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FUNE LOCAL GOVERNMENT AREA APRIL/MAY ADAMU ABUBAKAR YERIMA WEST POKOT COUNTY
KENYA JULY 2013 ACF AND CMN
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ACKNOWLEDGEMENTS Sincere gratitude goes to the following persons without whose support to the SLEAC training and survey could not have been possible:
1. Entire survey team from ACF Nairobi and West Pokot offices, Ministry of Health in West Pokot, other agencies including Food for the Hungry Kenya, International Medical Corps, Mercy USA, UNICEF and World Vision Kenya who participated in the SLEAC training and survey.
2. Entire ACF and Ministry of Health - West Pokot team who were involved in all the key decisions, planning and logistics.
3. Enumerators and drivers for the hard work in the field. 4. Emmanuel Mandalazi, Valid International consultant for the Coverage Monitoring Network
(CMN), for his technical support throughout the entire training and survey process.
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ACRONYMS ACF Action Against Hunger
CHWs Community Health Workers
CMN Coverage Monitoring Network
CSAS Centric Systematic Area Sampling
DNO District Nutrition Officer
ENA Emergency Nutrition Assessment
FHK Food for the Hungry International Kenya
FSNS Food Security and Nutrition Surveillance
GAM Global Acute Malnutrition
IMAM Integrated Management of Acute malnutrition
MAM Moderate Acute Malnutrition
MOH Ministry of Health
MUAC Middle 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
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
TBA Traditional Birth Attendant
VI Valid International
WVK World Vision Kenya
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EXECUTIVE SUMMARY Action Against Hunger/ACF-USA has been supporting the Ministry of Health (MoH) in implementing an Integrated Management of Acute Malnutrition (IMAM) programme in West Pokot County since September 2011. ACF took over this supportive role from Samaritan’s Purse International which was the main nutrition partner in the sub-county and had phased out its support from the area in May 2011.
In the course of programme implementation, ACF together with its partners including MoH and UNICEF decided to assess programme coverage in June 2012. At that time, a Semi Quantitative Evaluation of Access and Coverage (SQUEAC) investigation of the West Pokot IMAM programme was conducted which established a point coverage of 33.5% (95% CI: 24.0% - 44.8%)1
The SLEAC survey was an On-the-Job-Training (OJT) exercise for ACF staff, Ministry of Health and other partners such as Food for the Hungry Kenya, Mercy USA, International Medical Corps, World Vision, and UNICEF, and was conducted from 28th June to 18th July 2013.
for the Out-patient Therapeutic Programme (OTP) component of the IMAM programme in West Pokot county. For the present coverage assessment conducted a year later, Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) methodology was chosen so that in addition to providing an overall coverage estimate for the entire county, a mapping of coverage at the sub-county, as well as identification of any coverage heterogeneity within the county was undertaken.
Results Coverage classification Coverage was established through the SLEAC methodology based on the coverage classification standards used to classify coverage in each of the four sub-counties:
• Low coverage: 20% or less • Moderate: greater than 20% up to 50% • High coverage: above 50%
Based on the three-tier classification approach described above, none of the four sub-counties achieved high coverage classification. The point coverage for OTP was moderate in North Pokot and South Pokot, whilst low in West Pokot and Central Pokot. The overall county point coverage classification was moderate. SFP point coverage classification was found to be low across all the four sub-counties and the county coverage classification was also low.
Overall coverage estimates The overall OTP point coverage estimate was 21.7% (95% CI: 12.7% - 30.7%), and the overall SFP point coverage estimate was 10.0% (95% CI: 6.7% - 13.3%).
Barriers to service uptake and access
• In North Pokot, the major barriers identified were: o Previous rejection for MAM cases (access to SFP), and o Lack of programme understanding for SAM cases (access to OTP).
1 ACF, West Pokot County- SQUEAC Investigation Report, June, 2012
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• In South Pokot, the main barriers were: o Defaulting and lack of knowledge among SAM cases carers, and o Lack of programme awareness among MAM cases carers.
• In Central Pokot, the main barrier to access to OTP and SFP was lack of programme awareness
by carers of both SAM and MAM cases.
• In West Pokot, lack of programme awareness was the main reasons for failure to attend both OTP and SFP component of the programme.
Recommendations
- Advocacy meetings at all levels with all partners in nutrition and health programmes as well as with community leaders such as chiefs, village elders, and religious leaders to increase programme awareness.
- Use of mass media especially local radio stations to raise programme awareness and to improve community’s understanding/recognition of malnutrition.
- Orientation of mother support groups including Traditional Birth Attendants, Reproductive Health Workers and teachers of Early Childhood and Development schools in active case finding.
- Increase outreach/mobile sites to address the problem of distance.
- Ensure integration of screening for malnutrition in the existing services to ensure that there are no missed opportunities.
- Maintain constant supply of RUTF/RUSF to avoid the problem of defaulting due to stock outs.
- Ensure that rejected cases are handled carefully and are made to understand reasons for non-admission. One of the ways to address this is for the programme staff to avoid central screening where even healthy children are asked to come for measurement. More Community Health Workers (CHWs) or other community volunteers should be identified and trained to assist with active case finding, and caregivers should be encouraged to take the child to the volunteer in their settlement for MUAC or oedema check or take the child to the health facility providing OTP/SFP every time they suspect that s/he is becoming malnourished.
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LIST OF FIGURES AND TABLES
FIGURES
Figure 1: Administrative structure of West Pokot County used for sampling (that is for West Pokot: County, Sub county then division, then location, sub location then village). .................................................... 10 Figure 2: Algorithm for a three-class simplified LQAS classifier ........................................................................... 12 Figure 3: Map of OTP point coverage by sub-county ................................................................................................. 14 Figure 4: Map of SFP point coverage by sub-county .................................................................................................. 15 Figure 5: Reasons for not attending OTP in North Pokot ......................................................................................... 18 Figure 6: Reasons for not attending SFP in North Pokot .......................................................................................... 19 Figure 7: Reasons for not attending OTP in Central Pokot ...................................................................................... 19 Figure 8: Reasons for not attending SFP in Central Pokot ....................................................................................... 20 Figure 9: Reasons for not attending OTP in West Pokot ........................................................................................... 21 Figure 10: Reasons for not attending SFP in West Pokot ......................................................................................... 21 Figure 11: Reasons for not attending OTP in South Pokot ....................................................................................... 22 Figure 12: Reasons for not attending SFP in South Pokot ........................................................................................ 22 Figure 13: Map of OTP period coverage classification by sub-county ................................................................. 36 Figure 14: Map of SFP period coverage classification by sub-county .................................................................. 37 TABLES Table 1: Sample sizes and number of villages sampled .............................................................................................. 10 Table 2: Sampling interval per sub-county ................................................................................................................. 11 Table 3: West Pokot survey data per sub-county ....................................................................................................... 13 Table 4: OTP coverage classification results ............................................................................................................... 13 Table 5: SFP coverage classification results ................................................................................................................ 15 Table 6: Weighting analysis .......................................................................................................................................... 16 Table 10: STATUS OF COVERAGE (June 2012) ASSESSMENT RECOMMENDATIONS AS OF MAY 2013 ............... 24 Table 11: Issues affecting programme coverage and the recommendations on how each could be addressed obtained from the SLEAC .............................................................................................................................................. 29 Table 12: OTP period coverage classification ............................................................................................................. 35 Table 13: Overall SAM Period coverage estimate ....................................................................................................... 35 Table 14: SFP period coverage classification .............................................................................................................. 36 Table 15: Overall MAM Period coverage estimate ......................................................................................................... 37
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CONTENTS
ACKNOWLEDGEMENTS ............................................................................................................................................................ 1
ACRONYMS .................................................................................................................................................................................... 3
EXECUTIVE SUMMARY ............................................................................................................................................................. 4
LIST OF FIGURES AND TABLES ............................................................................................................................................. 6
CONTENTS ..................................................................................................................................................................................... 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 .............................................................................................. 11 2.4 COVERAGE ESTIMATORS .......................................................................................................................................... 12
3. RESULTS .............................................................................................................................................................................. 13
3.1 BARRIERS TO SERVICE UPTAKE AND ACCESS .................................................................................................. 18
4. CONCLUSION AND RECOMMENDATION ............................................................................................................... 23
ANNEX 1: WEST POKOT SLEAC TRAINING PARTICIPANT LIST ........................................................................... 31
ANNEX 2: WEST POKOT SLEAC TRAINING SCHEDULE ............................................................................................ 32
ANNEX 3: LIST OF SAMPLED VILLAGES FOR THE SLEAC WIDE AREA SURVEY ............................................ 33
ANNEX 4: PERIOD COVERAGE CLASSIFICATION AND MAPPING ........................................................................ 35
ANNEX 5: QUESTIONNAIRE FOR CARERS OF SAM AND MAM CASES NOT IN THE PROGRAM ................ 38
ANNEX 6: WIDE AREA SURVEY TALLY SHEET ........................................................................................................... 39
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1. INTRODUCTION In September 2011, Action Against Hunger (ACF) began supporting the Ministry of Health-led Integrated Management of Acute Malnutrition (IMAM) programme in West Pokot County. ACF moved in to bridge the gap created by the departure of the main nutrition partner Samaritan’s Purse International that phased out from the area in May 2011. At that time, malnutrition rates were at alert levels of 14.9% and 2.3% for GAM and SAM respectively2
In June 2012, a Semi Quantitative Evaluation of Access and Coverage (SQUEAC) investigation of the West Pokot IMAM programme showed point programme coverage to be 33.5% (95% CI: 24.0% - 44.8%)
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3 for Out-patient Therapeutic Programme (OTP) across the whole county. A year after, a follow-up coverage survey was planned to assess the progress of the programme with regards to coverage. At this point, the programme requirements in terms of coverage assessment had changed significantly. These were partly a result of the change in the administrative structure of Kenya whereby counties have been divided into new structures called sub-counties and of the greater autonomy provided to the counties to manage and control their affairs, including health and nutrition programmes4,5
1. To map coverage for both OTP and Supplementary Feeding Programme (SFP) components and at sub-county level.
. These changes therefore required a method that provides coverage results not only at the county level but more importantly at the sub-county level. Initial discussions between Valid International and ACF through the Coverage Monitoring Network (CMN) explored the potential of using the Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) methodology for the present coverage assessment with the following objectives:
2. Provide an indication of coverage heterogeneity within the county.
3. Report an overall coverage estimate for the whole county.
Conducting a SLEAC in each of the four sub-counties was deemed by all parties as the most appropriate method given the current programmatic context. In addition, MAM coverage was included in order to have baseline information as this has never been assessed before.
The current assignment was conducted with the participation of ACF staff, Ministry of Health and other partners such as Food for the Hungry International, Kenya, Mercy USA, International Medical Corps, World Vision, and UNICEF. This report describes the process and presents the results of the SLEAC survey national training conducted in the West Pokot IMAM programme from 28th June to 18th July 2013. The first five days were dedicated to theoretical aspects, focusing on an overview of the West Pokot IMAM programme, as well as an overview of SQUEAC and SLEAC processes with the core team of 23 participants (Annex 1). In addition, enumerators were recruited to support the actual
2 ACF, West Pokot County- SQUEAC Investigation Report, June, 2012. 3 ibid 4 A. O. Omari, S. N. Kaburi, and T. Sewe, Change Dilemma: A Case of Structural Adjustment through Devolution in Kenya, 2010 (unpublished) 5 Government of Kenya, The new Constitution of Kenya, Government Printers 2010.
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survey process and were trained on the case-finding method to be used for the survey. Soon after the training, the actual SLEAC survey for the entire West Pokot county started and went on between 4th and 17th July 2013 (Annex 2).
2. METHODOLOGY SLEAC is a rapid and low-resource survey method that classifies (e.g. low, moderate or high) coverage at the service delivery unit (SDU) level. The sub-counties were selected as units of classification because service delivery is managed at sub-county level. SLEAC requires small sample sizes (e.g. n ≤ 40) to make reliable classifications per SDU6
2.1 SLEAC PRIMARY SAMPLING UNITS (PSUS)
. SLEAC can also estimate coverage over several service delivery units, hence ideal for assessing the overall coverage across the different sub-counties of West Pokot County.
SLEAC primary sampling units (PSUs) are the most basic administrative units within a sub-county from which the target population is to be sampled. For this survey, the villages across West Pokot County were the PSUs.
2.2 SLEAC SURVEY SAMPLE DESIGN First sampling stage method: In a first sampling stage, PSUs (villages) to be surveyed in each of the sub-counties of West Pokot County were randomly selected using systematic sampling from a complete list of villages per sub-county stratified by administrative units such as locations or sub-locations (see Figure 1). Sample size: The target number of villages to be sampled for SLEAC in each sub-county was determined using an LQAS sampling calculator (available at http://www.brixtonhealth.com/hyperLQAS.html). Based on the minimum sample size requirement, the appropriate number of villages to sample was estimated using the following formula:
𝑛𝑣𝑖𝑙𝑙𝑎𝑔𝑒𝑠 = 𝑇𝑎𝑟𝑔𝑒𝑡 𝑠𝑎𝑚𝑝𝑙𝑒 𝑠𝑖𝑧𝑒
𝐴𝑣𝑒𝑟𝑒𝑔𝑒 𝑣𝑖𝑙𝑙𝑎𝑔𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝐴𝑙𝑙 𝑎𝑔𝑒𝑠 × . . % 𝑢𝑛𝑑𝑒𝑟 5 × 𝑆𝐴𝑀 𝑝𝑟𝑒𝑣𝑎𝑙𝑒𝑛𝑐𝑒
The number of villages to be sampled by sub-county was calculated using this formula and based on the parameters listed in Table 1. Villages in each sub-county were grouped according to their sub-location. Selection of villages to sample was done by systematically selecting villages from this stratified list beginning with the village found on a randomly determined starting position on the list (generated by ENA for SMART software). Subsequent villages were then selected based on a constant sampling interval until the required number of villages to sample was reached. Details of the sampled villages are included in Annex 3 of this report. Important to note is that all villages were included in the sampling frame, except for those with known security issues emanating from ethnic clashes. 6 Myatt M, et al, (2012), Semi-Quantitative Evaluation of Access and Coverage (SQUEAC)/ Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC), FANTA III/FHI360, Technical Reference. Available at: http://www.fantaproject.org/downloads/pdfs/SQUEAC-SLEAC-Technical-Reference-Oct2012.pdf
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Figure 1: Administrative structure of West Pokot County used for sampling (that is for West Pokot: County, Sub county then division, then location, sub location then village). Table 1: Sample sizes and number of villages sampled
Sub-county
Estimated total population
(3% Population
increase projection)7
Average village
population
% under 5
SAM prevalence
Target sample size
(n) nvillages
North Pokot 122,108 354 19.2 1% 35 51 Central Pokot 100,554 397 19.2 1% 33 43 South Pokot 164,034 374 19.2 1% 37 52 West Pokot 175,178 375 19.2 1% 37 51 Sampling interval: The sampling interval for the systematic sampling of villages was determined by dividing the total number of villages in each sub-county by the number of villages needing to be sampled as per calculations above. The sampling intervals used for the systematic sampling in each of the sub-counties are in Table 2.
7 Kenya National Bureau of Statistics Office. 2009 population census projections for population size and number of villages
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Table 2: Sampling interval per sub-county
Sub-county Total number of villages
Number of villages
sampled per sub-county
Sampling interval Total number of villages in the sub−county
Total number of sampled villages
North Pokot 345 51 6 Central Pokot 253 43 5 South Pokot 439 52 8 West Pokot 467 51 9
Second stage sampling method: This method is usually either an active and adaptive case finding method or a house-to-house screening. It involves active and adaptive case finding in which all or near all malnourished children are searched for or measured using MUAC tape (in addition to identification of bilateral pitting oedema). For the West Pokot SLEAC, house-to-house method was applied and used exclusively since the survey also aimed at finding MAM cases which are usually detected by screening all children. Having completed the first stage sampling in which villages were selected, the team was divided into 14 teams comprising one core team member who was the team leader and an enumerator. Each team visited one village per day. Once the team arrived in the villages, a village elder was identified to work with the team as a village guide. Upon completion of this wide area survey the team met centrally to collate the information.
2.3 COVERAGE STANDARDS AND DECISION RULES In order to classify coverage, standard thresholds classifications were set by the survey core team. After several discussions among the core team members, and based on the experience of the programme staff (MoH and ACF) and their knowledge of the programme it was deemed that programme coverage would not exceed 50%. This was also in line with the SPHERE standards for measuring coverage of rural therapeutic feeding programmes. The following coverage standards were eventually decided as most appropriate:
• Low coverage: 20% or less • Moderate: greater than 20% up to 50% • High coverage: above 50%
These standards were used to create decision rules using the following rule-of-the thumb formula:
𝒅 𝟏 = ⌊ 𝑛 × 𝑝1 ⌋ = � 𝑛 ×20
100 � = �
𝑛5
� 𝑎𝑛𝑑 𝒅𝟐 = ⌊ 𝑛 × 𝑝2 ⌋ = � 𝑛 ×50
100 � = �
𝑛2
�
These decision rules were used to classify coverage in each of the four sub-counties where n is the sample size achieved by the survey, p1 the lower threshold (20%) and p2 is the upper threshold (50%). A threshold value (𝑑) is established to determine the number of cases that need to be covered in order for coverage to be satisfactory. If the number of covered cases exceeds the threshold value then
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coverage is classified as being satisfactory. If the number of covered cases found does not exceed the threshold value then the coverage is classified as being unsatisfactory.
Figure 2: Algorithm for a three-tier simplified LQAS classifier
2.4 COVERAGE ESTIMATORS Two coverage estimators are normally used in therapeutic feeding programmes: point and period. Point coverage is used to provide a snapshot of programme performance at the time of the current survey and has a strong emphasis on the coverage and timeliness of case-finding and recruitment The following formula is used to calculate point coverage:
𝑃𝑜𝑖𝑛𝑡 𝐶𝑜𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑖𝑛 𝑝𝑟𝑜𝑔𝑟𝑎𝑚𝑚𝑒 (𝑐)
𝑇𝑜𝑡𝑎𝑙 𝑐𝑎𝑠𝑒𝑠 𝑓𝑜𝑢𝑛𝑑 (𝑛)
Period coverage includes recovering cases. These are children that should be in the program because they have not yet met program discharge criteria. It is calculated as:
𝑃𝑒𝑟𝑖𝑜𝑑 𝐶𝑜𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑖𝑛 𝑝𝑟𝑜𝑔𝑟𝑎𝑚𝑚𝑒 + 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑖𝑛𝑔 𝑐𝑎𝑠𝑒𝑠(𝑐)
𝑇𝑜𝑡𝑎𝑙 𝑐𝑎𝑠𝑒𝑠 𝑓𝑜𝑢𝑛𝑑 + 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑖𝑛𝑔 𝑐𝑎𝑠𝑒𝑠 (𝑛)
The choice as to which coverage estimator to use requires careful consideration because either of the two can give misleading coverage results depending on the quality of service delivery and implementation. To illustrate this notion, the point coverage estimator can potentially classify a programme even with good active case-finding, timely recruitment and short lengths of stay as having a low coverage. The period coverage estimator can classify a programme with poor or no active case finding and recruitment and long lengths of stay due to late presentation and /or late admission as
Sample Number of
Covered cases
exceeds d2?
Number of
Covered cases
exceeds d1?
Classify as low
Classify
as high
Classify
as moderate
NO NO
YES YES
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having high coverage. Two guiding principles have been recommended for the choice of coverage estimator to report based on context of the programme8
1. If there is good active case-finding and recruitment (i.e. SAM cases found early in the stage of the disease) and short lengths of stay then the period coverage estimator is appropriate.
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2. If there is poor or no active case-finding and recruitment (i.e. SAM cases found late in the stage of the disease) and long lengths of stay due to late presentation and / or late admission then it is appropriate to use the point coverage estimator.
The West Pokot County IMAM programme currently faces issues of weak community mobilisation. There is no active case-finding and recruitment in all the four sub-counties due to very few Community Health Workers (CHWs) trained per OTP/SFP site. This translates to CHWs working mostly at the health facility rather than in the communities finding cases. It was therefore agreed that point coverage is the most appropriate estimator to use for reporting about the programme coverage.
3. RESULTS Table 3 summarises the data for the wide area survey and Tables 4 and 5 show point coverage classification for OTP and SFP respectively, in each sub-county. Figures 3 and 4 map coverage classification for OTP and SFP respectively.
Table 3: West Pokot survey data per sub-county
Sub County SAM cases found
SAM cases in OTP
In OTP recovering
MAM Cases found
MAM Cases in SFP
In SFP Recovering
North Pokot 19 5 5 63 8 22 Central Pokot 38 6 10 108 16 16 West Pokot 20 4 2 77 7 10 South Pokot 21 5 1 85 5 7 County Total 98 20 18 333 36 55
Table 4: OTP coverage classification results
Sub County
SAM cases found
(n)
SAM cases
in OTP (c)
Decision rule (d1)
Is c > d1?
Decision rule (d2)
Is c > d2? Coverage Classification
North 19 5 3 Yes 9 No Moderate Central 38 6 7 No 19 No Low West 20 4 4 No 10 No Low South 21 5 4 Yes 10 No Moderate County 98 20 19 Yes 49 No Moderate
8 Guevarra, E. Norris, A. Guerrero, S. and Myatt, M. (2012) Assessment of Coverage of Community-based Management of Acute Malnutrition. CMAM FORUM Technical Brief 1
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For clarification on the interpretation of the coverage classification results shown in Table 4, for instance in North Pokot: d1 = 19/5 =3.8 (as per formula above), with c = 5 SAM covered, hence, c > d1 d2=19/2 = 9.5 (as per formula above), with c = 5 SAM covered, hence c < d2
therefore c is above 20% and below 50%, thus coverage is moderate.
Figure 3: Map of OTP point coverage by sub-county
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Table 5: SFP coverage classification results
Sub County
MAM Cases found
(n)
MAM Cases in SFP
(c)
Decision rule (d1)
Is c > d1? Decision
rule (d2)
Is c > d2? Coverage
Classification
North 63 8 12 No 31 No Low Central 108 16 21 No 54 No Low West 77 7 15 No 38 No Low South 85 5 17 No 42 No Low County 333 36 66 No 166 No Low
Figure 4: Map of SFP point coverage by sub-county
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None of the four sub-counties achieved high coverage classification. The point coverage for SAM was moderate in North Pokot and South Pokot whilst low in West Pokot and Central Pokot. The overall county point coverage classification was moderate. MAM point coverage classification was found to be low across all the four sub-counties and the county coverage classification was also low.
Period coverage classification was also done during the analysis with the core team and has been included in this report (Annex 4) not for reporting purposes but is meant to be for future reference for the training participants.
Overall coverage estimates County-level coverage estimates were calculated using a posterior weighting approach using the number of cases estimated in each surveyed service delivery unit divided by the total number of cases across all service delivery units based on the method described in Myatt et al, 2012 as shown in table 6.
Table 6: Weighting analysis
Sub County Population % of 6-59 months
SAM Prevalence
N W=N/∑N
North Pokot 122108 19.2% 1% 234 234/1077=0.22
Central Pokot
100554 19.2% 1% 193 193/1077=0.18
West Pokot 175178 19.2% 1% 336 336/1077=0.31
South Pokot 164034 19.2% 1% 314 314/1077=0.29
Total 19.2% 1% 1077 1.00
N =⌊ population of service delivery unit all ages ×percentage of population6 -59months × SAM Prevalence ȷ 100 100 The overall OTP point coverage estimate (Tables 7&8) was 21.7% (95% CI: 12.7% - 30.7%) and the overall SFP point coverage estimate was 10.0% (95% CI: 6.7% - 13.3%).
Chi-square test was performed to check whether coverage across sub-counties was patchy. The value of the chi-square test statistic obtained was 0.84, and when compared to the critical value 7.81 (for four surveys), it was less than critical value thus the coverage was not patchy (Table 9).
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Table 7: Overall SAM Point coverage estimate
Population Data
Total expected
SAM Weight Sample Cases
IN Coverage
proportion Weighted coverage
Sub-county Population % 6 - 59
months SAM
prevalence N w N c c / n w * c / n
North Pokot 122108 19.2% 1% 234 0.22 19 5 0.26 0.0572 Central Pokot 100554 19.2% 1% 193 0.18 38 6 0.16 0.0283 West Pokot 175178 19.2% 1% 336 0.31 20 4 0.20 0.0624 South Pokot 164034 19.2% 1% 314 0.29 21 5 0.24 0.0694 Total - 19.2% 1% 1077 1.00 98 20 - 0.2173
Table 8: Overall MAM Point coverage estimate
Population Data Expected
MAM Weight Sample Cases
IN Coverage
proportion Weighted coverage
Sub-county Population % 6 - 59 months
MAM prevalence N w n c c / n w * c / n
North Pokot 122108 19.2% 3% 703 0.22 63 8 0.13 0.0276 Central Pokot 100554 19.2% 3% 579 0.18 108 16 0.15 0.0265 West Pokot 175178 19.2% 3% 1009 0.31 77 7 0.09 0.0284 South Pokot 164034 19.2% 3% 944 0.29 85 5 0.06 0.0172 Total - 19.2% 3% 3235 1 333 36 - 0.0996
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Table 9: Chi- square test analysis
Sub County
Sample size O * E ** (0 − E )2**
(0 − 𝐸 )2𝐸
North Pokot 19 5 19× 20
98 = 3.88 (5 − 3.88)2 =1.26
1.263.88
=0.32 Central Pokot 38 6 38 × 20
98= 7.76 (6 − 7.66)2= 2.7
2.77.76
=0.40
West Pokot 20 4 20 × 2098
=4.08 (4 − 4.08)2 = 0.01 0.014.08
= 0.00 South Pokot 21 5 21 × 20
98=4.28 (5 − 4.28)2 = 0.52 0.52
4.28 = 0.12
SUM 98 20*** 20*** 𝒙𝟐 =0.84 * The number of covered cases observed in each survey ** The number of covered cases expected in each survey if coverage is not patchy *** These columns should have the same total
3.1 BARRIERS TO SERVICE UPTAKE AND ACCESS The survey data compiled from questionnaires (Annex 3) administered to carers of both SAM and MAM cases not covered by the programme identified different barriers to access to the current West Pokot IMAM programme. These barriers varied from sub-county to sub-county as shown in Figures 5 to 11.
In North Pokot, the two major barriers identified were previous rejection for MAM cases (access to SFP, Figure 6), and lack of programme understanding/awareness for SAM cases (access to OTP, Figure 5).
Figure 5: Reasons for not attending OTP in North Pokot
0 5 10 15 20 25 30 35 40 45
Lack of knowledge about programme Previous rejection
Carer cannot travel with more than one child No time/too busy
Site too far Lack of Knowledge about SAM
Discharged cured Defaulted
Proportion of cases not covered
Reasons for not attending OTP in North Pokot
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Figure 6: Reasons for not attending SFP in North Pokot
Previous rejection was the main reason why carers were not attending SFP in North Pokot. Indeed, rejection happened during mass screening during which carers of children not malnourished at the time of screening felt that their children were rejected.
In Central Pokot, the main barrier to access to both OTP and SFP was lack of programme awareness by carers of SAM and MAM cases (Figures 7&8).
Figure 7: Reasons for not attending OTP in Central Pokot
0 5 10 15 20 25
Previous rejection Defaulter
Site too far No time/too busy
Cannot recognize condition as manutrition Rumours of RUTF/RUSF stockouts
Discharged cured Discharged not cured
Proportion of cases not covered
Reasons for not attending SFP in North Pokot
0 5 10 15 20 25 30 35 40
Carer not aware of the program Defaulter
Cannot recognize condition as malnoutrtion Site too far
No screening was done at the site No time/too busy
Previous rejection
Proportion of children not covered
Reasons for not attending OTP in Central Pokot
20
Figure 8: Reasons for not attending SFP in Central Pokot
In West Pokot, lack of programme awareness and failure to recognize malnutrition signs and symptoms were the main reason for failure to attend both OTP and SFPs (Figures 9&10).
0 5 10 15 20 25
Carer not aware of the program Condition not recognised as malnutrition
site too far Defaulted
No time/too busy Discharged as cured
Previous rejection Discharged not cured
No screening was done at the site Carer caanot travel with more than one child
RUTF/RUSF causes diarrhea Rumours of RUTF/RUSF stockouts
Proportion of cases not covered
Reasons for not attending SFP Central Pokot
21
Figure 9: Reasons for not attending OTP in West Pokot
Figure 10: Reasons for not attending SFP in West Pokot
0 5 10 15 20 25
Carer not aware of the programme child not recognised as malnourished
Site too far Defaulted
No time/too busy Discharged cured
Previous rejection Discharged not cured
No screening done at site Carer cannot travel with more than one child
RUTF/RUSF casues diarhea Rumours of RUTF/RUSF stockouts
Proportion of cases not covered
Reasons for not attending OTP in West Pokot
0 10 20 30 40
Carer not aware of programme
Lack of Knowledge of SAM
No time/too busy
Never admitted due to stock outs
Previous rejection
Difficulty with child care
Defaulter
Site too far
Discharged cured
Proportion of cases not covered
Reasons for not attending SFP in West Pokot
22
Figure 11: Reasons for not attending OTP in South Pokot
In South Pokot, the main barriers to SAM treatment were defaulting and lack of knowledge about malnutrition (Figure 11),;lack of programme awareness was the main barrier to MAM treatment (Figure 12). Carers in South Pokot also listed programme site being too far and high defaulter rate as the main reasons for not attending SFP.
Figure 12: Reasons for not attending SFP in South Pokot
0 5 10 15 20 25
Defaulter Lack of knowledge of SAM
Lack of OTP programme awareness Site too far
Discharged cured Discharged not cured
Carer cannot travel with more than one child Favouritsm/ discrimination at the site
Child teething so no need for treatment
Proportion of cases not covered
Reasons for not attending OTP in South Pokot
0 5 10 15 20 25 30 35
Site too far Defaulter
Discharged cured Previous rejection
RUTF/RUSF associated with HIV/AIDS No time/too busy
RUTF/RUSF stockouts Difficulty with child care
Child never screened at site Carer cannot travel with more than one child
Proportion of cases not covered
Reasons for not attending SFP in South Pokot
23
4. CONCLUSION AND RECOMMENDATION As previously discussed, point coverage for both OTP and SFP component of the IMAM programme in all the four sub-counties did not reach a high coverage classification. The point coverage for SAM treatment was moderate in North Pokot and South Pokot whilst low in West Pokot and Central Pokot. The overall county point coverage classification for OTP was moderate. SFP point coverage classification was found to be low across all the four sub-counties translating into a low coverage classification for MAM treatment for the whole county.
The majority of barriers to access to treatment identified during the current SLEAC survey point to the weak community mobilisation component of the IMAM programme in West Pokot County. This therefore means that the programme should invest adequate resources (time, financial and human) into community-based activities to promote programme understanding and adherence to treatment regimens.
Tables 10 and 11 point out the status of recommendations put forth during the SQUEAC investigation in June 2012 and the current recommendations based on the SLEAC assessment in July 2013 respectively.
24
Table 7: STATUS OF COVERAGE (June 2012) ASSESSMENT RECOMMENDATIONS AS OF MAY 2013
ISSUES( SQUEAC, June 2013) RECCOMENDATIONS(SQUEAC 2012)
WHAT HAS BEEN DONE ANY COMMENTS/ WAY FORWARD
Vastness of the county that limits access to various parts due to heavy rains and at times insecurity
The staff capacity in West Pokot County at the moment is stretched. This should be increased while maximizing on available community units through advocacy
ACF Staff capacity was increased by 2 HINI officers in February 2013. Increased numbers of outreaches from 10 outreaches to 13 outreaches in October 2012. Provision of commodities using the Distribution Plan to ensure that facilities don’t run out of supplies. Sensitization of the community units has been conducted through of CHWS on IMAM.
The CHWS attached to the community units should be sensitized more on IYCN and IMAM. There should be monthly meetings for CHW’s in the units to get feedback on ongoing activities, challenges addressing any gaps.
Poor documentation, for example, lack of exit details, no physical address to enhance follow up in case of defaulters
Strengthen the on job training on appropriate and proper documentation while increasing awareness of health information management.
The on-going OJT and joint supervision has strengthened the documentation at the health facilities. Training has been done to 57 health managers on TOT to get more involvement through monitoring of facilities during OJT. Monthly support provided for in-charges’ meeting which is used as an avenue of feedback Review meeting on HINI indicators with all the TOT to assess coverage , reporting indicators was conducted. Continuous medical education has been
Continue to mentor and undertake OJT sessions on program documentation. Strengthen action plan and follow-up on joint OJT. The facility in-charges meeting should be strengthened, training of the DHMT on DHIS; CME’s and focused trainings to capacity build health workers.
performed. Action plans at the facility level on documentation were created and are in place. Joint work plan was formulated with MoH and partners.
ISSUES( SQUEAC, June 2013) RECCOMENDATIONS(SQUEAC 2012)
WHAT HAS BEEN DONE ANY COMMENTS/ WAY FORWARD
Lack of representativeness was cited in the recruitment of CHW’s posing a challenge in reporting as some CHW’s are working where there are no community units.
There is routine support supervision undertaken by the various stakeholders. This should be supported by documentation of findings and areas for follow up at both facility and regional offices for close follow up of measures that have been put in place Involvement of provincial administration in CHW recruitment so as to appropriately link them to community units.
There has been involvement and follow up by the community strategy persons in selection of the CHWs as they have to come from the community units.
There is need for mapping and creation of functional community units in every location. Strengthen the linkages between the community and health facility. More support in training of the CHW’s from the units on full community package on IMAM and IYCN.
Lack of training and roll out of the WHO.CHANIS and shortage of Mother to child booklet.
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 and the production of mother child booklets.
ACF assisted in the printing of the summary of the CHANIS and distributed it in most facilities. However the facilities lacked the tally sheet for the CHANIS. This still remains as a challenge due to inadequate or less distribution of the WHO CHANIS and mother to child booklet in most facilities across the County.
Strengthen Joint OJT on the use of CHANIS, Partners to support the printing of the CHANIS and advocate for the availability of the MCH booklets at the County and national level. Currently, there is an ongoing distribution from national level, hence the DNO should be able to place an order for the MCH booklets. There is need to liaise with the MOMS and MOPHS departments to ensure that CME/OJT are conducted during monthly in-charges meeting, addressing the knowledge gaps in updating growth charts. The DHMT, through the district in-charges meeting and CNTF should roll out the new CHANIS tools so as to conform the MCH booklet and WHO growth standards.
ISSUES( SQUEAC, June 2013) RECCOMENDATIONS(SQUEAC 2012)
WHAT HAS BEEN DONE ANY COMMENTS/ WAY FORWARD
Increased distance to health facilities/ centres with no IMAM integration in existing outreach sites
Integrate IMAM into existing outreach sites and increase numbers/coverage of these based on needs Full financial support needs to be accorded to outreach sites as the
Increased numbers of outreaches from 10 outreaches to 13 in October 2012. Integrated outreaches is on-going in places where the health facilities are distant.
Lobby for more integrated outreaches where health facilities are distant.
Ministry of Health is using Health Sector Strategic Funds.
ISSUES( SQUEAC, June 2013) RECCOMENDATIONS(SQUEAC 2012)
WHAT HAS BEEN DONE ANY COMMENTS/ WAY FORWARD
Poor anthropometric measurement quality, with a lot of digit preference and rounding off in the registers at the facility.
Have follow up sessions on the classroom trainings undertaken. Ensure that all facilities have appropriate and functional anthropometric equipment e.g. in Parua dispensary(has no IMAM services). The training package of CHWs in community units needs to incorporate a component of nutrition to enable CHWs in taking proper MUAC measurements, as well as understand screening and referral criteria.
The CHWs attached to the health centres have had a comprehensive training package of IMAM including various nutrition topics on screening, referral and active case finding in the trainings done. There has been sensitization workshop for the community health workers from the units on screening, identification and referral. There is ongoing joint OJT on how to take correct anthropometric measurements, emphasizing on precision and accuracy. The registers are also checked on a regular basis with corrections being addressed immediately. Most of the height boards in the facilities have errors.
Advocate for the replacement or repair of faulty height boards at County level. Strengthen OJT on anthropometric measurements. A more comprehensive package for both IMAM and IYCN is required for the CHWs from the Units.
Lack of awareness on what malnutrition is as well as on the targeted feeding programs and adequate IYCN practices.
Create and increase awareness on these issues through 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
Sensitization awareness has increased through formation of M.T.M.S.G and C.H.G from the community to improve on nutrition information IEC materials and banners have been circulated and tailored to fit the situation and being as friendly as possible mainly during calendar activities to include Malezi bora emphasising on nutrition and WASH
Formation of more MTMSG and CHG and strengthening the existing groups , targeting community component . Formation of FTFSG’s at the community level to support the mothers or caregivers on promotion of IYCN. Form linkages of MTMSG with relevant ministries to include MOA (Njaa Marufuku Kenya).MOW, NDMA, Micro-
were put off by the generic “scary” pictures of malnourished children.
information. Finance, Social services so as to promote formation of IGA’S hence sustainability. IEC material to be done in local language.
Table 8: Issues affecting programme coverage and the recommendations on how each could be addressed obtained from the SLEAC
Issues arising Recommendations Action Plan Process indicators Responsible Previous rejection from the programme
Ensure that rejected cases are handled carefully and are made to understand reasons for non-admission. Avoid central screening where even healthy children are asked to come for measurement.
More CHWs or other community volunteers should be identified and trained to assist with active case finding. Encourage the caregiver to take the child to the volunteer in their settlement for MUAC or oedema check or take the child to OTP/SFP every time they suspect that s/he is becoming malnourished.
Trainings for CHWs or other volunteers planned for and conducted
Program manager Program Staff MoH Managers/Officers OTP/SFP staff
Lack of Programme awareness
Advocacy meetings at all levels with all partners in nutrition and health programmes and community leaders such as chiefs, village elders, and religious leaders on programme awareness. Use of mass media especially local radio stations to raise programme awareness and improve community’s understanding/recognition of malnutrition.
Orientation of more people at community level including mother support groups, Traditional Birth Attendants, Reproductive Health Workers and teachers of Early Childhood and Development schools in sensitisation and active case finding activities
Identify context specific channels of communication and develop culturally appropriate messages.
Advocacy plan developed
Appropriate messages developed and disseminated
Program staff MoH OTP/SFP staff
Community leaders
Ad hoc screening for malnutrition in existing services
Ensure integration of screening for malnutrition in the existing routine services to ensure that there are no missed opportunities. Compile screening reports for malnutrition
Regular supervision to the health facilities and review of screening reports
Supervision checklists and reports reviewed and compiled
MoH
Programme staff
Issues arising Recommendations Action Plan Process indicators Responsible
Misconceptions around RUTF and stock outs
Involve a wide range of people and methods to disseminate programme information further with focus on the RUTF misconceptions. Ensure consistent supply of RUTF/RUSF
Initiate an advocacy component on the use of RUTF into the program by involving different key community figures. Explore the use of media i.e. community radio in disseminating programme information further especially on RUTF, dangers of defaulting, programme procedures and organisation etc. Consider using carers of children who have successfully been treated in the IMAM programme to clarify the importance of RUTF Have buffer stocks to avoid shortages
Advocacy meetings planned for and conducted Community radios identified and approached to discuss working modalities Role models identified and oriented
MoH Program manager/ Nutrition Coordinator Community leaders
Long distance and difficult terrain
The program needs to increase the number and frequency of outreach services and distribution days.
Advocate for support from government and other partners working in the County on this issue.
Advocacy meetings planned for and conducted
Programme Manager, MoH (DNO), UNICEF/ donors
In summary, it is important to acknowledge the vastness of the county and the difficulties with the terrain which should be factored in when planning various activities for the programme in West Pokot. Attention and technical support should be given to MoH staff in the health facilities who are involved in the daily programme activities. For example, the issue of children not being screened for malnutrition needs to be addressed as it a missed opportunity for case finding, which could be reinforced with training more people (i.e. CHWs, TBAs, any other existing community support groups etc.) at the community level in active case finding and community sensitisation. Irregular RUTF/RUSF supplies should be minimised because they directly and indirectly contribute to defaulting. It would also be ideal to conduct SQUEAC investigations to understand more of the identified barriers, which could be used to strengthen the programme.
31
Annex 1: West Pokot SLEAC Training participant list NAME AGENCY PHONE POSITION EMAIL 1. ANASTACIA
MALUKI MERCY
USA 0729 590179 Monitoring and evaluation
coordinator [email protected]
2. SUSAN LUBALO ACF 0705634461 Nutrition program manager –West Pokot
3. EMMY CHEPKWONY
ACF 0722984935 Asst. nutrition program manager-West Pokot
4. FAITH NZIOKA ACF 0724563103 Asst. FSNS program manager-Nairobi
5. KEVIN MUTEGI ACF 0725635303 FSNS officer-Nairobi [email protected]
6. NAHASHON KIPRUTO
ACF 0720325755 FSNS officer-West Pokot [email protected]
7. REBECCA WACHIRA
ACF 0726233003 FSNS officer-West Pokot [email protected]
8. ISAAC WACHIRA
ACF 0717304433 Nutrition program manager-Garbatulla
9. FRANCIS KYALO
FHK 0723950355 Monitoring and evaluation specialist
10. ELIZABETH CHEROP
UNICEF 0706100690 Nutrition support officer-West Pokot
11. LEAH CHELOBEI
MOH 0728088096 District nutrition officer-West Pokot (Job group K)
12. THOMAS CHIKCHIK
MOH 0720873761 Deputy district public health nurse-West Pokot(Job group L)
13. ISAAC OWAKA MOH 0725870089 Public health officer-West Pokot(Job group L)
14. JOSEPH LOCHAUN
MOH 0728361481 Public health officer –Central Pokot(Job group L)
15. THOMAS RUMON
MOH 0725622776 Community strategy focal point-South Pokot(Job group H)
16. SAMUEL BARGOTIO
MOH 0710155375 Clinical officer –North Pokot(Job group L)
17. LEAH NGARI IMC 0724739244 Nutritionist -Isiolo [email protected]
18. BETTY CHEYECH
ACF 0720134069 HiNi officer-West Pokot [email protected]
19. SCHOLASTICA MWONGELA
ACF 0725366643 HiNi officer-West Pokot [email protected]
20. JEDIDA NGUI ACF 0710459488 HiNi officer-West Pokot [email protected]
21. JACOB PKORIR ACF 0728838511 HiNi officer-West Pokot [email protected]
22. BERNARD Muriuki
World Vision
0724480659 Nutrition officer-Kitui [email protected]
23. EMMANUEL MANDALAZI
VI 0703568961 CMN Consultant [email protected]
24. IMELDA AWINO ACF 0728866161 FSNS Programme Manager [email protected]
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ANNEX 2: West Pokot SLEAC Training Schedule Date Activity 27th June 2013 Arrival in Nairobi
Meeting with ACF Kenya National team 28thJune 2013 Travel from Nairobi to West Pokot 29th June 2013 Central Meeting with Core team for orientation: Overview of West
Pokot IMAM Programme/introduction to SQUEAC and SLEAC 30th June 2013 SLEAC: Coverage classification 1st July 2013 Central Meeting with Core team.
Estimating Coverage over Wide Areas 2nd July 2013 Central Meeting with Core team SLEAC orientation (whole day)
mapping and sampling for West Pokot County IMAM programme- 3rd July 2013 Central Meeting with Core team Planning for the Wide Area Surveys and
forming teams, plan movements and logistics 4th July 2013 SLEAC Wide Area Survey 5th July 2013 SLEAC Wide Area Survey 6th July 2013 SLEAC Wide Area Survey 7th July 2013 SLEAC Wide Area Survey 8th July 2013 SLEAC Wide Area Survey 9th July 2013 SLEAC Wide Area Survey 10th July 2013 SLEAC Wide Area Survey 11th July 2013 SLEAC Wide Area Survey 12th July 2013 SLEAC Wide Area Survey 13th July 2013 SLEAC Wide Area Survey 14th July 2013 SLEAC Wide Area Survey 15th July 2013 SLEAC Wide Area Survey 16th July 2013 SLEAC Wide Area Survey 17th July 2013 Central Meeting with Core team: Review of findings and data analysis
Completion of SLEAC Wide Area Survey in remaining villages in West Pokot Sub-county by enumerators
18th July 2013 Completing data entry and travel from West Pokot to Nairobi 19th July 2013 Review of data and on-going analysis 20th July 2013 AM: Debriefing with Imelda and Joy in Nairobi
PM: Departure from Nairobi
33
ANNEX 3: List of sampled villages for the SLEAC Wide Area survey
North Pokot Sub-County Central Pokot Sub-County
South Pokot Sub-County West Pokot Sub-County
No Village Villages Villages Village 1. Lowayaten Emlo Aron Kolit 2 Napodo Saka Cheptero Lastkowo 3 Kapunetan Kalaas Tachit Akimulitin 4 Lokitelawoyan Chemorkos Tukumo Kayap 5 Oyokol Onoch Tongenyo Lemu 6 Mekuyo Tortoi Kopombo Kiwanja Ndege 7 Cheporo/Lopedot Kamoiben Karsina Nateleng 8 Karorok Ptalam Chepareria South Rotekech 9 Kamokos Mell Kasongwor(B) Tartar 10 Kamila'a' Empoghat Simat Kalokiru 11 Kiwawa'b' Kadow Chepkit Arol 12 Kakou Sengelel Kapyamat Kakoghun 13 Adapale Pkutung Kaptarin Sees 14 Tirken Chemusar Cheseto Sirkol 15 Katuwot Sotin Emposos Motuput 16 Losidok Pkaliny Msiywon Cheptosok 17 Lopok Pkyot Achawa Tapamasian 18 Bendera Kasamogh Sosurwo Tukumon 19 Chepirporko Chemtwo Cherelio Kalanga 20 Kalia Roso Mokoyon Kaibos(B) 21 Printa Kosholoi Chesoromia Tuiyopei 22 Lokilelian Kaghpoch Chekutwen Kapchila 23 Lulunga Chepemo Koitongugh Kamariny(A) 24 Lomada Sopol Chemaltin Mutelo 25 Kongotunyor Kapkogh Cheposat Apipin 26 Atulia Kamariach Sukot Cereals(V) 27 Aparipar Chekoghin Cheptuiyis Tangi Moja(Iii) 28 Tiyinei Chemuro Koghmu Hospital Quarters 29 Kapilakin Akiriamet'c' Kamos Sepulion, Kilimajaro(I) 30 Sput-Put Nauyakwan Chepnoyon Kalan 31 Chemakeu Molos Morian Bondeni(Viii) 32 Kororon Kaitapos Kamol Sunflower(A) 33 Narochichi Kasaka Kedukak Kaplelach Koror 34 Orowo Chesito Kalopot Sakwa(Ii) 35 Kampi-Ndege Mokowa Chemoywo Cherelio 36 Longorkan Saksurot Pirimotoy Rorok 37 Nasikiria Runo Ghatiaril Kapkeno Tea Centre 38 Loushenikou Sisit Katiarsoyen Ompolion 39 Asilong Chekukui Mtia Loputuk 40 Chemoror Rena Parayon Kantpodin 41 Kasaka Chepar Cheptupoon Kariwo 42 Takar Titiot Kaporor Kapriwok 43 Kapyomot Kasasiran Chepukat Lopen 44 Kotulpogh Kamulogon Kaptukugh Sees"A" 45 Aporomoi Kachemungu Remaa Kedingan 46 Empowatu Kacherobei Kapoyotwo Morchichi 47 Chemasis Kaperur Simaton 48 Murkorio Tondwo Katukumwok 49 Churum Ptarakon Cheripporko 50 Tinyar Parayon Kakoron 51 Nakwapugha Lulwoi Kapetekenei
34
52 Kompasis Adado 53 Sinjo `a` 54 Tengar
35
ANNEX 4: Period coverage classification and mapping
Period coverage: all the four sub-counties achieved moderate coverage for SAM and the overall coverage classification for the whole county was moderate. For MAM, North Pokot and Central Pokot reached moderate period coverage whilst West Pokot and South Pokot was low. The overall period coverage classification for the county was moderate.
Table 9: OTP period coverage classification
Sub County
SAM cases in OTP and rec
(c)
SAM cases and rec
(n)
Decision rule (d1)
Is c > d1 Decision rule (d2)
Is c > d2?
Coverage Classification
North 10 24 4 Yes 12 No Moderate Central 16 48 9 Yes 24 No Moderate
West 6 22 4 Yes 11 No Moderate
South 6 22 4 Yes 11 No Moderate
County 38 116 23 Yes 58 No Moderate
Overall OTP period coverage estimate – 31.5% (95% CI: 22.2% - 40.8%). The Chi-square test showed period coverage to be homogenous.
Table 10: Overall SAM Period coverage estimate
Total expected
SAM
Weight Sample Cases IN
Coverage proportion
Weighted coverage
Sub-county Population % 6 - 59 months
SAM prevalence
N w n c
c / n w * c / nNorth Pokot 122108 19% 1% 234 0.22 24 10 0.42 0.0905Central Pokot 100554 19% 1% 193 0.18 48 16 0.33 0.0597West Pokot 175178 19% 1% 336 0.31 22 6 0.27 0.0851South Pokot 164034 19% 1% 314 0.29 22 6 0.27 0.0795Total - 19% 1% 1077 1 116 38 - 0.3149
Population Data
36
Figure 13: Map of OTP period coverage classification by sub-county
Table 11: SFP period coverage classification
Sub County
MAM cases in SFP and rec (c)
MAM cases and rec (n)
Decision rule (d1)
Is c > d1?
Decision rule (d2)
Is c > d2?
Coverage Classification
North 30 85 17 Yes 42 No Moderate
Central 32 124 24 Yes 62 No Moderate
West 17 87 19 No 48 No Low
South 12 92 18 No 49 No Low
County 91 388 77 Yes 194 No Moderate
Overall SFP period coverage estimate – 22.2% (95% CI: 18.0% - 26.4%). The Chi-square test showed period coverage to be heterogeneous.
37
Table 12: Overall MAM Period coverage estimate
Figure 14: Map of SFP period coverage classification by sub-county
Population Data
Total expected MAM Weight Sample
Cases IN
Coverage proportion
Weighted coverage
Sub-county Population
% 6 - 59 months
MAM prevalence N w n c c / n w * c / n
North Pokot 122108 19% 3% 703 0.22 85 30 0.35 0.0767Central Pokot 100554 19% 3% 579 0.18 124 32 0.26 0.0462West Pokot 175178 19% 3% 1009 0.31 87 17 0.2 0.0609South Pokot 164034 19% 3% 944 0.29 92 12 0.13 0.0381Total - 19% 3% 3235 1 388 91 - 0.2219
ANNEX 5: 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___________________________________________
39
ANNEX 6: Wide Area Survey Tally sheet Sub-county:______________Village:______________________ Team:_______Date:_____________
# OF SAM CASES FOUND (MUAC ≤11.4/oedema)
SAM CASES IN OTP (MUAC ≤11.4/oedema)
IN OTP PROGRAMME BUT RECOVERED (MUAC ≥ 𝟏𝟏.𝟓𝒄𝒎 or no oedema)
# OF MAM CASES FOUND (MUAC ≥11.5- ≤12.4)
MAM CASES IN SFP (MUAC ≤12.4)
IN SFP PROGRAMME BUT RECOVERED (MUAC ≥12.5)
