GARISSA COUNTY FUNE LOCAL GOVERNMENT AREA APRIL/MAY ADAMU ABUBAKAR YERIMA NOVEMBER 2013 MOH, ACF, MERCY USA, UNICEF, TDH, APD

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ACKNOWLEDGEMENT Appreciation goes to the following persons with whose efforts the SLEAC survey exercise was successful:

1. The entire survey team from Action Against Hunger | ACF - International, Mercy USA, UNICEF, TDH, APD who worked tirelessly in the entire survey process. 2. The MOH team in County for the key role in planning of sensitization meetings, field data collection and dissemination of results. 3. Communities living in Garissa County who allowed the teams to assess their children thus providing the survey team with the information required. 4. The MOH West Pokot team who were key in sensitization meeting and data collection supervision.

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ACRONYMS ACF Action Against Hunger | ACF - International APD Agency for peace and development CHMT County Health Management Team CHWs Community Health Workers DHIS District Health Information System DNO District Nutrition Officer FS&L Food Security and Livelihoods GAM Global Acute Malnutrition CMAM Community-based Management of Acute malnutrition CMN Coverage Monitoring Network CNC County Nutrition Coordinator IRC International Rescue Committee KRCS Kenya Red Cross Society LQAS Lot Quality Assurance Sampling MAM Moderate Acute Malnutrition MOH Ministry of Health MTMSGs Mother To Mother Support Groups MUAC Mid-Upper Arm Circumference NGO Non-governmental Organization OTP Outpatient Therapeutic Program PSU Primary Sampling Unit RUSF Ready to use Supplementary Food RUTF Ready to use Therapeutic Food SAM Severe Acute Malnutrition SFP Supplementary Feeding Program SDU Service Delivery unit SLEAC Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage SMART Standardized Monitoring and Assessment of Relief and Transitions SQUEAC Semi Quantitative Evaluation of Access and Coverage TDH Terre des homes UNICEF United nation children’s fund WASH Water, Sanitation and Hygiene WFP World Food Program

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EXECUTIVE SUMMARY

The assessment was conducted to evaluate access and coverage of integrated management of acute malnutrition (IMAM) program among children aged 6 to 59 months with severe acute malnutrition (SAM) and moderate acute malnutrition (MAM). The most recent integrated nutrition survey1 carried out in April 2013 indicated wasting rates had reached the serious interpretation level2 with a Global Acute Malnutrition (GAM) rate of 12.0% (9.3-15.5 95%CI). No coverage assessment had been conducted before at Garissa County level. The program assessment was conducted in November 2013 using Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) with the main objective of mapping out coverage at Sub-County level and also provides possible recommendations for program reforms. The assessment was a participatory process conducted with financial and human resources from Ministry of Health (MOH) Garissa County, Action Against Hunger (ACF), Mercy USA, UNICEF, Terre des homes (TDH), and Agency for peace and development (APD). Members from MOH West Pokot also participated as survey team supervisors; this was a follow up on enhancing capacity earlier built on SLEAC methodology3. Coverage was classified based on the coverage standards as follows:  Low coverage: 20% or less.  Moderate: 20% up to less than 50%.  High coverage: 50% and above.

The estimates in some Sub-Counties were below the SPHERE minimum standards of 50% for IMAM coverage in a rural setting. Results indicated that IMAM program coverage was patchy in the County with results summarised in table 1.

Table 1: Summary of program coverage assessment results, Garissa County, November 2013 Sub-County OTP SFP 1. Fafi Moderate Moderate 2. High High 3. Garissa Low Moderate 4. Balambala High Low 5. Hulugho Moderate Moderate 6. Lagdera High High 7. High Moderate

Overall program coverage for Garissa County was 48.7% (40.9-56.5 95%C.I) and 40.7% (35.6-45.8 95% C.I) for Out Patient Therapeutic Program (OTP) and Supplementary Feeding Program (SFP) respectively.

Table 2 summarizes some of the barriers to program coverage and access identified across the Sub- counties and possible recommendations. Further investigation using Semi Quantitative Evaluation of Access and Coverage (SQUEAC) is proposed in Sub-Counties with low (Garissa) and high (Lagdera)

1Garissa County SMART survey April 2013 2 WHO threshold 2006 3 Training on SLEAC methodology July 2013 in West Pokot

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OTP coverage. This will gather more evidence to inform program reforms.

Table 2: Summary of barriers and recommendations

Barriers Recommendations Lack of program awareness Advocate for integrated outreach activities; carer support group trainings; continuous group health talks at health centre. Long distance and competing Integrated outreach services should be undertaken in villages household chores such as far from health facilities. livestock herding leading to high Community mobilization and sensitization on importance of defaulting. IMAM program should be enhanced. Active case finding and absentee/defaulter tracing should be emphasized. Need to support community units through engaging with Community Health Workers (CHWs) and reviving units which are not active. Lack of /inconsistent supply of Ensure timely supply of the commodities by Kenya Red Cross Ready to use Supplementary (KRCS) /World Food Program (WFP) to the Sub-Counties. Food (RUSF) and Ready to use Improve on timely and accurate reporting of stock. therapeutic Food (RUTF) Low understanding on Enhancing community sensitisation on acute malnutrition admission criteria to selective and the treatment protocol. feeding program by the caregivers. Ensure that rejected cases are told and made to understand reasons for non-admission. One of the ways to address this is for the program staff to explain to the caregivers the interpretation of the cut-off points and reasons why the program is selective. Poor adherence to IMAM Continuous On the job training (OJT) should be undertaken programs protocol by the health for health workers to ensure that IMAM program protocol is workers. strictly adhered to. Non-existence of IMAM program Sub-County health management team in Hulugho Sub County in Hulugho division. should work with supporting partners to ensure that IMAM program is initiated in all the health facilities. Low integration of IMAM Mentorship should be enhanced to the health workers program with other services through OJT to ensure that screening for malnutrition is done offered at the health facilities. to every child who attends the health facility.

TABLE OF CONTENTS

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ACKNOWLEDGEMENT ...... 2 ACRONYMS ...... 3 EXECUTIVE SUMMARY ...... 4 TABLE OF CONTENTS ...... 5 LIST OF FIGURES AND TABLES ...... 7 1. INTRODUCTION ...... 8 2. METHODOLOGY ...... 9

2.1 SLEAC PRIMARY SAMPLING UNITS (PSUS) ...... 9 2.2 SLEAC SURVEY SAMPLE DESIGN ...... 9 2.3 COVERAGE STANDARDS AND DECISION RULES ...... 10 2.4 COVERAGE ESTIMATORS...... 11 3. RESULTS ...... 11

3.1: OUTPATIENT THERAPEUTIC PROGRAM ...... 12 3.2 SUPPLEMENTARY FEEDING PROGRAM ...... 16 4. CONCLUSION AND RECOMMENDATION ...... 23 ANNEX 1: GARISSA SLEAC PARTICIPANTS ...... 30 ANNEX 2: GARRISA SLEAC SENSITIZATION MEETING SCHEDULE ...... 31 ANNEX 3: LIST OF SAMPLED VILLAGES IN EACH SUB-COUNTY ...... 32 ANNEX 4: QUESTIONNAIRE FOR CARERS OF SAM AND MAM CASES NOT IN THE PROGRAM ...... 34 ANNEX 5: WIDE AREA SURVEY TALLY SHEET...... 35 ANNEX 6: WIDE AREA SURVEY SUMMARY SHEET ...... 36

ANNEX 7: PARTICIPANTS DURING RESULTS PRESENTATION ...... 37

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LIST OF FIGURES AND TABLES

FIGURES Figure 1: Administrative structure of Garissa County ...... 9 Figure 2: Algorithm for a three-tier simplified LQAS classifier ...... 11 Figure 3: Map of OTP point coverage by Sub-County ...... 13 Figure 4: Reasons for not attending OTP in Hulugho ...... 15 Figure 5: Reasons for not attending OTP in Garissa Sub County ...... 15 Figure 6: Reasons for not attending OTP in Ijara ...... 16 Figure 7: Map of SFP point coverage by Sub-County ...... 18 Figure 8: Reasons for not attending SFP in Lagdera ...... 19 Figure 9: Reasons for not attending SFP in Dadaab ...... 19 Figure 10: Reasons for not attending SFP in Balambala ...... 20 Figure 11: Reasons for not attending SFP in Fafi ...... 20 Figure 12: Reasons for not attending SFP in Hulugho ...... 21 Figure 13: Reasons for not attending SFP in Garissa ...... 22 Figure 14: Reasons for not attending SFP in Ijara ...... 22

TABLES

Table 1: summary of program coverage assessment results ...... 4 Table 2: Summary of barriers and recommendations ...... 5 Table3: Sample sizes and number of villages sampled...... 10 Table 4: Assessment data per Sub County ...... 12 Table 5: OTP point coverage estimates ...... 12 Table 6: Overall OTP coverage estimates ...... 13 Table 7: Chi-square test analysis for OTP ...... 14 Table 8: SFP point coverage estimates ...... 17 Table 9: Garissa County overall SFP coverage estimate ...... 17 Table 10: Chi-square test analysis for SFP ...... 18 Table 11: County health management team and stakeholder discussions and recommendation ...... 24

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1. INTRODUCTION

Garissa County is located in North Eastern region of Kenya. It covers an area of 44,174.5 km2 with an estimated population of 623,0604. The County consists of seven Sub-Counties namely Garissa, Dadaab, Lagdera, Balambala, Ijara, Fafi and Hulugho. Rainfall pattern in the County is generally erratic and unreliable. The communities living in Garissa County are majorly pastoralist (90%), agro-pastoralist (7%) and others relying on formal employment and petty trade at 3%.5

The results of Garissa County integrated nutrition survey6 revealed serious7 GAM rates of 12% (9.3- 15.5 95% CI). This was a slight improvement though statistically insignificant in the nutrition situation compared to 2011 survey results (GAM 16.2%). The coverage assessment was conducted to evaluate access and coverage of IMAM program.

Important to note is that the assessment was done in collaboration with nutrition partners operating in Garissa County. MOH staff from also joined the team as supervisors. The West Pokot team had been trained earlier in July 2013 on program coverage methodology8. Specific objectives of the program coverage assessment were:  To map out coverage for both SFP and OTP at Sub-County level.  To provide an indication of coverage heterogeneity within the County.  To provide an overall coverage estimate for the County.  To provide relevant recommendations to enhance program coverage at the County.

This report describes the process and presents the results of the IMAM program coverage assessment conducted in Garissa County from 12th November to 3rd December 2013. The first two days were scheduled for sensitization meeting, while actual data collection process took place from 14th to 28th November 2013. Preliminary SLEAC results were shared at the County health management team (CHMT) on 29thNovember 2013 while presentation and validation of the results were disseminated on 3rd December 2013 at Garissa County health and nutrition forum.

4Kenya National Bureau of Statistics (KNBS) Census 2009. 5Long rains assessment July –August 2013 6Garissa County SMART survey April 2013 7 WHO standards 2006 8 SLEAC methodology

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2. METHODOLOGY

SLEAC methodology was employed to achieve the stated objectives. SLEAC is a rapid low-resource survey method that classifies coverage (e.g. low, moderate or high) at the service delivery unit (SDU) level and can estimate coverage over several service delivery units. The Sub-counties were selected as units of classification because service delivery in Garissa County is managed at Sub-County level. 2.1 SLEAC PRIMARY SAMPLING UNITS (PSUS)

SLEAC primary sampling units (PSUs) are the most basic administrative units within a study area within which the target population is sampled from. For this survey, villages were the PSUs across Garissa County. 2.2 SLEAC SURVEY SAMPLE DESIGN

First stage sampling method: Villages were sampled in each of the Sub-counties through systematic random sampling methodology from a complete list of villages stratified by administrative units (see Figure 1). Important to note is that all villages were included in the sampling frame except for villages that were known to be insecure. The target sample size for SLEAC in each Sub-County was determined using Lot Quality Assurance Sampling (LQAS) sampling calculator.

Dadaab Sub-County Divisions Location 36PSU sLocatio s36PS

Ijara Sub-County Divisions nsLocation 45PSUUs

sLocatio s45PS

Fafi Sub-County 16PSU Divisions nsLocation Us Divisions sLocatio s16PS GARISSA 211 Lagdera Sub-County Divisions nsLocation U26PSUs COUNTY PSUs Divisions sLocatio s26PS 211 Balambala Sub-County Us33PSU Divisions nsLocation PSUs Divisions sLocatio s33PS Garissa Sub- County Divisions Locationns 20PSUUs Divisions sLocatio s20PS Hulugho Sub-County Divisions Locationns 35PSUUs sLocatio s35PS

ns Us Figure 1: Administrative structure of Garissa County

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Table 3: Sample sizes and number of villages sampled

PARAMETERS DADAAB IJARA FAFI LAGDERA BALAMBALA GARISSA HULUGHO No. of villages 89 87 43 67 69 76 75 Total population 80,420 50,800 104,344 82,167 76,070 164,431 52,288

Total <5 years 14,475 9,144 16,486 14,132 10,801 26,308 9,411 Total 6-59 13,028 8,229 14,837 12,718 9,721 23,677 8,470 months SAM caseload 65 41 74 63 48 118 42 (0.5%) Target sample 25 21 27 25 23 31 21 size Average village 903 584 2426 1226 1102 2,163 697 population (all ages) Nth villages 36 45 16 26 33 20 35

Second stage sampling method: This involved active case finding or a house-to-house screening of children 6-59 months using paediatric MUAC tape and examination of bilateral pitting oedema. During the assessment all malnourished children identified who were not in IMAM program were referred to the nearest health facility. Survey team composition: A total of 14 teams, two per Sub-County participated during the sensitization meeting and data collection exercise. The survey team comprised of one MOH staff and one program staff from the partner organizations. One SLEAC trained person was allocated per Sub- County to guide the teams in the process. Once the team arrived at the sampled villages, a village elder/CHW/area chief was identified to guide the teams during data collection. The number of villages covered in a day varied depending on the village population and accessibility. Each day, the teams would submit data to the supervisor for quality checks and compilation. 2.3 COVERAGE STANDARDS AND DECISION RULES

Garissa County is a rural setting. SPHERE standards for measuring rural therapeutic feeding program s were considered and the following coverage standards were decided as most appropriate:  Low coverage: 20% or less.  Moderate: 20% up to less than 50%.  High coverage: 50% and above. These standards were used to create decision rules using the following rule-of-the thumb formulae below:

⌊ ⌋ ⌊ ⌋ ⌊ ⌋ ⌊ ⌋ ⌊ ⌋ ⌊ ⌋

These decision rules were used to classify coverage in each of the seven Sub-counties where: n = sample size achieved by the survey P1= lower threshold (20%) P2 =upper threshold (50%).

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A threshold value ( ) was established to determine the number of cases that need to be covered in order for coverage to be satisfactory as shown in Figure 2.

Number of NO Number of NO

Sample cases cases Classify as

covered covered LOW exceeds d2 exceeds d1 d2d2? ddjmkdd1d 1?

YES YES

Classify as Classify as HIGH MODERATE

Figure 2: Algorithm for a three-tier simplified LQAS classifier

2.4 COVERAGE ESTIMATORS

Generally, Garissa County IMAM program is exemplified by no or low active case finding, weak community mobilisation, high defaulter and long length of stay in the program as evident from the routine data. Point coverage was therefore the most appropriate estimator to use for reporting coverage of the program. The following formula was used to calculate point coverage:

푁푢푚푏푒푟 𝑜푓 푐 푠푒푠 푖 푟𝑜푔푟 푚푚푒 (푐) 푃𝑜푖 푡 퐶𝑜푣푒푟 푔푒 푇𝑜푡 푙 푐 푠푒푠 푓𝑜푢 ( )

3. RESULTS

This section presents findings that include Sub-County summaries, coverage classification for both OTP and SFP and barriers to access to IMAM program. A total sample size of 78 SAM cases was obtained against a target sample size of 173. The deviation could be attributed to improved household food security at the time of assessment9. The improved nutritional status of children might have lowered the SAM caseload considering that SAM prevalence was derived from April 2013 integrated

9 Long rains assessment 2013

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nutrition survey. The measure of coverage provides solely classification of coverage that is below or above a threshold as per the LQAS methodology employed. The lower-than-expected sample does not significantly affect the reliability of the results presented. Table 4 summarizes the SLEAC results for each Sub-County and overall County value.

Table 4: Assessment data per Sub-County

Sub-County Target SAM cases SAM In OTP MAM MAM In SFP Total sample found cases in recovering Cases Cases in Recoverin screened size (<11.5cm) OTP (>11.5cm) found(> SFP(>11. g(>12.5cm (SAM ) (n) (<11.5cm) 11.5- 5- ) (c) <12.5cm <12.5cm) ) Fafi 27 4 1 8 21 10 22 8,59 Ijara 21 22 19 21 135 82 7 2,982 Garissa 31 7 0 3 24 5 5 1,920 Balambala 23 7 6 12 49 8 50 1,447 Hulugho 21 27 6 0 210 58 33 2,818 Lagdera 25 6 6 6 46 37 27 1,729 Dadaab 25 5 4 10 16 7 7 2,846 County 173 78 42 60 501 207 151 14,601

3.1: OUTPATIENT THERAPEUTIC PROGRAM

Table 5 summarizes OTP point coverage results and provides a coverage classification based on the decision rule.

Table 5: OTP point coverage estimates Sub-County SAM cases SAM cases Decision Is c Decision Is c Coverage found (n) in OTP (c) rule (d1) >d1? rule (d2) >d2? Classification Fafi 4 1 0 Yes 2 No Moderate Ijara 22 19 4 Yes 11 Yes High Garissa 7 0 1 No 3 No Low Balambala 7 6 1 Yes 3 Yes High Hulugho 27 6 5 Yes 13 No Moderate Lagdera 6 6 1 Yes 3 Yes High Dadaab 5 4 1 Yes 2 Yes High

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Figure 3: Map of OTP point coverage by Sub-County

Four Sub-counties as shown in figure 3 achieved the SPHERE standards of ≥50%. Garissa Sub-County had the lowest coverage with none of the severely malnourished children assessed covered by the program. Weighted analysis for OTP coverage for the entire Garissa County was 48.7% (40.9-56.5 95% C.I.) classified as moderate. Table 6 below shows the weighted analysis for OTP coverage estimate.

Table 6: Overall OTP coverage estimates

Sub- Total % of <5 % of (6- SAM N W=N/ΣN (W Xc/n] County population 59) prevalence (SMART April 2013) Fafi 104,344 15.8 90 0.5% 74 0.164 0.041 Ijara 50,800 18 90 0.5% 41 0.091 0.079 Garissa 164,431 16 90 0.5% 118 0.262 0 Balambala 76,070 14.2 90 0.5% 48 0.106 0.091 Hulugho 52,288 18 90 0.5% 42 0.093 0.021 Lagdera 82,167 17.2 90 0.5% 63 0.140 0.14 Dadaab 80,420 18 90 0.5% 64 0.144 0.115 1 c Σ(WX /n)=0.487

The OTP coverage across Sub-counties was heterogeneous thus the overall County estimate should be interpreted cautiously. There was a significant difference between the expected and observed results; this is illustrated by chi-square test analysis obtained as indicated in table 7. The chi-square test value

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obtained was 18.04 which is greater than the critical value of 12.59 (for seven Sub-Counties), thus the coverage was patchy.

Table 7: Chi-square test analysis for OTP

Sub-County Sample Observed Expected (E) ( )

size (O ) (0 − E )2

Fafi 4 1 4 = 2.15 ( ) 1.32 0.61

Ijara 22 19 11.85 ( ) = 51.12 =4.31

Garissa 7 0 3.77 ( ) 14.21 = 3.77

Balambala 7 6 3.77 ( ) = 4.97 1.32

Hulugho 27 6 ( ) = 72.93 5.02

Lagdera 6 6 3.23 ( ) = 7.67 2.37

Dadaab 5 4 2.69 ( ) = 1.72 0.64

SUM 78 42 42 18.04

Barriers to OTP uptake and access

Various issues were identified as reasons why severely malnourished cases not covered were not attending OTP. These are classified according to respective Sub-Counties.

Hulugho Sub-County Lack of IMAM program was the main barrier in Hulugho Sub-County (Figure 4). The entire Hulugho division did not have any facility or outreach offering IMAM services. In other divisions namely Sangailu and Bothai previous rejection was cited by many caregivers; with an explanation that the community health workers did not admit the children to the program supposedly to reduce their workload. This indicates that some CHWs do not understand their roles thus regular OJT and close supervision is vital.

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Reasons for not attending OTP in Hulugho

Defaulted Site too far Previous rejection No IMAM programme

0% 10% 20% 30% 40% 50% 60% 70% 80% Proportion of children not covered

Figure 4: Reasons for not attending OTP in Hulugho

Garissa Sub-County Discharged while not cured came out strongly as the main barrier in Garissa Sub-County (Figure 5). A case scenario was a severely acute malnourished child with medical complications who had been admitted to the stabilization centre at Provincial General Hospital. After meeting discharge criteria, the child was not transferred to OTP but was rather sent home. Other reasons affirmed by caregivers were that they had other competing duties to attend to and thus had no time to attend to the program. Difficulties with childcare and previous rejection were also cited by some of the caregivers.

Reasons for not attending OTP in Garissa

Previous rejection Difficulty with child care No time/too busy Discharged not cured

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Proportion of children not covered

Figure 5: Reasons for not attending OTP in Garissa Sub-County

Ijara Sub-County There were three main reasons for not attending to OTP in Ijara namely; Defaulting, inconsistency of outreach services and caregivers being too busy to attend to the program because they had other household chores to attend to (Figure 6).

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Reasons for not attending OTP in Ijara

IMAM programme defaulted

No time/too busy

Defaulted

0% 5% 10% 15% 20% 25% 30% 35% Proportion of children not covered

Figure 6: Reasons for not attending OTP in Ijara Dadaab Sub-County Dadaab had one major issue; RUTF stock-out. It was noted during brainstorming session that initially Dadaab did not have a store previously thus they obtained supplies from Lagdera Sub-County. Delay in submission of monthly reports leading to a delay in delivery of the supplies was cited from discussion as an attribute to RUTF stock out. Informal interviews indicated some of the boosters as good program awareness and active case finding.

Balambala Sub-County Absenteeism and shortage of health workers with some health centres being run by one health worker was the major issue in Balambala. Caregivers cited that most of the time they go to the health facility to seek for services, they find it closed because the health worker is away. This was also mentioned during brainstorming session that based on previous supervision reports there has been serious absenteeism in Balambala Sub-County specifically in two health facilities (Jarajara and Daley).

Fafi Sub-County Lack of outreach services was the only barrier in Fafi Sub-County as the Sub County is vast with long distances to health facilities. Community near Hagadera refugee camp were not allowed to get services at the camp.

Lagdera Sub-County All the severely malnourished children found in Lagdera were attending the program. Active case finding was mentioned as the key to success in Lagdera Sub-County.

3.2 SUPPLEMENTARY FEEDING PROGRAM

Table 8 summarizes SFP point coverage results and provides a coverage classification based on the decision rule.

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Table 8: SFP point coverage estimates

Sub- MAM MAM Decision Is c Decision Is c Coverage County cases cases in rule (d1) >d1? rule >d2? Classification found (n) SFP (c) (d2) Fafi 21 10 0 Yes 10 No Moderate

Ijara 135 82 27 Yes 67 Yes High

Garissa 24 5 4 Yes 12 No Moderate

Balambala 49 8 9 No 24 No Low

Hulugho 210 58 42 Yes 105 No Moderate

Lagdera 46 37 9 Yes 23 Yes High

Dadaab 16 7 3 Yes 8 no Moderate

Balambala Sub-County had the lowest SFP point coverage below 20% with Lagdera and Ijara Sub- counties meeting the SPHERE standards above 50%. Weighted analysis for SFP coverage for the entire Garissa County was 40.7% (35.6-45.8 95% C.I.) classified as moderate. Table 9 shows the weighted analysis for SFP coverage estimate.

Table 9: Garissa County overall SFP coverage estimate

Sub Total % of <5 % of MAM N W=N/ΣN (W Xc/n) County population (6-59) prevalence Fafi 104,344 15.8 90 3.9% 578 0.164 0.078 Ijara 50,800 18 90 3.9% 320 0.091 0.055 Garissa 164,431 16 90 3.9% 923 0.261 0.054 Balambala 76,070 14.2 90 3.9% 379 0.107 0.018 Hulugho 52,288 18 90 3.9% 330 0.093 0.026 Lagdera 82,167 17.2 90 3.9% 496 0.14 0.113 Dadaab 80,420 18 90 3.9% 508 0.144 0.063 3534 1 Σ(W Xc/n)=0.407

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Figure 7: Map of SFP point coverage by Sub-County

The SFP coverage across Sub Counties was heterogeneous. There was a significant difference between the expected and observed results; this is illustrated by chi-square test analysis obtained as indicated in table10. The chi-square test value obtained was 48.94 which is greater than the critical value of 12.59 (for seven Sub-Counties), thus the coverage was patchy.

Table 10: Chi-square test analysis for SFP

Sub- Sample Observed Expected (E) ( )

County size (O ) (0 − E )2

Fafi 21 10 21 = 8.68 ( ) 1.74 0.200

Ijara 135 82 55.78 ( ) = 687.49 =12.32

Garissa 24 5 9.92 ( ) 24.21 = 2.44

Balambala 49 8 20.24 ( ) = 149.82 7.37

Hulugho 210 58 86.77 ( ) = 827.71 9.54

Lagdera 46 37 19.00 ( ) = 324 17.05

Dadaab 16 7 6.61 ( ) = 0.15 0.02

SUM 501 207 207 48.94

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Barriers to SFP uptake and access Reasons for moderately malnourished children not covered by SFP are categorised according to respective Sub Counties. Defaulting is a major issue across most of the Sub Counties due to long distances and difficult with child care. In adequate screening and relapse also came out strongly as some of the reasons the cases were not covered.

Lagdera Sub-County The main barrier to SFP coverage in Lagdera was long distance and lack of means of transport to the program delivery point (Figure 8).

Reasons for not attending SFP in Lagdera

Defaulted Child not screened at health… Difficulty with child care Discharged as cured Site too far

0% 5% 10% 15% 20% 25% 30% 35% Proportion of children not covered

Figure 8: Reasons for not attending SFP in Lagdera

Dadaab Sub-County Child not screened at the facility/ outreach site was the main reason cited by the caregivers in Dadaab Sub-County. This is an evidence of inadequate active case finding at the outreach sites and low passive screening at the health facilities. Other reasons included previously rejected for the program whereby carers of rejected children become unwilling to attend the program even when their children health condition deteriorates. Others were too busy with other chores therefore could not attend to the program (Figure 9).

Reasons for not attending SFP in Dadaab

Previous rejection No time/too busy Child not screened in the…

0% 10% 20% 30% 40% 50% 60% Proportion of children not covered

Figure 9: Reasons for not attending SFP in Dadaab

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Balambala Sub-County The main reason cited by carers in Balambala Sub-County for not attending the program was previously discharged as cured; which relapse of acute malnutrition. Defaulting and child not being screened also came out strongly. Caregivers whose children were not screened mentioned that they had been in the health facility for other services but their children were not screened, indication of inadequate passive screening at the health facilities (Figure 10).

Reasons for not attending SFP in Balambala

Previous rejection Household migrated far away Site too far No time/too busy Child not screened Defaulter Discharged cured 0% 5% 10% 15% 20% 25% 30% 35% 40% Proportion of children not covered

Figure 10: Reasons for not attending SFP in Balambala

Fafi Sub-County The main reason reported was that the site for IMAM program was too far and there were no outreach services to the villages (Figure 11). Other reasons included lack of integrated10 program, not allowed to attend to the program in Hagadera refugee camp and previously discharged as cured.

Reasons for not attending SFP in Fafi

No outreach Defaulter Discharged cured IMAM program only for refugees Program not integrated with outreach Site too far 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Proportion of children not covered

Figure 11: Reasons for not attending SFP in Fafi

10 Only immunization services are undertaken at the outreach sites

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Hulugho Sub-County No knowledge of IMAM program in Hulugho Division was the main barrier (Figure 12). Poor adherence to IMAM program protocol by health workers was evident, about 16% of the caregivers cited that their children were discharged before they got cured. There was also inadequate integration of IMAM program with other services since children seeking other services were not screened in some health facilities and outreach sites. This is also an indication of inadequate active and passive case finding. Defaulting and difficulty with childcare and previous rejection was evident in the other divisions which have IMAM program.

Reasons for not attending SFP in Hulugho

Discharge cured Child not screened Discharge not cured No time/too busy RUSF stock out Site too far Previous rejection Difficulty with child care Defaulter No IMAM programme 0% 10% 20% 30% 40% 50% 60% 70% 80% Proportion of children not covered

Figure 12: Reasons for not attending SFP in Hulugho Garissa Sub-County Difficulty in childcare was the main reason cited in Garissa Sub-County; most caregivers stated that they were unable to attend to the program because they had other children to take care of (Figure 13). Previous rejection was also highly cited; carers whose children had been previously screened and rejected never bothered to attend to the program again.

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Reasons for not attending SFP in Garissa

No time/too busy Discharged cured Site too far Child not screened in hospital Previous rejection Defaulter Previous rejection Difficulty with child care 0% 5% 10% 15% 20% 25% Proportion of children not covered

Figure 13: Reasons for not attending SFP in Garissa

Ijara Sub-County Defaulting was the main reason moderately malnourished children were not covered in SFP. Previous rejection, relapse cases and inadequate screening also highly contributed to non-attendance to SFP program (Figure 14). Carers whose children had been previously screened and rejected due to various reasons would never bother to attend to the program again. Some of these carers had been told that their child was not malnourished and would not be admitted to the program, or that there were no rations for SFP thus the child could not be admitted to the program. Observations and informal interviews indicated that the program awareness among the care givers was good, as well as existence of active case finding.

Reasons for not attending SFP in Ijara

Discharge as not cured never interested in programme Site too far No time/too busy Child not screened in hospital Discharge as cured Previous rejection Defaulter

0% 5% 10% 15% 20% 25% 30% 35% Proportion of children not covered

Figure 14: Reasons for not attending SFP in Ijara

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4. CONCLUSION AND RECOMMENDATION

Most barriers identified during the SLEAC assessment points to weak community mobilisation component of the IMAM program, poor adherence to IMAM protocol by health workers and low integration of the program with other services in the health facilities in Garissa County. The program should therefore invest adequate resources (time, financial and human) into community-based activities to ensure optimal service delivery.

Further SQUEAC investigations in a Sub-County with low coverage (Garissa) and another with high coverage (Lagdera) is recommended. This will gather in depth information on the barriers which could be used to reform the program as well as boosters which other Sub-counties can adopt to improve their program coverage. Table 11 indicates the possible recommendations specified for each Sub-County. This will call for more actions through prioritized interventions to ensure attainment of SPHERE minimum standards of above 50% as depicted for rural settings.

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Table 11: County health management team and stakeholder discussions and recommendation

Issues arising Sub-County Recommendations Action Plan Process indicators Responsible Outreach program is not FAFI Ensure at all times that Advocate for integrated Integrated outreaches MOH and integrated with IMAM; only outreach services are fully outreaches by all the conducted in all the supporting immunization services are integrated so that the partners. villages far from the partners undertaken at the outreach members of the community health facilities sites. far from the health facilities can as well receive the essential health care. Lack of outreach services to FAFI Scale-up outreach services Proper identification and All outreach sites MOH and most of the villages far from to areas not covered and mapping all the villages identified and clearly supporting the health facilities and enhance community in need of outreach mapped out. partners therefore the caregivers do not mobilization and services by MOH and know of program s that treat sensitization. partners. All the outreach sites acute malnutrition MOH allocating the functional and outreach sites to the supported different partners for Key messages support. developed and Conduct community disseminated. awareness sessions on IMAM and to increase population awareness about acute malnutrition. Host communities are not FAFI Outreach services should Lobby with agencies Meetings with MOH and allowed to attend to IMAM be undertaken at the host supporting refugee stakeholders planned supporting

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program in Hagadera since it is community program to initiate a host and conducted partners only for refugees. community program There was inconsistency of IJARA Ensure that there is All partners to share Quarterly plans MOH and outreaches with some villages consistency in the delivery quarterly activities and developed and supporting totally stopped without the of program outreaches close monitoring and reviewed regularly. partners knowledge of the caregivers. There should be improved feedback enhance communication among all through Sub-County stakeholders on the NTFs. management of Exit plan should also be outreaches.. developed during the initial phase of the program Difficulty in childcare was the GARISSA Sensitization of the Identify the mothers MOH and main reason cited in Garissa mothers on the importance affected by the problem Appropriate activities supporting Sub-County; most caregivers of the program. and link them with organized and partners stated that they were unable to Identify mentor mothers mentor mothers. implemented. attend to the program because through mother to mother they had other children to take support groups who will Organize activities to be care of too. assist them understand undertaken through child health and also other MTMSGs services available such as family planning etc.

The Sub-County has shortage FAFI Regular supervision of Undertake monthly joint Supervision schedules CHMT and of health workers such that health workers should be supervision and and reports compiled. Sub-CHMT some health centres are run by enhanced. Follow-up and mentoring of health one health worker. feedback mechanisms workers. More health workers Nonetheless it was noted that strengthened. deployed at the health there is a serious absenteeism Lobby at the County level centres. in some health facilities to ensure that more specifically in Jarajara and health workers are Daley and this clearly has a employed and deployed. negative impact on program coverage. Lack of IMAM program in the HULUGHO IMAM program should be The DNO -Ijara to have a Gaps identified, report MOH to entire Hulugho division, and put in place in Hulugho meeting with supporting compiled and spearhead. most of the caregivers were division. partners on possibility of appropriate capacity Partners not aware of the program. jumpstarting IMAM building of health supporting Intensive community program at Hulugho Sub workers done before nutrition in mobilization and District Hospital as a the program is started. the county. sensitization should be matter of urgency. undertaken.

It was noted that there is low HULUGHO To ensure effective Re-open the closed health All closed facilities CHMT and staffing, low immunization, and implementation of IMAM facilities and deploy opened and staff deployed Sub-CHMT high malnutrition. Lack of program, key strategies health workers to offer reporting because there is few need to be devised by MOH the services. technical staff to write the and partners to improve reports or analyse the situation service delivery and fill on the ground. staffing gaps in the Sub Two health facilities are also county.

closed due to lack of staff to offer the services. Previous rejection at the health HULUGHO Identify CHWs who can Community to identify CHWs identified and Facility in- facility mainly by the support at the facility when the CHW and facility in- trained charges, community health workers the facility staffs are not charge undertake OJT community who avoid admitting eligible there in order to avoid leaders. children to ease workload. interruption of services and neglect of patients especially in facilities which have only one health worker. Health workers should closely supervise CHWs. Distance to the health facility. LAGDERA Increase outreach/mobile Mapping of all villages far Outreach schedule MOH and sites to address the from the health facilities covering all the villages partners problem of distance. and ensure that they are developed and reached through implemented. outreaches. RUTF/RUSF stock-out renders DADAAB Mentoring through OJT Nutrition reports should RUSF/RUTF requested caregivers reluctant to attend should be undertaken to be properly reviewed early enough and no to IMAM program. It was noted ensure that timely good before submission to the stock-out at all times. during discussion that quality reports are DHIS. commodity dispatch depends submitted. on timely and quality reports KRCS, MOH, from the health facilities which WFP is not the case in many health Proper coordination and All communication facilities. communication should be should be done in writing There has also been poor enhanced between the to improve accountability

supply coordination by the MOH and the KRCS to and service delivery. WFP cooperating partner improve the supply chain leading to delayed deliveries of nutrition commodities and supply of short expiry commodities to facilities.

There is high defaulting, a IJARA Establish the root cause of Sensitise the community MOH and great barrier to program BALAMBAL high defaulter rate. on the importance of partners coverage A The health workers consistent attendance to Monthly review of the HULUGHO together with supporting IMAM program. defaulters traced at the partners should establish a Involve CHWs to trace the facility level. strategy to ensure that all defaulters defaulters are traced and brought back to the program. There is high relapse of acute FAFI, Identify the reasons for Multi-sectoral Underlying causes of MOH and malnutrition. BALAMBAL relapse and ensure that the collaboration with other malnutrition identified partners ALAGDERA underlying causes of sectors such as WASH, and addressed supporting malnutrition are addressed FSL nutrition, by linking the affected WASH and children to the appropriate FSL activities program s Previous rejection by the DADAAB To enhance proper and Mentor program staff OJT schedule developed Program program was evident; the IJARA continuous program through OJT. and implemented staff, Carers of previously rejected GARISSA sensitisation at community CHMT and children were unwilling to level to ensure that all the partners attend the program even when key issues and protocols their children's condition are known by the

deteriorates. community. Poor integration of IMAM BALAMBAL Mentorship should be Set up quarterly OJT OJT checklists program with other services in AGARISSA enhanced to the health activity schedules which developed, reports MOH and the health facility. IJARA workers through OJT to should be evaluated. reviewed and compiled supporting DADAAB ensure that screening for partners IMAM program is done to every child who attends the Mass screening activity health facility at all entry Partners to have a budget scheduled for each points. for quarterly mass MUAC quarter developed and Low active case finding Conduct quarterly mass screening implemented. MUAC screening and sensitization campaigns in the whole Sub-County.

Annex 1: Garissa SLEAC participants NO NAME AGENCY POSITION 1 ABDI ADEN KOSAR APD Nutrition Officer 2 ABDIAZIZ RONE ELMI MOH- IJARA Nutritionist 3 ABDIKADIR ABDALLA ACF HiNi Officer 4 ABDIMALIK IBRAHIM MOH- IJARA DNO 5 ABDULLAHI MOHAMED MERCY USA Community Mobilizer 6 ADAN DAGANE GEDI MERCY USA Community Mobilizer 7 AHMED HAJI MOH- GARISSA CPHO 8 AHMED HASSAN MOH- LAGDERA Nutritionist 9 ALI AMIN ACF Volunteer/ Enumerator 10 ALIBILE AHMED ACF Nutrition Officer 11 ALISIA OSIRO ACF Nutrition program Manager 12 ASLI AHMED MOH- DADAAB Nutritionist 13 CAROLINE MWANIKI MOH- GARISSA Nurse 14 CLAUDET K. BARAZA MOH- FAFI Nurse 15 FAITH NZIOKA ACF FSNS Ass. Program Manager 16 GULED AHMED MERCY USA Enumerator 17 HASSAN ALI MERCY USA M & E officer 18 HUSSEIN IBRAHIM APD Nutrition Officer 19 KEVIN MUTEGI ACF FSNS Officer 20 LATHAN OSMAN MOH- GARISSA Nurse 21 LAURA KIIGE UNICEF Nutrition Officer 22 LEAH CHELOBEI MOH –WEST POKOT CNO 23 LILIAN BIWOTT MOH- BALAMBALA Nurse 24 MARK MIRITI MOH- BALAMBALA Nurse 25 MERAB APONDI MERCY USA Field Coordinator 26 MOHAMED ALI OMAR MERCY USA Community mobilizer 27 MOHAMED MALELE MOH- DADAAB Nutrition Nurse 28 MOHAMUD OSMAN MERCY USA Deputy Field Coordinator 29 MUSA INDETIE MOH- GARISSA Ag CNC 30 MUSA TOTO MOH- LAGDERA DNO 31 OWAKA ISAAC MOH - WEST POKOT PHO 32 PAULINE WAWERU MOH- HULUGHO Clinical Officer 33 RAGOW GABOW TDH HNE 34 ROSELYNE ARUSEI ACF FSNS Officer 35 SULEIMAN M. KHALIF MOH- HULUGHO Nurse 36 UBAH MUSTAFA MERCY USA Intern/Enumerator 37 VIVIAN KENDUIYWA MOH- FAFI DNO 38 YUSUF ALI ACF Nutrition Deputy Program Manager

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ANNEX 2: Garrisa SLEAC sensitization meeting Schedule Sensitization meeting held in Nomads hotel, Garissa

Date Time Activity schedule Key person 12/11/2013 8:00am Arrival 8:05AM-8:10am Introduction MoH 8:10AM Opening remarks by County health Dr. Mohammed A. Sheikh. coordinator 8:30AM- An overview of objectives of program Faith and Laura 10:00am coverage assessment 10:00pm- Tea break 10:30pm 10:30pm- SLEAC Methodology Kevin and Leah 1:00pm 1:00pm-2:00pm Lunch break 2:00pm-4:00pm Field procedures MOH staff at each Sub- County, Alisia, Hassan and Merab Overview of complete villages in Sub- Counties Sampling of villages per Sub-County Hassan and Kevin 4:10pm Participants can leave at their own pleasure 13/11/2013 8:00am Arrival 8:10am- Finalization of field procedures Hassan and Kevin 9:300am How to conduct MUAC Musa Indetie measurements/Oedema examination Overview of data collection tool and Faith and Isaac tally sheet Calendar of events Hassan 9:30-10:00am Movement plan Faith and Roselyn 10:00am Tea break To be shared among team leaders Teams to depart to their respective allocated Sub-County

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ANNEX 3: List of sampled villages in each Sub-County S/NO LAGDERA DADAAB BALAMBALA GARISSA FAFI HULUGHO IJARA 1 Bulla Madina Bulla township Balambalacentre Shimbirey Mansabubu Hulughocentre Arislay 2 Bulla Kuwait FafahKalaa Bulla msikiti Bulla Mzuri Mathabgesi Bulla ahmed BulaSarman 3 Elanle Bulla Guro Bulla Hospital Bulla Hajji Welmerer Jilomata BulaDahir 4 Barfin Waanri Bulla Gun Toure Kiwanja Kabasalo Kalangalderow 5 Skansaka Marodhiley Jarajara Dololoweyne Buiyoadhan Dafedam Dabarmatan 6 Gosma Abdisamad Hifow Barka Inyasin Korahindi Gababa 7 Garse Bulla Gussa Kone Faryar Bogour Bulla Iftin Dahir 8 Janju Bulla Riig Hagarjarer Eldere Jelow Korogai Danai 9 Qurahey and Libahlow Daley centre Sanbul Hasisimey Hursan Alijarire 10 Garson Bulla Banan Der derey Bulla kari Mufti Gololbele Hubi 11 Fadiweyn Labasigale Welmarer Jarirof Degwardey Kulan Abalatirow 12 Dal Lehele Aligabey AgalAar DekaBune Guyo Boni BulaWaraday 13 Bulla kulan Bulla sheikh Danyere center Bulla Adaan Bulla sharif Junction Gerille 14 Bulla Secondary Bulla deka Bulla Tunki Bulla Punda Warable Iredkele Hussein Katalo 15 Benane township Bulla crush Bulla Gullet Ziwani Ruqa Doy Gurei 16 Kambisamaki Bulla primary Elane Kambi Moto Degwardey Baldig MAAH-V-DAM 17 Eldere township Bulla Dana Gawan Al-faruq Saberal Dama 18 Sarti Bulla School Kasha centre Bulla Riiq Kolosh dam Moit 19 Labile Uthole Bulla Hagar Bulla Tawakal Bobtay Dabelweeyne 20 Jilango Sarira Omar Muhamud Bulla Iskadek Dibayu konodinto 21 Goriale township Bulla Gudud Ohio Bultuhama Konodinto 22 Bulla Abey Bulla Deka Mudey Bulla gogor Gumarey 23 Bulla Oscar Bahuri Bulla mobile Kartoub Bulla godon

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24 Ahmed Tukale Bulla Qalbidawac Damaja Mataarba Sagar 25 Sabena Bulla Riig Gabobey Arab dere QololDerow 26 Tuere Bulla Mosque Fardiweyne Goloshgutu Konso 27 Bulla AP Hirbai Maradulow Livestock 28 safaricom Habarow Kenisaa Asmali 29 Abdisugow Gel disdis Wakabharey Warlay 30 DamajaleAbak Halkano Gololo Ijaracentre 31 Bulla red cross Kora Harerdero Sangoleycentre 32 Bulla Kiwanja Sickley Ege Bulawacha 33 Bulla carlifornia Kiwanjandege Irekharwa Agudaley 34 Bulla daresalaam Habarkolisa Sufi Bashir 35 Madhahgisi Gundi 36 Malayley 2 Hamorat 37 BulaHawo 38 BulaFarow 39 BulaHidaya 40 BulaGuwa 41 Abdigure 42 Ndapia 43 Bulla Dakran 44 Turkata 45 Ruqa

ANNEX 4: Questionnaire for carers of SAM and MAM cases not in the program Sub-County:______Village______Team No.______Date______1. Do you think that this child is malnourished? 1. YES 2. NO □ 2. Do you know of a program that can treat malnourished children? 1. YES 2. NO □ IF YES... 3. What is the name of this program? ______4. Where is this program? ______5. Has this child ever been to the program site or examined by program staff? 1. Yes 2. NO □ If YES... 6. Why is this child not in the program now? □Previously rejected □Defaulted □ Discharged as cured □ Discharged as not cured □Other reasons______7. If YES in Qn 2 and NO in Qn 5 then why is this child not attending this program? Do not prompt. Probe ‘Any other reason?’(I. YES 2. NO) □ Program site is too far away □ No time/too busy to attend the program □ Carer cannot travel with more than one child □ Carer is ashamed to attend the program □ Difficulty with childcare □The child has been rejected by the program □Other reasons______

ANNEX 5: Wide Area Survey Tally sheet Sub-County:______Village:______Team: ______Date:______# OF SAM SAM CASES IN IN OTP # OF MAM MAM CASES IN SFP CASES FOUND OTP PROGRAM CASES FOUND IN SFP PROGRAM (MUAC (MUAC BUT (MUAC ≥11.5- (MUAC BUT ≤11.4/oedem ≤11.4/oedem RECOVERED ≤12.4) ≤12.4) RECOVERED a) a) (MUAC (MUAC ≥12.5) or no oedema) 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 Total children 6-59 months screened 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000

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ANNEX 6: Wide area survey summary sheet SLEAC SUMMARY SHEET Date:…………………………....Sub-County………………………...Name of team leader……………………...... Team no:……......

Name Total number Total Total number Total Total Total number Total of the of SAM cases number of in OTP number of number of of cases in children village found SAM cases program but MAM cases MAM cases SFP program 6-59 (MUAC in OTP recovering found in SFP but months <11.5/ (MUAC (MUAC (MUAC (MUAC recovering screened oedema) <11.5/ ≥ . or no ≥11.5- <12.5) (MUAC ≥12.5) oedema) oedema) <12.5)

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ANNEX 7: Participants during results presentation Name Designation Organization Email Address Cell-phone

Dr. Mohamed Abbey County DH MOH [email protected] 0722111263

Dr. Sofia Mohamed Chief Officer of Health MOH [email protected] 0725300625

Musa Indetie Ag. CNC MOH [email protected] 0724940474

Abdimalik Ibrahim DNO (Ijara) MOH [email protected] 0722646373 Bashir Hassan DPHN (DDB) MOH [email protected] 0721270698 Mohamed M. Abdi Ag.DMOH (DDB) MOH [email protected] 0717057288 m AbdirashidDiney DMOH Hulugho MOH [email protected] 0720918149 Aden Musa Nutrition Officer IRC [email protected] 0724872764 rg Dr. Ochieng Erick DMOH MOH [email protected] 0726142614 Hassan M Hassan DMOH MOH [email protected] 0721544392 Hassan Anshur DPHN (Ijara) MOH [email protected] 0720265250 DabasoJillo FC MSF [email protected] DaudHirey DMOH, Lagdera MOH [email protected] 0720326580 Pauline Akoth RNO KRC Omolo.pauline@kenyaredcr 0724294777 oss.org Alicia Bonnie NUT PM ACF Nut-ddb.ke@acf- 0707181422 international.org Dr. Farah Amin DMOH MOH [email protected] 0710719920 Francis Kidake NSO (Dadaab) UNICEF [email protected] 0728592369 Antony Kanja NUT. OFFICER KRCS Kanja.antony@kenyaredcro 0728067350 ss.org Dr. sanjeevVerma HPM TDH Hpm.ke@tdh-ch 0706056636 Amina Maalim CPN KRCS [email protected] 0729276031 m MerabApondi FC MERCY USA [email protected] 0721124727 Kevin Mutegi FSNS OFFICER ACF Fsnsoff-nbo@acf- 0725635303 international.org Musa Toto DNO MOH [email protected] 0723988593 Pamela Kaguri NUT. Officer MOH [email protected] 0718255467 Hussein Mohamed CDIO NDMA [email protected] 07229088457 Alio AlkajeroGitari DPHN (Hulugho) MOH [email protected] 0725593367 Dr. Njoroge PMCC MOH [email protected] 0729682838 Omar Mahat CMLS MOH [email protected] 0726794527 Mohamed Yussuf CHOP MOH [email protected] 0723782547

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Evan Bett M&E (ACF) ACF m&eddb-ke@acf- 0707181420 international.org Siyat Hassan DPHN (FAFI) MOH-FAFI [email protected] 0722947573 Mohamed Salat CNO MOH [email protected] 0721424557

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