West Pokot County‐ SQUEAC Investigation June, 2012

SEMI QUALITATIVE EVALUATION OF ACCESS & COVERAGE (SQUEAC)

REPORT

WEST POKOT COUNTY

Funded by

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TABLE OF CONTENTS BACKGROUND ...... 4 INVESTIGATION PROCESS ...... 4 STAGE ONE: Identification of areas of high and low coverage and reasons for coverage failure using available program data ...... 4 MUAC ADMISSIONS: ...... 7 STAGE TWO: HYPOTHESIS TESTING ...... 8 STAGE THREE: WIDE AREA SURVEY ...... 9 Developing a prior: ...... 9 Sampling methodology ...... 11 Spatial representation ...... 11 WIDE AREA SURVEY RESULTS ...... 12

LIST OF FIGURES Figure 1: Program admissions in West, North and Central Pokot districts ...... 5 Figure 2: Trends in diarrhoeal incidences in West Pokot County ...... 6 Figure 3: Admissions and defaulters in North Pokot district ...... 6 Figure 4: Admissions and defaulters in Central Pokot district ...... 6 Figure 5: Admissions and defaulters in West Pokot district ...... 7 Figure 6: MUAC admissions ...... 7 Figure 7: OTP Register snap shot ...... 7 Figure 8: Test prior curve ...... 11 Figure 9: Summary of reasons for non‐attendance ...... 12 Figure 10: Resultant curve of prior, likelihood and posterior ...... 13

LIST OF TABLES Table 1: Hypothesis test findings ...... 8 Table 2: Small area survey for coverage classification ...... 9 Table 3: Contributing weights of boosters and barriers to coverage ...... 10 Table 4: Minimum number of villages ...... 11 Table 5: Summary of stage three findings ...... 12 Table 6: Key findings and possible recommendations ...... 14

APPENDIX APPENDIX 1: WEST POKOT STAGE THREE DETAILED FINDINGS ...... 16 APPENDIX 2: SEASONAL CALENNDER, WEST POKOT COUNTY. Adopted from FEWSNET ...... 17 APPENDIX 3: MAP OF WEST POKOT COUNTY ...... 17 APPENDIX 4: OUTREACH SITES IN POKOT NORTH DISTRICT ...... 18 APPENDIX 5: OUTREACH SITES IN POKOT CENTRAL DISTRICT ...... 18 APPENDIX 6: OUTREACH SITES IN WEST POKOT DISTRICT ...... 20

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LIST OF ABBREVIATIONS ACF‐ Action Against Hunger AIC – African Inland Church GAM‐ Global Acute Malnutrition IMAM‐ Integrated Management of Acute malnutrition IYCN‐ Infant and Young Child Nutrition KAP‐ Knowledge Attitude and Practice MUAC – Middle Upper Arm Circumference NGO‐ Non‐governmental Organization OTP‐ Outpatient Therapeutic Program RUTF‐ Ready to use therapeutic feeds SAM‐ Severe Acute Malnutrition SMART‐ Standardized Monitoring and Assessment in Relief and Transitions SQUEAC‐ Semi Quantitative Evaluation of Access and Coverage SFP‐ Supplementary Feeding Program WASH – Water, sanitation and hygiene

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BACKGROUND

West Pokot County lies in and has three districts. These are Central, West and North Pokot districts. The county is vast and is divided into three main livelihood zones namely agro pastoral, pastoral and mixed farming. Malnutrition rates in West Pokot in May 20111 were close to emergency threshold. Global and Severe acute malnutrition rates of 14.9 %( 13.5‐ 18.8) and 2.3% (1.3 – 4.2) respectively were unveiled with proxy program coverage estimates of 19.4% and 50.0% for SFP2 and OTP3 accordingly. These findings were unveiled at a point in time when the main nutrition partner (Samaritan’s Purse International)was moving out of the area (May 2011). ACF thus moved into the county to bridge the gap beginning in October 2011. The agency’s activities mainly focus on nutrition with sanitation and hygiene aspects incorporated. This was a phased approach that sought to deal with the vastness of the area beginning in Central Pokot and eventually trickling into North and West districts. As highlighted above, malnutrition rates in the county have generally been poor with May 20124 unveiling GAM5 and SAM6 rates of 12.3 %( 9.3‐ 16.0) and 1.5% (0.7‐ 3.2) respectively; design effect of 1.21. This situation indeed calls for concerted efforts to curb further deterioration. It was thus necessary to undertake a coverage investigation in West Pokot County with the following objectives:  To determine baseline coverage of SAM programs using an approved methodology for Kenya, (SQUEAC)  To identify possible boosters and barriers to coverage  To develop feasible recommendations based on assessment findings  To capacity build ACF and Ministry of Health personnel in West Pokot County on the basic of how to undertake a coverage investigation The SQUEAC investigation was carried out by ACF Kenya with the support of ACF‐UK’s Evaluations, Learning & Accountability Unit. A three stage methodology was employed during this exercise.

INVESTIGATION PROCESS

STAGE ONE: Identification of areas of high and low coverage and reasons for coverage failure using available program data

A number of program data set that could either boost or hamper program coverage was reviewed during this exercise. This was a participatory approach undertaken by five persons from the Ministry of Health in West Pokot County and five ACF program staff.

1 MAY 2011 West Pokot Integrated Nutrition and Food Security survey ; Samaritan Purse International &Yedidah consultancy firm 2SFP: Supplementary Feeding Program 3OTP: Outpatient Therapeutic Program 4 Integrated SMART survey by ACF Kenya mission 5GAM: Global Acute Malnutrition 6SAM: Severe Acute Malnutrition

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PROGRAM ADMISSIONS

300 WEST NORTH CENTRAL 250 200 150 100 50 0 FEB FEB JAN JAN DEC OCT AUG JULY NOV MAY MAY SEPT MAR JUNE APRIL APRIL MARCH

2011 2012 Figure 1: Program admissions in West, North and Central Pokot districts The trends in admissions show a similar pattern in the three locations from January 2012 with a peak noted in February 2012 as highlighted above. This was mainly attributed to ACF – roll out of nutrition activities into the two other districts, Central and North Pokot. No comparisons or deductions can be made from the data in 2011 since available data was unreliable. Investigation findings indicate gaps in reporting in the past year as there was a parallel system in use. What this meant is that not all data was being channeled to the Ministry of health and having a comprehensive overview at the time of assessment was a challenge. The reporting rates from most facilities were less than 100.0% with some data missing from registers as shown below. For example, physical address in the register was missing. This would eventually make defaulter tracing and follow up challenging. Nevertheless, the graphs obtained were studied to deduce factors behind these. As illustrated above, admissions were generally lower in West Pokot as compared to the other two districts. This was and is mainly attributed to relatively lower case loads by virtue of its livelihood zone as well as increased awareness of programs, relatively good access to facilities as most are situated along passable and all weather roads. Admissions were relatively higher in the North and Central Pokot districts. In North, most admissions were from two non‐government facilities. These were Alale AIC7 and Amakuriat mission hospitals. Further probing into the matter indicated consistency in RUTF supplies, a motivated and dedicated team hence services are excellent and good documentation as observed. Indeed, these acted as pull factors for beneficiaries' to the facilities. It should however be noted that accessibility to most parts of this district is hampered more so during the rainy seasons. This eventually affects the reporting rates and access by beneficiary to health facilities. Most of the above factors affect Central district.

7 African Inland church

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The figure below highlights some of the weakness noted such as lack of reporting with data missing at some points as highlighted. For example, no data could be obtained in North Pokot district from January to May 2011 due to lack of records/no reporting.

Figure 2: Trends in diarrhoeal incidences in West Pokot County PROGRAM ADMISSIONS AND DEFAULTER This section presents the findings of admissions and defaulters by district. The data quality was questionable as most of it was incomplete Nevertheless; deductions were made on trends observed. Beans harvesting is done in August.

180 NORTH ADMISSIONS NORTH DEFAULTERS Most households thus move far 160 away from home to the farms 140 120 thence the high defaulters. 100 However, it should be noted 80 60 that defaulters in August 40 surpass the admissions as 20 0 highlighted

FEB FEB JAN JAN DEC OCT AUG JULY NOV MAY MAY SEPT MAR

JUNE Figure 3: Admissions and APRIL APRIL

MARCH defaulters in North Pokot 2011 2012 district

140 CENTAL ADMISSIONS CENTRAL DEFAULTERS As noted above, the defaulters 120 in November are more than 100 admissions. This simply means 80 that the retention of 60 beneficiaries in the program at 40 that point in time was 20 compromised. 0

FEB FEB JAN JAN DEC OCT AUG JULY NOV MAY MAY SEPT MAR Figure 4: Admissions and JUNE APRIL APRIL

MARCH defaulters in Central Pokot 2011 2012 district

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WEST ADMISSIONS WEST DEFAULTER 120 100 80 60 40 20 0 FEB FEB JAN JAN DEC OCT AUG JULY NOV MAY MAY SEPT MAR JUNE APRIL APRIL MARCH 2011 2012

Figure 5: Admissions and defaulters in WestPokot district

MUAC ADMISSIONS: The figure below indicates a very long tail with MUAC admission. This is an indicator of late care seeking behaviour attributed to a number of factors to include competing activities by caretakers like cultivation of land and gold mining. Care practises were further worsened by long distance to facilities in the midst of limited outreach services whose services are further hampered by inaccessibility due to heavy rains.

400 MUAC MEASUREMENTS AT ADMISSION 350 300 250 200 150 100 50 0 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.1 9.0 <9.0 11.4 11.3 11.2 11.1 11.0 10.9 10.8 10.7 10.6 10.5 10.4 10.3 10.2 10.1 10.0 MUAC MEASUREMENT Figure 6: MUAC admissions The figure above further illustrates digit preferences during MUAC measurements. Records audit indeed indicated that most measurements are indeed rounded off mostly to point zero and five as indicated in the snap shot to the left.

Figure 7: OTPRegister snap shot

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SUMMARY OF QUALITATIVE DATA ON COMMUNITY PERCEPTONS

CAUSES OF MALNUTRITION Believed to be caused by lack of food as a result of poor harvest, cattle migrating in the dry season , witchcraft

REASONS FOR DEFAULTING Long distance to facitlities, lack of supplies at the facility, some households are scared of pictorial presentations of malnourished child especially in an area called Tapach where malnutrition is assosciated with HIV/AIDS, physical barriers such as lagas, perception on RUTF that it is for HIV Aids patients, family conflicts, lateness of health workers at the facility, insecurity, plenty of milk after long rains thus there is no need to seek health care

HEALTH SEEKING BEHAVIOUR: This is mainly sort from hospitals, traditional herbs or sacrifices

The community perceptions above indeed indicate the need for the various actors led by the Ministry of Health to improve on a couple of issues to include sensitization on malnutrition, its causes and management. The hypothesis below was thus developed: Coverage is low in North (pastoral) and Central (Agro pastoral) districts and high in West Pokot districts (Mixed farming) The contributing factors to the development of this hypothesis were . Livelihood zones as indicated in the brackets above. The pastoral nature in the North district is a barrier to access as population movements is seasonal and rampant as compared to the other sites more so the West district. The data sets showed an increase in defaulters from the North and Central districts. . Accessibility to facilities and services is better in West as compared to other districts . The county head quarter is situated in West Pokot district. This area therefore has the privilege of getting information and updates earlier (well informed) before other sites. As such, West has more programs by NGO’s as compared to other districts translating into more awareness

STAGE TWO:HYPOTHESIS TESTING

Sample sites for testing the hypothesis were identified purposively with findings tabulated below Table 1: Hypothesis test findings DISTRICT Recovering Severe Severe malnourished Summary reasons for non‐ child in malnourished child childe NOT IN PROGRAM attendance program IN PROGRAM WEST 1 0 1 NEW CASE CENTRAL 0 0 2 DEFAULTER, NEW CASE NORTH 6 21 9 DEFAULTER, NEW CASE

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The information above was used to classify coverage against the SPHERE acceptable coverage in rural set ups. A threshold of 50.0% was thus used. The decision rule was therefore calculated using the following formula: d= [n x p/100] where n and p refers to the following: n = total number of cases found p = coverage standard set for the area Table 2: Small area survey for coverage classification COVERAGE CLASSIFICATION DISTRICT DEDUCTIONS CALCULATION/FINDINGS Coverage standard (p) 50.0% Coverage cannot be deduced for =1* (50/100) =0.5 WEST POKOT Decision rule (d) this area since number of cases if Thus zero too low Cases covered 0 Coverage standard (p) 50.0% Number of cases covered (0) is Decision rule (d) =2* (50/100) = 1 less than decision rule of 1 CENTRAL POKOT thence coverage is less than Cases covered 0 50.0% Coverage standard (p) 50.0% Number of cases covered (9) is Decision rule (d) =30* (50/100) =15 less than decision rule of 15 NORTH POKOT Cases covered 9 thence coverage is less than 50.0%

The findings above clearly indicated that coverage was low in North. However, the sample size obtained in Central and West Pokot was too small to either confirm or deny the hypothesis. The team thus moved onto stage three to determine the head coverage

STAGE THREE: WIDE AREA SURVEY

Developing a prior:

The Bayesian technique was used in stage three. The data gathered in stage one and two were consolidated and analyzed to make more sense as the analysis evolved. This was thereafter grouped into two; boosters and barriers and thereafter weighted. The score ranged between 0 and 5; with zero being the least score in that order. The scoring process was participatory. A factor was identified and each participant gave a score which was then averaged to provide the factor score as shown in the table below. The boosters were thereafter added to the minimum coverage (0.0%)while the barriers deducted from the maximum coverage (100.0%). A median value was thereafter calculated.

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Table 3: Contributing weights of boosters and barriers to coverage BOOSTERS VALUE BARRIERS Outreach services social mobilization 4.4 4.7 Poor topography /terrain Appropriate IEC materials 2.8 3.3 Poor integration, team work and motivation of staff Motivation of CHWS with incentives 3.6 3.0 Stigma about malnutrition and nutrition supplements. Sensitization of the community 4.1 3.9 Competing activities Availability and commitment of CHWS in some 3.3 4.5 Poor documentation and reporting facilities Integration of program activities and services 4.5 2.8 Migration patterns especially in North Pokot (pastoral) Calendar activities such as Malezi 4.1 2.8 Rejection of beneficiaries in the facility (Adherence to admission criteria protocols by staff is interpreted as rejection by the community) 3.5 Non consistent supply chain of RUSF8, CSB and oil (Lapse in distribution to facilities) 3.4 Inadequate staff especially in Government facilities 3.6 Inadequate and improper storage of RUTF 3.4 Lack of awareness 2.6 Insecurity/politics 3.0 Stigma about malnutrition and RUTF 3.2 Weak supervision of staff TOTALS 26.8 47.7 Added to minimum coverage (0.0%) 26.8 52.3 Subtracted from maximum coverage (100.0%) MEDIAN 39.6 Alpha(α) value 14.2 22.0 Beta(β) value

The obtained median value was then used to determine the test prior in the SQUEAC coverage estimator calculator (Version 2.02). The highlighted alpha and beta values were obtained and used in determining the minimum sample size required as explained below.

8 RUSF: Ready To Use Supplementary Food

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Figure 8: Test prior curve

Sampling methodology

Minimum sample size The following formula was used in the determination of the above to achieve 34 cases n= mode x (1‐mode) ‐ (α + β – 2) (Precision / 1.96) squared

Calculations were then undertaken to determine the minimum number of villages to sample as shown in the table below Table 4: Minimum number of villages

Target Sample Size: 34 (as per calculations above) 328 (Approximated from Kenya National Bureau of statistics census Average village population 2009.) Prevalence of SAM: 1.5% (Point estimate from May 2012 Integrated SMART survey) % Children aged 6‐59 months: 19.2% (WEST POKOT COUNTY specific figures from statistics office) Total villages to sample 36 VILLAGES (based on calculations)

Spatial representation An up to date map (AO) of the study area was obtained to scale (see Annex). This was instrumental in determining the 36 villages to sample. Several quadrants were first drawn and sampling done in 12 of these quadrants as they covered 50.0% or more of the study area, with a total of three villages sampled (selection based on proximity to the village to center) per quadrant to obtain the required sample (36). It is important to note that one quadrant was not assessed due to security concerns in the area.

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In the village, an active and adaptive case finding method was used. In each village, a key informant was identified. Case sensitive definitions were shared with the informant that were later used to identify a case. Subsequent cases were identified through this, snow balling as well as screening of children less than five years of age.

WIDE AREA SURVEY RESULTS Table 5: Summary of stage three findings Number of cases Number of current SAM cases 41 Number of SAM cases in the program 12 Number of SAM cases not in the program 29 Number of recovering cases attending the program 17

The figure below summarizes the reasons for non‐attendance to programs Reasons for non attendance, West Pokot County

Defaulter

Difficulty with child care

Program site too far

not aware of malnutrition

Not aware of the programme

0 5 10 15 Figure 9: Summary of reasons for non‐attendance OVERAL COVERAGE ESTIMATION

This report presents the point coverage as the best estimates of the situation as per findings on ground. The rationale behind this being poor case finding and late presentation and admission in West Pokot

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Figure 10: Resultant curve of prior, likelihood and posterior The figure above indicates a strong overlap between the likelihood and prior. The point coverage was thus estimated at 33.5% (24.0 – 44.8).This is below the SPHERE bench mark of 50.0% in rural areas.

CONCLUSION AND RECOMMENDATIONS

The year 2011 was a major transition phase in nutrition in West Pokot County. This marked the exit of one partner in May 2011, a program gap for close to five months before the entry of ACF. The change had not only been for the implementing partners but also key personnel from the ministry of health. Continuity of earlier established measures was thus hampered as this started from scratch. The following recommendations are thus put forth with this back ground in mind

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Table 6: Key findings and possible recommendations

ISSUE POSSIBLE RECOMMENDATION Vastness of the county that limits access to . The staff capacity in West Pokot County at the moment is various parts due to heavy rains and at times stretched. This should be increased while maximizing on insecurity available community units through advocacy Poor documentation, for example, lack of . Strengthen the on job training on appropriate and proper exit details, no physical address to enhance documentation while increasing awareness of health follow up in case of defaulters information management Lack of representativeness was cited in the . There is routine support supervision undertaken by the various recruitment of CHW’s posing a challenge in stakeholders. This should be supported by documentation of reporting as some CHW’s are working where findings and areas for follow up at both facility and regional there are no community units offices for close follow up of measures that have been put in Lack of training and roll out of the WHO place CHANIS and shortage of Mother child . Involvement of provincial administration in CHW recruitment so booklet as to appropriately link them to community units. . Lobby for funds from various stakeholders in the district to be able to have adequate training tools to undertake training and roll out of WHO CHANIS reporting indicators . Lobby for funds from stakeholders to support in the production of mother child booklets Increased distance to health . Integrated IMAM into existing outreach sites and increase facilities/centerswith no IMAM integration numbers/coverage of these based on needs in existing outreach sites . Full support needs to be accorded to outreach sites as the Ministry of Health is using Health Sector Strategic Funds High defaulter rates . Strengthen the community component by increasing number of community unit personnel through innovative approaches such as volunteerism . Initiate where there is need and enhance active case finding and defaulter tracing at community levels Poor anthropometric measurement, with a . Have follow up sessions on the classroom trainings undertaken lot of digit preference and rounding off as . Ensure that all facilities have appropriate and functional shown below anthropometric equipment e.g. in Parua  The training package of CHW’S in community units needs to incorporate a component of nutrition to enable the CHW’S take proper MUAC measurements as well as understand screening and referral criteria Lack of awareness on what malnutrition is as  Create and increase awareness on these issues through well as the targeted feeding programs sensitization forums such as calendar activities, community meetings, trainings, church forums, baraza’s while also developing appropriate IEC material as feedback from informal sessions indicated that some caretakers were put off by the generic “scary” pictures of malnourished children

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Poor IYCN practices evidenced by the . Undertake a detailed IYCN study to clearly understand following: factors surrounding this components and how best to . Low exclusive breast feeding rates address them of 36.0% (May 2012) . Community sensitization by CHW’S , growth monitoring . High stunting levels 43.2% (38.5 – 48.0) . Analysis by age of admission in OTP indicated that close to 50.0% of these were infants aged 6 – 12 months Poor Water sanitation and hygiene (WASH) . Strengthen WASH programs in the area. This can be done especially in North and Central Pokot through a detailed KAP study on WASH that would clearly districts. assist in definition of programs The May 2012 SMART survey noted an increase in diarrheal incidences amongst children less than five years from 22.3% in May 2011 to 51.3% in May 2012. This was mainly attributed to open defection, utilization of unsafe water sources and poor hand washing practices at critical points.

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APPENDIX 1: WEST POKOT STAGE THREE DETAILED FINDINGS SEVERE MALNOURISHED CASES NOT IN VILLAGE NAME SCREENED MAM RECOVERING IN PROGRAM PROGRAM 1 CHERANGANY 23 9 1 0 0 2 AMOLICH / NAKWIJIT 101 4 0 1 1 3 AKIRIAMET 64 0 0 0 1 4 LOKITELAWIAN 75 8 2 0 6 5 TANDAPOS 55 7 0 0 1 6 KALOKUNA 29 2 0 4 1 7 NARUORO 59 12 1 2 2 8 KARON 100 1 0 0 0 9 KASIKIREI 20 3 0 0 0 10 KATAPOTIN 65 2 0 0 0 11 TIYENEI 35 3 0 0 0 12 NAMORU 46 6 0 0 0 13 KATUDA 35 0 0 0 0 14 KAMILA 55 7 0 1 2 15 SEBIT 86 0 2 0 3 16 PARUA (TARIKIT) 54 0 0 0 3 17 AKIRIAMET CENTRAL 35 4 3 0 1 18 IMONPOGHET 29 5 0 0 0 19 TIKIT 58 23 0 0 0 20 SIMBOL 29 3 0 0 0 21 SARAMEK 19 3 0 0 0 22 MURKOKOI 60 1 0 0 0 23 KAPKORIS 60 4 1 0 1 24 KOCHIY 68 3 0 0 3 25 MUGHAT 67 7 0 0 0 26 MARING 47 1 0 1 0 27 CHIKAR 56 3 0 0 2 28 PITPAGH 36 4 1 1 1 29 ANNET 51 11 0 0 0 30 CHERATAK 40 1 0 0 0 31 KOROMONOT 48 5 2 0 1 32 CHEPKECHIR 35 1 1 0 0 33 AMAKURIAT EAST 16 1 0 0 0 34 TISON/PUTOR 38 6 3 2 0 1694 150 17 12 29

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APPENDIX 2: SEASONAL CALENNDER, WEST POKOT COUNTY. Adopted from FEWSNET

APPENDIX 3:MAP OF WEST POKOT COUNTY

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APPENDIX 4: OUTREACH SITES IN POKOT NORTH DISTRICT S/NO LINKED FACILITY OUTREACH SITE 1 KACHELIBA DH MURWEPONG 2 KONYAO DISPENSARY MADING 3 AMAKURIAT DISPENSARY NANGILAP 4 KAURIONG DISPENSARY WASAT 5 LOSAM DISPENSARY LOSAM 6 AIC ALALE KASES AIC ALALE MBARU AIC ALALE TATWA AIC ALALE ALANY AIC ALALE KAMILA AIC ALALE NAPELET 7 BFC BENDERA CHEPKONDOL [KASEI] 8 KACHELIBA MOBILE POKOTUSA KACHELIBA MOBILE CHERANGAN KACHELIBA MOBILE NAKWIJIT KACHELIBA MOBILE KARAMERI APPENDIX 5: OUTREACH SITES IN POKOT CENTRAL DISTRICT NO LINK FACILITY OUTREACH 1 KABICHBICH HEALTH CENTRE CHESUPET KABICHBICH HEALTH CENTRE CHEPKONO KABICHBICH HEALTH CENTRE SIMOTWO KABICHBICH HEALTH CENTRE TONOYON KABICHBICH HEALTH CENTRE KAPSAIT KABICHBICH HEALTH CENTRE KOPKUNYUK 2 KAPTABUK DISPENSARY POROWO KAPTABUK DISPENSARY SINGOROKOI KAPTABUK DISPENSARY CHEPARTEN KAPTABUK DISPENSARY SARAMEE 3 SINA DISPENSARY SUKUT SINA DISPENSARY SESIMWO SINA DISPENSARY NGATANGAT SINA DISPENSARY SIKOWO 4 TAPACH DISPENSARY KAMELEI TAPACH DISPENSARY KOKWOPSIS TAPACH DISPENSARY KAPUSIEN 5 SONDANY DISPENSARY CHONGIS 6 PARAYON DISPENSARY PARAYON PARAYON DISPENSARY SEKUTION 7 KAPSNGAR DISPENSARY KAGHMUU KAPSNGAR DISPENSARY PSUKUNO KAPSNGAR DISPENSARY CHEPYOMOT 8 WAKOR DISPENSARY KOKWOTENDWO WAKOR DISPENSARY YAYAU

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WAKOR DISPENSARY ONOCH WAKOR DISPENSARY TOOSIKIRIO WAKOR DISPENSARY SOKA WAKOR DISPENSARY IYON WAKOR DISPENSARY SKAK/KOKWOTENDWO 9 ORTUM MISSION PARUA ORTUM MISSION SAMICH ORTUM MISSION CHEPTIANGWA ORTUM MISSION KERELWA ORTUM MISSION MORPUS 10 SEKERR DISPENSARY CHEPTEM SEKERR DISPENSARY MBARA SEKERR DISPENSARY TEMOGH SEKERR DISPENSARY SOSTIN SEKERR DISPENSARY MARINY SEKERR DISPENSARY NGOYOMWO SEKERR DISPENSARY KAPORO SEKERR DISPENSARY CHOPOTWO 11 MARICH DISPENSARY ORWA MARICH DISPENSARY KALOYATUM 12 NASOLOT DISPENSARY PAREK 13 SSDH PTOKOU SSDH SANGAT 14 TAMKAL DISPENSARY SOLION TAMKAL DISPENSARY KOKWOSOSION TAMKAL DISPENSARY PAROO TAMKAL DISPENSARY NYARPAT 15 CHESTA DISPENSARY CHEMURLOKOTYO CHESTA DISPENSARY KAPATET CHESTA DISPENSARY OTIOT CHESTA DISPENSARY SUPETOY 16 ANNET DSIP PITPAGH ANNET DISP CHERATAK 17 ARPOLLO DISP SABULMOI ARPOLLO DISP CHESEGON 18 MASOL SIMBOL 19 LOMUT DISP NYANGAITA LOMUT DISP KAMANAU LOMUT DISP TAKAIYWA

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APPENDIX 6: OUTREACH SITES IN WEST POKOT DISTRICT LINK FACILITY OUTREACH SITES 1 D.H. MCH NATELENG & TALAU 2 KAIBOS DISPENSARY PARAIYWA 3 KAPKORIS DISPENSARY CHEPKAPECHAK & CHELOWO 4 CHEPKECHIR DISPENSARY LOTONGOT 5 CHEPARERIA S.D.H. MCH CHEPTURNGUNY 6 KERINGET HEALTH CENTRE KANGILIKWAN, PSIGIRIO & KITALAPOSHO 7 TURKWEL HEALTH CENTRE CHEPOKACHIM, RITING & SIRWACH 8 SEREWO HEALTH CENTRE MERIESE AND KAMAIYECH 9 TAMOUGH HEALTH CENTRE MISKWONY & TOPTOLUM 10 PTOYO DISPENSARY KESOT, TIPET, MERUR&TAMQRKWA 11 EMPOUGH DISPENSARY KRICH & PSAPAI 12 CHEPNYAL DISPENSARY KOTIT, FOREST & CHEPKALIAN 13 CHEPKOPEGH DISPENSARY SHALPOUGH, KAIKAI, TIKEN & CHEMATONG 14 PSERUM DISP CHEPTIANGWA&KAKALAS 15 YWALATEKE DISP MONGORION 16 CHEPARERIA SDA PROPOI 17 NARAMAM DISPENSARY TIRKET 18 KADOKONY DISPENSARY KRESWO, MORTOME & LOKURNOI 19 KANYARKWAT DISPENSARY KATIKOMOR, KARENGER & LOLOTWO 20 ADURKOIT DISPENSARY AUSIKION 21 POOLE DISPENSARY KITALAKAPEL 22 NACHECHEYET DISPENSARY KOITUKUM & KOPEMOI 23 MISKWONY NAKWIJIT, KACHAMBILWA & CHEMAKEU 24 BFC CLINIC KAPROM

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