County Wajir East Sub County 22 OS and supporting the MoH in 20 HF MUAC admission < 110 mm < 115 mm < 115 mm < 115 mm Coverage results 8 Point: 30,0% (95% IC: 17.8-42.2) Point: 63.7% (95% IC: 46.6-78.5) Point: 62.7% (95% IC: 49.0-75.5) Point 1) Central division 48.3% (95% IC: 33.5-63.5) 2) Other divisions : 67.6% (95% IC: 55.1-78.0) Main barriers - Problems of rejected referrals and case definition - Relapsed cases (in SFP with MUAC <100mm) - Distance of OTP locations - Awareness of malnutrition - Monitoring of movements of the targeted group - Mobilization *Recommendations of the SQUEAC from December 2011 are available in the results part. - Lack of access to programme sites - Migration - Challenges associated with MoH managing malnutrition - Minimal inclusion of key field sources of referral - Stigma - Lack of CSB - Previous rejection - Apathy in childcare - Distance for a proportion of the community - Insecurity - Staffing 8 Period coverage: CSAS 2006: 49.1% (95% IC: 33.6-64.6), SQUEAC 2010 80.6% (95% IC: 70.0-88.9), March 2011 82.3% (95% IC: 74.1-88.8), Dec 2012 Central 67.6% (95% IC: 55.1-78.0), other 83.7% (95% IC: 74.0-90.3),

2. OBJECTIVES Main objective The main objective of this assessment was to evaluate access and coverage of the Integrated Management of Acute Malnutrition (IMAM) for children ages 6 to 59 months with SAM in Wajir East Sub County, North Eastern Province in Kenya, using the Semiquantitative evaluation of access and coverage (SQUEAC) methodology. Specific objectives - To develop capacity of various stakeholders on undertaking programme coverage assessments using SQUEAC methodology - To determine baseline coverage for IMAM - To identify boosters and barriers influencing IMAM programme access and coverage - To develop feasible recommendations to improve IMAM programme access and coverage Photo 1 : SQUEAC Investigation team in Wajir East Sub County, North Eastern Province in Kenya. September 2013

3. METHODOLOGY 9 3.1. GENERAL OVERVIEW The Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) is a coverage assessment method developed by Valid International, FHI 360/FANTA, UNICEF, Concern Worldwide, World Vision International, Action Against Hunger, Tufts University, and Brixton Health. The methodology is semi-qualitative in nature, meaning that it draws from a mixture of both quantitative data from routine programme monitoring activities as well as qualitative data collected on the field. This mixed methods approach combines data sources to estimate programme coverage and to develop practical measures that can improve access and coverage. - Quantitative data came mainly from routine monitoring information that the programme already collected including: admissions, defaulting, recovery, middle upper arm circumference (MUAC). Routine programme data was coupled with complementary data like agriculture, labor, and disease calendars, anthropometric nutritional surveys, and agricultural and food security assessments. - Qualitative data collected came from interviews, focus groups and questionnaires with various key informants. Together, the data were triangulated by source and method to formulate hypotheses about coverage and access. Data triangulation is a powerful technique that helped validate our findings through cross verification. Hypotheses were then tested with small-area surveys and small sample surveys. Then, a wide area survey was conducted in the community to determine the point coverage estimate. Lastly, the results from the quantitative and qualitative analyses and the wide-area likelihood survey were combined and the overall global coverage estimate was calculated using Bayesian statistical techniques. 9 2012. SQUEAC and SLEAC Technical Reference. FANTA. Available at http://www.fantaproject.org/sites/default/files/resources/squeac-sleac-technical-reference- Oct2012_0.pdf 14

The coverage assessment was fourth coverage study in the area. It was conducted between the 20th September to the 3rd October 2013. It was carried out at the end of the dry season and when food availability was apparently good. The SQUEAC methodology used consisted of 3 stages, applying the principles of triangulation (by source and method) and sampling to redundancy. 3.2. STAGES Stage 1: Identification of potential areas of high and low coverage and access barriers Identification of potential areas of high and low coverage using routine programme data; in this stage, triangulation of data is going to be done by various sources and methods as highlighted below. 1. Recommendations follow up of SQUEAC December 2011 Analysis of recommendations from the SQUEAC of December 2011 follows up. The evolution of the factors influencing coverage positively and negatively has been studied. 2. Quantitative data Quantitative, routine programme data helped to evaluate the general quality of IMAM service, to identify admission and performance trends and to determine if the programme adequately responds to need. It also helped point out problems in screening and admission. Lastly, routine programme data analysis provided the first insights into variation in programme performance between OTPs. Route programme data analysis (January 2012 June 2013) 37 OTP: 16 OS + 21 HF - Global (OTP and SC) trends of admission and defaulters over time and compared to the agricultural calendar, the lean period, child epidemics and diseases, workload, weather patterns and key events - Admission: admission by OTP and SC - OTP and SC programme performance indicators over time (recovery, default, death, non-response). - Stock break out data. Complementary from children card (June August 2013) for 33 from 37 OTP 10 : 14 OS + 19 HF - MUAC at the time of admission 10 Krof Harar HF OTP, Halane OS OTP, Dambas HF OTP and Orgaralle OS OTP. 15

- Discharged o Cured: length of stay (LoS) and MUAC at discharge. o Defaulters: length of stay (LoS) and MUAC at discharge. - OTP admissions by category (MUAC, W/H and Oedema) - The village lists populations belonging to each OTP and distance walking to OTP. Admissions per village Not available - Admissions and defaulters per village - Source of referral to the OTP 3. Qualitative data Qualitative data was collected to investigate programme operations, to unravel the opinions and experiences of actors involved in IMAM and to identify any potential barriers to access. The following methods were used: focus groups, semi-structured interviews, structured interviews, case studies, observation and information from previous coverage assessments. Interviews and focus groups were conducted with key informants either directly or indirectly involved in the IMAM program. These included: women s and men s community, SCI programme staff, local authorities, OTP/SC nurses, CHW, caregivers of SAM children, Informal caregivers (traditional healers and traditional birth attendants), partners (WFP, Aldef, and UNICEF) and mother to mother support group and county HDA. Finally we couldn t meet county or sub county health authorities. The BBQ framework. Throughout the investigation, the data are going to be organized, analyzed and triangulated using the Barriers, Boosters and Questions (BBQ 11 ) framework. It is a tool that facilitates iterative data collection that is then categorized into one of three categories. The various data organized within the BBQ framework, when combined, will help providing information about where coverage is likely to be satisfactory as well as where it is likely to be unsatisfactory. Additionally, the BBQ provided information about likely barriers to services access that exists within the IMAM program. 11 Barriers are negative findings that deter from programme coverage and complicate access to service. Conversely, boosters contribute to a higher coverage and facilitate access. Lastly, questions, are those findings elements to be further investigated, and either become a barrier or booster or remain inconclusive 16

Stage 2: Confirms the location of areas of high and low coverage The goal of stage 2 is to test the hypotheses about coverage and access elaborated in stage 1. These hypotheses usually take the form of identifying areas where the combined data suggest that coverage is likely to be either high or low. The small-area surveys method was used to test the hypotheses for IMAM high and low coverage areas. The active and adaptive case-finding methodology was used to find SAM cases. Data surveys will be analysed using simplified lot quality assurance sampling (LQAS). The LQAS classification technique analyses data using the following formula: where If the number of covered cases found (that is, those cases in the program) is greater than then then the coverage of the surveyed area is classified as being greater than or equal to the coverage standard. If the number of covered cases found (that is, those cases in the program) is less than then then the coverage of the surveyed area is classified as being less than or equal to the coverage standard The threshold chosen was 58.0%. The middle point coverage SQUEAC (from central and other divisions) results in Wajir East in December 2011 was the guide to establish this threshold. If the number of covered cases found (that is, those cases in the program) is less than then then the coverage of the surveyed area is classified as being less than or equal to the coverage standard 17

Stage 3: Wide area survey conducted to estimate overall coverage. The goal of stage three is to calculate the overall coverage estimate. This is done using a Bayesian statistical technique called beta-binomial conjugate analysis. Conjugate analysis begins with a beta distributed, probability density called the prior. The prior is then combined with a binomial distributed, likelihood function called the likelihood. The likelihood is going to be determined by a wide-area coverage survey that will be conducted across the entire programme catchment area; the mode of the likelihood was, in fact, the point coverage estimate from the survey. Because the prior and the likelihood are mathematically expressed in similar ways (as probability distributions) they can be combined through conjugate analysis, the result of which is the posterior probability density the posterior. The mode of the posterior is the final coverage estimate. 1. The Prior The prior was constructed by combining the results from stages 1 and 2, that is: routine programme data, qualitative data and all relevant findings from the small-area and small sample surveys. The prior was the result of combining four modes: 1) The Simple BBQ : The simple BBQ is the first and simplest approach to calculating the prior. A uniform score of 5 points was attributed to each element (either a barrier or booster). The total booster and total barrier scores were summed. The total booster score was then added to the minimum possible coverage (0%) and the total barrier score was subtracted from the maximal possible coverage (100%). The coverage estimate was calculated by taking the mean of these two percentages. 2) The weighted BBQ : a score from 1 to 5 was attributed to each element. The score reflected the relative importance or likely effect that the element had on coverage. The coverage estimate was calculated by the method explained above. 3) The concept map : is a graphical analysis technique that was used to organize the data. The final product, the concept-map, is a diagram that visualizes relationships between findings. It was elaborated within a context frame, which is defined by an explicit focus topic. Links were drawn between each concept, representing the relationship between them. The various relationships types traced included: results in, leads to, encourages, helps create, allows, etc. Two concept maps were created, for barriers and boosters. For each map, the total number of linkages was counted. Like before the booster linkage sum was added to the minimum possible coverage value (0%) while the barrier linkage sum was subtracted from to the maximum possible coverage value (100%). The coverage estimate was calculated by taking the mean of these two percentages. 4) The histogram prior : During a participatory working group, the investigation team designed a histogram representing the prior mode. This was done realistically and democratically. The mode, minimum and maximum coverage values were chosen credibly.

2. The likelihood A wide-area likelihood survey was conducted over the entire programme catchment area to calculate the coverage estimate. The active and adaptive case-finding methodology was used to identify the SAM cases. The case definition used for coverage survey was defined as a child matching the admission criteria of the programme. The admission criteria of the Kenyan IMAM programme included children age between 6 and 59 months with at least one of the following criteria: 1) a MUAC of <115 mm and/or 2) W/H < - 3 Z-scores and / or 3) bilateral pitting oedema A simple structured interview questionnaire was used to caregivers of non-covered cases for SAM Annex 1. The sample size required was calculated by using the following equation: 1. Mode: prior value expressed as a proportion. 2. α et β: shape parameters of the prior. 3. Precision : desired precision. In the present case the precision used was 0.135 (13.5%). 4. SAM prevalence: 0.2% was chosen after stage 2 results. Initially the rates considered were 0.7%, the prevalence in the last SMART survey in May 2013 (for MUAC admission criteria) in Wajir East Sub County. But the prevalence was found inferior to these data and this was revised downwards following the results from stage 2. 5. Average village population: 2,759 population in Wajir East (based on Sub County health office data which is projected fom the 1999 census since the 2009 data was refuted) 6. Population between 6 and 59 months : approximately 20.0% And the sample size will was into the minimum number of villages needing to be sampled to achieve the sample size using the following equation: X The number of village required was randomly selected with ENA for SMART software 12. 12 Available at: http://www.nutrisurvey.de/ena/ena.html [Visited October 2013] 19

3. Overall Coverage Estimate The point or period coverage estimate was chosen for SAM coverage. By method of Bayesian betabinomial conjugate analysis the prior probability density was combined with the coverage estimate from the likelihood survey to calculate the mode of posterior probability density. The Posterior Probability is the estimate of the overall coverage: it represents the synthesis of the prior probability and likelihood generated by the calculator with Bayes credible interval (CI) of 95%. Recommendations and Action Plan: A final important step is the development of an action plan that clearly identifies the actions to be undertaken, indicators, evaluation methods and deadlines. 3.3. ORGANIZATION OF THE EVALUATION 3.3.1 CMN technical support The SCI team, the Kenyan MoH (from Wajir and Mandera province) and Islamic Relief Kenya received the technical support of the Coverage Monitoring Network (CMN). The CMN Project is a joint initiative by ACF, Save the Children, International Comitee, Concern Worldwide, Helen Keller International and Valid International. The programme is funded by ECHO and USAID. This project aims to increase and improve coverage monitoring of the Community Management of Acute malnutrition (CMAM) programme globally and build capacities of national and international nutrition professionals; in particular across the West, Central, East & Southern African countries where the CMAM approach is used to treat acute malnutrition. It also aims to identify, analyse and share lessons learned to improve the IMAM policy and practice across the areas with a high prevalence of acute malnutrition. The technical and methodological support was provided by a Regional Coverage Advisor (RECO) Inés ZUZA SANTACILIA. During the evaluation CMN support was conducted in three phases: - 1st phase: remote technical support for the planning and preparation of the evaluation with the CMN RECO. - 2nd phase: in field technical support in Wajir East Sub County. The CMN RECO was deployed to support training on the use of the SQUEAC methodology and the implementation of the evaluation until Stage 1. - 3rd phase: remote support for the completion of the investigation, analysis of results and report writing. The SQUEAC plan is in Annex 2. 20

3.3.2 Team training, logistic organization and evaluation development The investigation team (described in Annex 3) was composed of members of SCI from Wajir, Mandera and Nairobi, MoH staff (from Wajir and Mandera County) and cone partner (IRK). The SQUEAC was conducted in the field by the CMN RECO in collaboration with the SCI Nutrition M&E Specialist (Caroline Njeri KIMERE). A two days training in the SQUEAC methodology was made by the CMN RECO in Wajir town. This training targeted people that integrated the evaluation team and other people who might be interested in the methodology. The RECO couldn t travel to the field because of the security situation (it would have required army protection). For the three steps the investigation team was divided in three teams, composed by normally three people each. 3.4. LIMITATIONS The evaluation was limited by the following elements: - The security situation didn t allow the RECO to travel into the field (apart from Wajir town) - Some villages were not accessible due to the security situation e.g Gunana, Konton - During the SQUEAC a polio campaign was being conducted in Wajir East. Because of this Outreach sites were not working along the Stage 1 data collection because the children had received double ration the week prior to make up for time during the campaign. - On checking for the OTP admissions by category it was realized in some cases the admission was done by both MUAC and W/H but the information was not correctly captured in the registers. - On the admission information it was noted that the village information of where the beneficiaries came from were not collected in many of the OTP/ the patients cards which would make it hard to trace the kids. - There is not available a list of villages in small units (some villages are conglomerates of small villages) and some new villages were not included in the official list. SCI completed handly the list of villages. - No updated map of Wajir East was available. - The distance to the OTP sites wasn t available - Programme data for the years before 2012 was not available from both the SCI programme or the MoH for analysis for the SQUEAC survey. - Low SAM prevalence at the moment of the SQUEAC which made the precision of the likelihood survey low. 21

4. RESULTS 4.1. STAGE 1 4.1.1. Recommendations follow up of SQUEAC December 2011 Table 2: Resume of the recommendations of the SQUEAC of December 2011 and the follow up, Wajir East, Kenya. September 2013 Recommendation 1 Community sensitization Community sensitization should in particular seek to address 2 Community mobilization Description Achieved Fully Partial ly Not Ongoing Comments Previous rejection This is being addressed with the health workers giving health education but we need to see if it has worked during this survey Apathy in childcare and neglect Address any rumours or misinformation on the programme such as food contamination. Benefits of other interventions such as family planning (FP) Purposely target all key field sources of referral namely the Traditional Birth Attendants (TBAs), traditional healers and Sheiks. And work closely with the local administration and other social services available to support in enhancing childcare. SC has secured funding for FP component but it is a sensitive issue due to religion. TBA mainly have been used since they know the families Quarterly meetings with the local leaders Seek to map out migratory patterns in the county to enhance linkage between programs in the Sub County s during drought periods This was started but with the improvement of malnutrition this has been lower. The GFD targeting takes malnutrition as a target. Provide CHWs microphones and bicycles. There has not been funding for this

3 Strengthen support to MoH 4 Monitoring and evaluation SCI should continue offering technical support to MoH to build capacity in IMAM. In addition SCI should support in supervision of mobilization activities within the MoH facility catchment areas. Map out all catchment villages in the site areas and indicate the village of origin on the admission cards The admission cards should indicate the source of referral to assess the key referral sources in the community Confirm data accuracy particularly in comparison to the context e.g. defaulters. 5 Programming To address double registration that could be occurring in the Central division 6 Emergency The programme should have emergency programming strategies in case of unplanned occurrences. 7 Staffing Fast track recruitment of critical staff in The programme emergencies or explore different ways of should seek to: ensuring critical field positions do not stay vacant for very long. Address and support the community mobilizers and CHWs particularly with the reporting challenges. 8 Advocacy MoH ownership and facilitation to be able to comfortably manage IMAM. Infrastructure to facilitate in programme implementation mainly roads. On the job training has been on-going monthly. There are organized mass screenings when this is done. Mobilization however need to be strengthened This may not have happened due to high nurse workload. It is still thought to be important and agreed to be advocated for suggested to have data management meeting with facility staff. N/A The strategy changed and SC is no longer doing direct implementation. Training for CHWs has been done. Supportive supervision and On the job training ongoing but there are still issues on reporting. Now the MOH implementing the program Waiting to see this through the county government

4.1.2. Quantitative data analysis a. Needs response : admissions and defaulters trends compared to seasonal and key events calendar Figure number 4 shows the OTP admission over an 18 -month period (January 2012 June 2013). This graph is aligned with seasonal and Key event calendar developed by the investigation team (weather patterns, seasonal calendar of human diseases associated with SAM in children, food availability, and workload). Together these two figures helped evaluate to what extent the programme responds to seasonal needs. There were 54 defaulters along these months. Figure 4: OTP admission patterns over time compared with seasonal event calendar, Wajir East Sub- County, Kenya. Jan 2012-June 2013 Number of cases 300 250 200 150 100 50 Total (SC + OTP) x Total Defaulters 0 Jan Fev March Apr May June July Aug Sept Oct Nov Dec Jan Fev March Apr May June Season floods Hunger gap Food prize Diarrhea ARI Malaria Kalaazar Measles Herding (animals) Gum collection Nomadism Insecurity Ramadhan Animal calving BSFP SCI Funding Gap Mass Screening J F M A M J J A S O N D J F M A M J dry rainy dry rainy dry rainy Clan

For the period under review, (Jan 2012 to June 2013), a total of 2 666 SAM children were admitted to OTPs and SC with a mean of 148.1 children admitted per month. 54 defaulters were notified during the period. Data quality issues were detected in one OTP along the register revision in Stage 1 especially with the period after MOH took over management of IMAM (since August 2012) with very few numbers of defaulters reported (3). The SAM admission trends are reflecting few months of the year trends. The hunger gap is from January to Mid-April with a peak March. The admission trends however are low during the hunger gap. One of the reasons could be that families are moving with the animals in search of water and pasture 13. The admission peaks were usually after mass screening and during the rainy season which is also the peak period for most of the illnesses like diarrhoea, acute respiratory infections (ARIs) malaria and Kalazar. b. OTP vs SC admissions The percentage of children admitted to the SC could be an indicator of the timeliness of admissions. It is directly related to the percentage of SAM cases that arrive at the OTP with associated medical complications. Children remaining untreated for long periods with declining nutritional status develop medical complications and end up needing SC care. A high percentage of SAM cases with medical complications could often the product of a late presentation and uptake of services. In Wajir East Sub County proportion of programme admissions requiring inpatient care from January 2012 to June 2013 was 6.3%. This percentage is slightly above the 5% recommended for established programs but it is within acceptable limits. This could be partly because of referrals received from other Sub Countys like sub counties like Mandera West and Central and Wajir South Figure 5: OTP admission compared with SC admissions. Wajir East Sub County, Kenya. January 2012 to June 2013 13 Nomadism or hearding: during the rainy season communities move to the places where there are water (with no mosquitoes) 25

c. Admissions by OTP Figure 6 below shows the number of SAM cases admitted per OTP over a 12-month period (July 2012 June 2013). MCH OTP is the one that received more cases during the period (185 SAM admissions). This could be attributed to it being in an urban setting (Wajir town) and therefore has a high catchment population. The OTP sites with the least admissions were Sarman, Dunto and Hodhan which had been affected by insecurity during the clan clashes. Figure 6: SAM admissions per OTP site. Wajir East Sub-County, Kenya. July 2012-June 2013 Figure 7 below shows the percentage of SAM cases admitted per OTP and the percentage of population of the catchment area per OTP over the 18-month period (January 2012 June 2013). Figure 7: Percentage of SAM admissions per OTP and percentage of population catchment area. Wajir East sub county, Kenya. January 2012 -June 2013 26

Dasheq, Elben, Hungai, Kutulo, AIC, Alimaow, Arbaqaramso,MCH, Wajir bor and Wagberi health facilities are the ones that received proportionally much more percentage of cases than expected for their catchment area compared to Dambas, Dunto Sarman, korof Harar and Makoror health facilities who admitted few compared to their catchment populations. This could be attributed to wrong catchment population calculations, admissions from nearest villages which were not factored in the catchment population and double registration as was the case for AIC. This problem was mainly noticed in the relatively urban centers compared to the rural ones. d. Admissions MUAC Admission MUAC is an indicator for late /early presentation and service uptake at the OTP level. It can be a measure of direct coverage failure because late admissions are those non-covered SAM cases that went untreated for a significant period of time. Late admissions almost always require inpatient care and are associated with prolonged treatment, defaulting and poor treatment outcomes. Figure 8 reports the MUAC distribution for SAM cases admitted by MUAC from January 2012 to June 2013. The admission MUAC criterion is < 115 mm. The MUAC median at admission was 112 mm (in red). That means 50% or the children arrive with a MUAC less than 112 mm with some presenting with a MUAC as low as 90mm. The median MUAC at admission in general was very similar in all OTP ranging from 110mm and 114mm. The OTP with the least median MUAC at admissions was Tarbaj (105 mm). And the one that had the highest median MUAC were Arbaqaramso, Elben, jowhar and Katote OTP at 114 mm. During the analysis of MUAC data, an over-representation of rounded values (i.e. 105 mm, 100 mm, 90mm etc.) was observed, indicating imprecision in the MUAC measurement. Figure 8: MUAC at OTP admission. Wajir East Sub County, Kenya. Jan 2012-June 2013 27

e. Admission by type In the country, admissions for OTP are based on MUAC < 110 mm with (with length > 65 cm), and or WHZ score <-3 and or presence of bilateral pitting edema. In Wajir East 48.0% of the OTP admissions were based on MUAC and 47.8% were based on WHZ score as shown in the figure below. Figure 9: Percentage of admissions by the different admission criterion Wajir East, Kenya. March to August 2013 f. Performance indicators The performance indicators for the sub-county were within the acceptable SPHERE standards from January 2012 to June 2013. There were higher defaulting and non-response rates between the months of January to April in the two years which could be attributed to migration of the families with animals in search for pasture since this are the driest months. The performance indicators for the SC were 100% cure rates from July 2012 to June 2013 with the exception of January 2013 where there were 2 cases of defaulting. Figure 10: OTP Performance Indicators Wajir East, Kenya. January 2012 to June 2013 28

Looking at the performance indicators per OTP site however some of the OTP sites had 100% cure rates while in some on the sites like AIC defaulting was reported at greater that 50%. On going to the site to find out why that was the case it was discovered that this had been due to double registration with the beneficiaries served at both the MCH site and AIC. To curb this the distribution dates were synchronized and for this reason some most of them defaulted. The data quality in the site at the time of the survey was good. Figure 11: Performance Indicators per OTP site in Wajir East, Kenya. Jan 2012 to June 2013 g. Discharged cured The length of stay before recovery provides helpful insight into the duration of the treatment episode (e.g. the time from admission to discharge). In figure 12 below the OTP median length of stay (LoS) for children cured in the sub-county was 9 weeks however there was quite a no who stayed up to 15 weeks. The international standards define typical LoS should be between 30-40 days (4 to 6 weeks) to a maximum of 8 weeks. In this case the maximum length of stay was >15 weeks. And the median indicates the LoS in the Sub County is large because half of the cases stay more than the recommended maximum of 8 weeks. 29

Figure 12: Length of stay for discharge cured. Wajir East Sub-County, Kenya. May-August 2013 60 50 No Of Children 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 >15 No of Weeks in program h. Defaulters Figure 13 shows the median length of stay before defaulting in Wajir East (May to Aug 2013). A Short length of stay before default can suggest a poor reception or communication between beneficiary and health staff. On the other hand defaulters after several weeks of treatment could be related to long length stays (caretaker assuming the children is cured or tired of keeping on the treatment). Figure 13: OTP Length of stay before defaulting, Wajir East, KENYA. January 2012 May 2013. No of Children 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 >15 No of weeks in the program In Wajir East, the median week at defaulting was 5 weeks. There were defaulters both at the beginning of the treatment and after several weeks of treatment. Those who defaulted at the first and 30

second week were mostly from the sites that had been affected by the clan clashes (Dunto, Basanincha, Gunana). Those defaulters above 8 weeks could be related with the long LoS. The median MUAC at the last visit for defaulters is 11.5 mm. This means that 50% of the children defaulted from the programme before being recovered. i. Community mobilization In total there are 99 Community health workers in Wajir East. This translates to 2 CHWs per site with some sites with large caseloads having three. They are managed by the MOH through the public health department. For a duration of 2 months before the SQUEAC (July and August) the CHWs screened a total of 527 children (283 males, 244 females) and 355 Pregnant and lactating women (PLW) (181 pregnant, 174 lactating). Out of those screened a total of 106 children (54 males, 52 females) and 70 PLW (38 pregnant, 32 lactating). 4.1.3. Qualitative data analysis The qualitative methods used included focus groups, semi-structured and structured interviews, cases studies and observations. Doing so revealed boosters and barriers. Interviews and focus groups were conducted in villages across the sub county. Questionnaire guides were adapted and oriented to facilitate the collection of data pertinent to programme coverage and access. The investigation team also elaborated a list of terminology in the local languages (Annex 4) related to malnutrition and the RUTF. Qualitative data was triangulated by both method and source. All findings were indexed daily into the three-pane BBQ framework (complete BBQ can be found in Annex 5). Table 1 lists the sources and methods used during qualitative data collection. Questions ("Q") that appeared along stage one were analyzed and resolved within days. 31

Table 3:. SQUEAC BBQ framework legend. Wajir East Sub-County, KENYA. September 2013 Code Source Code Method Code Zone 1. SAM caretakers 2. Local authorities (religious, chief villages/elders) 3. Mother to mother support group (TBA) 4. Traditional healers/traditional dentist, TBA 5. OTP/ SC Nurse 6. CHW 7. Community of Women 8. Community of Men 9. Partners (WFP, etc.) 10. SCI programme staff 11. County /sub-county health authorities A. Group Discussion B. Semi Structured Interview C. Case Study D. Observation E. Data Analysis F. Last SQUEAC Dec 2011- jan 2012 C R Central Rest Table 2 details the principal factors that either negatively or positively influenced programme coverage and access during the qualitative data analysis in Wajir East; these are the main barriers and boosters. Table 4: Main programme barriers and boosters after qualitative data analysis. Wajir East Sub-county, Kenya. July 2013 Barriers Migration/ Nomadism( animals looking for water and pasture) Competing priorities disrupting OTP Services (Campaigns, trainings, meetings) Shortage and staff turnover at OTP sites Distance to health facilities/ OTP site Late seeking behavior (Sheikh, food) Boosters Good inter-linkage between community and health facilities (by CHWs follow up) Awareness of OTP and MUAC by caretakers and the community Good mobilization (Acceptance of program) Good integration at health facilities in services provided (Allows SAM Screening) Referrals from CHWs Collaboration and referral from TBA 32