Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) Kiyawa LGA CMAM Program Jigawa State, Northern Nigeria June-July 2014
Joseph Njau, Ifeanyi Maduanusi, Chika Obinwa, Francis Ogum, Zulai Abdulmalik, and Janet Adeoye ACF International
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ACKNOWLEDGEMENTS
Kiyawa LGA SQUEAC 1 has been implemented through generous support of the Children Investment Fund Foundation (CIFF). The ACF Nigeria Coverage Assessment Team are grateful to the following for their valuable contributions towards the successful completion of the Kiyawa Local Government Area (LGA) SQUEAC assessment.
Firstly, Gunduma Health System Board (GHSB) Jigawa State authorized the implementation of the SQUEAC assessment in Kiyawa LGA. Usman Tahir (Director General GHSB), and Kabir Ibrahim (Director Primary Health Care GHSB) were very supportive throughout the exercise, acting as the link between the State and the CMAM 2 Coverage assessment team. Aisha Aminu Zango, the State Nutrition Officer (SNO), Husaini Ado of National Population Commission (NPopC), Ibrahim Haruna Head of Department (HoD) Kiyawa LGA Water, Sanitation and Hygiene (WASH) Program and Suleiman Muhammad the Nutrition Focal Person (NFP) of Kiyawa LGA are acknowledged for providing the coverage assessment team with client/beneficiary records, anecdotal program information and the LGA maps.
Gloria Njoku, the ACF’s Head of Base, at Dutse office is appreciated for introducing the team to the various stakeholders and giving logisitical support to the SQUEAC investigation team. Peter Magoh the ACF security manager, and Abubakar Kawu (program support officer) conducted a very helpful security and logistics assessment prior to the implementation of the SQUEAC assessment. Abubakar played a key role in logistics and administrative support during the SQUEAC implementation period.
Joseph Njau (ACF CMAM Coverage Program Manager) provided technical support in the implementation of the assessment while Sophie Woodhead (of Coverage Monitoring Network team - CMN) gave useful insights in compilation and validation of this SQUEAC report. Ifeanyi Maduanusi (ACF Coverage Deputy Program Manager) led the coverage assessment team in training enumerators, supervision of the assessment and writing of the SQUEAC report. The ACF CMAM Program Coverage Officers (Chika Obinwa, Zulai Abdul Malik, Janet Adeoye and Francis Ogum) led the enumerator teams and were instrumental to ensure the quality of daily SQUEAC study activities. The effort of the enumerators -‘the foot soldiers’ in collecting information during the study is acknowledged.
Different stakeholders including health workers, caregivers, traditional and religious leaders, traditional birth attendants and other interviewees who, despite their busy schedule gave very useful information regarding the CMAM Program in Kiyawa LGA are highly appreciated.
Coverage Assessment Team
ACF International
1 Semi Quantitative Evaluation of Access and Coverage 2 Community-based Management of Acute Malnutrition
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Table of contents
1.1.1. EXECUTIVE SUMMARY ...... 7 2. INTRODUCTION ...... 8 3. OBJECTIVES ...... 10 4. METHODOLOGY ...... 10 5. DESCRIPTION OF FIELD ACTIVITIES ...... 14 6. RESULTS AND FINDINGS ...... 14
6.1. STAGE 1: ROUTINE MONITORING AND PERFORMANCE DATA -IDENTIFYING POTENTIAL AREAS OF LOW AND HIGH COVERAGE ...... 14 6.1.1. ROUTINE MONITORING (OTP CARDS ) AND PERFORMANCE DATA ...... 15 6.1.1.1. PROGRAM EXITS (DISCHARGE OUTCOMES ) ...... 15 6.1.1.2. ADMISSION TRENDS ...... 16 6.1.1.3. MUAC AT ADMISSION ...... 18 6.1.1.4. LENGTH OF STAY (L OS) FROM ADMISSION TO RECOVERY ...... 19 6.1.1.5. NUMBER OF VISITS BEFORE DEFAULT ...... 20 6.1.1.6. DEFAULTERS AND ALL EXITS BY LOCATION ...... 21 6.1.1.7. TIME TO TRAVEL TO CMAM (OTP) HF PLOT /DISTANCE FROM TREATMENT CENTRE ...... 22 6.1.2. CONCLUSION OF THE ROUTINE MONITORING (OTP CARDS ) ANALYSIS ...... 24 6.2. STAGE 1: QUALITATIVE DATA -INVESTIGATION OF FACTORS AFFECTING PROGRAM AND COVERAGE ...... 24 6.2.1. QUALITATIVE SAMPLING FRAMEWORK ...... 24 6.2.2. QUALITATIVE INFORMATION ...... 25 6.2.2.1. AWARENESS AND PERCEPTION OF THE PROGRAM , COMMUNITY MOBILIZATION , AND PEER -TO -PEER REFERRALS IN COMMUNITIES ...... 25 6.2.2.2. COMMUNITY VOLUNTEER (CV) ACTIVITY AND HIGH DEFAULT RATE ...... 25 6.2.2.3. HEALTH SEEKING BEHAVIOUR IN COMMUNITIES ...... 26 6.2.2.4. STOCK -OUT OF DATA TOOLS AND ROUTINE DRUGS LEADING TO CHARGES FOR OTP CARDS AND ROUTINE DRUGS 26 6.2.2.5. STOCK -OUT AND MISUSE OF RUTF, AND OCCASIONAL CLOSURE OF OTP SITES ...... 27 6.2.2.6. LARGE TURN -OUT OF BENEFICIARIES , LONG WAITING TIME , AND UNAVAILABILITY OF SHADES , MATS AND BENCHES 28 6.2.2.7. HEALTH WORKERS ACTIVITIES , NON -ADHERENCE TO CMAM GUIDELINES , AND TRAINING ...... 28 6.2.3. DATA TRIANGULATION ...... 29 6.2.4. CONCEPT MAP ...... 31 6.3. STAGE 2: SMALL AREA SURVEY AND SMALL STUDY ...... 31 6.3.1 SMALL AREA SURVEY ...... 32 6.3.1.2 CASE DEFINITION ...... 32 6.3.1.3 RESULT OF SMALL AREA SURVEY ...... 33 6.3.2 SMALL STUDIES ...... 34 6.3.2.1 SAMPLING METHODOLOGY ...... 34 6.3.2.2 CASE DEFINITION ...... 34 6.3.2.3 RESULT OF QUANTITATIVE SMALL STUDY ...... 34 6.3.3 SMALL STUDY ON DEFAULTERS ...... 35 6.3.3.1 RESULTS OF DESCRIPTIVE SMALL STUDY ...... 36 6.3.4 CONCLUSION OF SMALL AREA SURVEY AND SMALL STUDY ...... 37 6.4 DEVELOPING THE PRIOR ...... 38 6.4.1 HISTOGRAM OF BELIEF ...... 38 6.4.2 CONCEPT MAP ...... 39 6.4.3 UN-WEIGHTED BARRIERS AND BOOSTERS ...... 39 6.4.4 WEIGHTED BARRIERS AND BOOSTERS ...... 40 6.4.5 TRIANGULATION OF PRIOR ...... 42
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6.4.6 BAYES PRIOR PLOT AND SHAPE PARAMETERS ...... 42 6.5 STAGE 3: WIDE AREA (LIKELIHOOD ) SURVEY ...... 43 6.5.1 CALCULATION OF SAMPLE SIZE AND NUMBER OF VILLAGES TO BE VISITED FOR LIKELIHOOD SURVEY ...... 43 6.5.2 QUANTITATIVE SAMPLING FRAMEWORK ...... 44 6.5.3 CASE FINDING METHOD AND CASE DEFINITION ...... 45 6.5.4 QUALITATIVE DATA FRAMEWORK ...... 45 6.5.5 RESULTS OF THE WIDE ARE SURVEY ...... 47 6.5.6 POSTERIOR /C OVERAGE ESTIMATE ...... 49 7 DISCUSSIONS ...... 51 8 RECOMMENDATIONS ...... 51 9 ANNEXURE ...... 56
ANNEX 1: SCHEDULE (DETAILED ) OF IMPLEMENTED ACTIVITIES IN KIYAWA SQUEAC...... 56 9.4 ANNEX 2: PARAMETERS USED IN PRIOR BUILDING AND SAMPLE SIZE CALCULATION ...... 61 9.5 ANNEX 3: CONCEPT MAPS -TEAM A AND B...... 62 9.6 ANNEX 3: ACTIVE AND ADAPTIVE CASE FINDING PROCEDURE ...... 64 9.7 ANNEX 6: SUMMARY OF THE SMALL STUDY FINDINGS -KIYAWA LGA ...... 65
List of figures FIGURE 1: MAP OF NIGERIA (TOP RIGHT ) SHOWING JIGAWA STATE AND JIGAWA STATE MAP SHOWING KIYAWA LGA (INDICATED BY ARROW ). MAPS CAN BE DOWNLOADED AT HTTP :// LOGBABY .COM /ENCYCLOPEDIA /HISTORY -OF -JIGAWA - STATE _10024. HTML #.U_C Q7SIG-P8 ...... 9 FIGURE 2: MAP OF KIYAWA LGA SHOWING THE LOCATION OF THE 5 CMAM HF S (HF S) ...... 9 FIGURE 3: EXIT TRENDS FOR KIYAWA LGA CMAM PROGRAM -JANUARY 2013 TO APRIL 2014 ...... 16 FIGURE 4: ADMISSION TREND OF KIYAWA LGA CMAM PROGRAM AND THE SEASONAL CALENDAR OF EVENTS ...... 17 FIGURE 5: ADMISSION MUAC FOR KIYAWA LGA CMAM PROGRAM ...... 18 FIGURE 6: LENGTH OF STAY (L OS) FROM ADMISSION TO RECOVERY ...... 19 FIGURE 7: PROPORTION OF EXIT MUAC S -RECOVERED ...... 20 FIGURE 8: PLOT OF NUMBER OF VISITS BEFORE DEFAULT ...... 20 FIGURE 9: DEFAULTERS ’ MUAC ON EXIT ...... 21 FIGURE 10: PROPORTION OF EXIT MUAC S AT POINT OF DEFAULT ...... 21 FIGURE 11: DEFAULTERS VS EXITS -KIYAWA AND OTHER LGA S ...... 22 FIGURE 12: TIME TO TRAVEL TO CMAM SITES -CASES IN PROGRAM AND DEFAULTERS ...... 23 FIGURE 13: TIME TO TRAVEL TO CMAM SITES FOR EACH OF THE 5 CMAM HEALTH FACILITIES ...... 23 FIGURE 14: REASONS FOR NOT ATTENDING THE CMAM PROGRAM -SMALL AREA SURVEY ...... 33 FIGURE 15: ANALYSIS OF REASONS FOR DEFAULT AND CONDITION OF CASES FOUND IN THE STUDY IN STAGE 2 ...... 37 FIGURE 16: ILLUSTRATION OF TRIANGULATION OF PRIOR ...... 42 FIGURE 17: BAYES SQUEAC BETA -PRIOR DISTRIBUTION PLOT SHOWING THE SHAPE PARAMETERS AND THE SUGGESTED SAMPLE SIZE 43 FIGURE 18: KIYAWA MAP DIVIDED INTO QUADRANTS FOR SPATIAL SAMPLING OF VILLAGES ...... 45 FIGURE 19: BARRIERS TO PROGRAM ACCESS AND UPTAKE -WIDE AREA SURVEY (WAS) ...... 46 FIGURE 20: DISTRIBUTION OF QUADRANTS ACCORDING TO COARSE COVERAGE ESTIMATES ...... 49 FIGURE 21: BAYES PLOT SHOWING PRIOR , LIKELIHOOD AND POSTERIOR (CONJUGATE ANALYSIS ) ...... 50
List of tables
TABLE 1: PARAMETERS USED IN ANALYSES OF LIKELIHOOD SURVEY ...... 13 TABLE 2: SUMMARY OF OUTCOME DATA EXTRACTED FROM BENEFICIARY /OTP CARDS AT A GLANCE ...... 15 TABLE 3: SOURCES AND METHODS USED TO GET INFORMATION IN THE BBQ TOOL FOR KIYAWA LGA...... 29 TABLE 4: BARRIERS , BOOSTERS & QUESTIONS FINDINGS AND SOURCES OF INFORMATION ...... 30 TABLE 5: SIMPLIFIED LOT QUALITY ASSURANCE CLASSIFICATION OF SMALL AREA SURVEY RESULTS ...... 33 TABLE 6: SIMPLIFIED LOT QUALITY ASSURANCE CLASSIFICATION OF SMALL STUDY RESULTS ...... 35 TABLE 7: CMAM HF S AND VILLAGES SELECTED FOR DEFAULTER STUDY ...... 36
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TABLE 8: WEIGHTED BARRIERS AND BOOSTERS OF KIYAWA LGA CMAM PROGRAM ...... 40 TABLE 9: PARAMETERS FOR SAMPLE SIZE CALCULATION FOR LIKELIHOOD SURVEY ...... 44 TABLE 10: BARRIERS TO PROGRAM ACCESS AND UPTAKE -WAS ...... 46 TABLE 11: RESULTS OF THE LIKELIHOOD (WIDE AREA ) SURVEY ...... 47 TABLE 12: DISAGGREGATED SAM CASES PER QUADRANT AND COARSE ESTIMATE DURING THE WIDE AREA SURVEY ...... 47 TABLE 13: FRAMEWORK OF ACTION POINTS TO ADDRESS BARRIERS OF KIYAWA CMAM PROGRAM ...... 52
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ABBREVIATIONS ACF Action Contre La Faim | Action Against Hunger | ACF International
CIFF Children Investment Fund Foundation CMAM Community-based Management of Acute Malnutrition CV Community Volunteer FMOH Federal Ministry of Health GHSB Gunduma Health System Board IEC Information Education and Communication LGA Local Government Area NFP Nutrition Focal Person INGO International Non-governmental Organization OTP Outpatient Therapeutic Program PHC Primary Health Care RUTF Ready to Use Therapeutic Food SAM Severe Acute Malnutrition SLEAC Simplified Lot quality assurance sampling Evaluation of Access and Coverage SNO State Nutrition Officer SMART Standardized Monitoring Assessment of Relief and Transitions SMOH State Ministry of Health SQUEAC Semi Quantitative Evaluation of Access and Coverage VI Valid International
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1.1.1. Executive summary The Community-based Management of Acute Malnutrition (CMAM) in Kiyawa LGA of Jigawa State commenced in October 2011. CMAM is implemented in the five CMAM sites 3 by the Jigawa State’s Gunduma Health System Board (GHSB), Kiyawa Local Government Area (LGA) and primarily supported by UNICEF ‘D’ Field Office, Bauchi. Since inception of the CMAM program a SQUEAC 4 assessment had not been done in Kiyawa LGA. However, a recent SLEAC assessment 56 by Valid International (VI) unveiled a low classification 7 of coverage with 7 children out of total of 47 SAM cases found in Kiyawa LGA being in the program. This gave a coarse estimate of 14.8% which give a picture of program coverage. Kiyawa LGA was chosen for a SQUEAC assessment to identify positive and negative factors affecting CMAM program coverage, build capacity of SMoH and LGA staff, and to proffer recommendations to improve the CMAM coverage. Routine program data and client/beneficiary/Out Patient Therapeutic Program (OTP) records from May 2013 to May 2014 were extracted and analyzed. Five health Facilities (HFs) which offer the CMAM services 8 and 10 villages 9 which form part of the catchment population of these HFs in Kiyawa LGA were visited to obtain additional qualitative information about the CMAM program using different sources 10 and using different methods 11 . All the information was triangulated by the various sources and methods until no new information was forthcoming and then analyzed into negative factors (barriers) and positive factors (boosters) which affect program coverage. The key barriers to program access and coverage identified included; high number of defaulters, lack of motivation of community volunteers to conduct case-finding and defaulter tracing, non-adherence to CMAM national guideline/protocol, generalized stock-out routine drugs, stock-out of data tools for recording beneficiary information, consumption of RUTF by adults, and siblings of SAM children in communities, weak mechanism for delivery of RUTF to HFs. The key boosters include; large turnout of beneficiaries 12 , good awareness of the program in communities, good opinion of the program in communities, willingness of beneficiaries to stay in the program despite challenges 13 , peer-to-peer referrals by caregivers, good working relationship between Health workers (HWs) and CVs.
3 All the five CMAM sites Katuka, Garko, Maje, Kwanda and Katanga 4 Semi Quantitative Evaluation of Access and Coverage 5 D’ Field Office is located in Bauchi, Bauchi State. 6 Chrissy B., Bina S., Safari B., Ernest G., Lio F. & Moussa S.; Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) Survey of Community-based Management of Acute Malnutrition program; Northern States of Nigeria-(Sokoto, Kebbi, Zamfara, Kano, Katsina, Gombe, Jigawa, Bauchi, Adamawa, Yobe, Borno). Valid International. February 2014 7 The SLEAC used a three-class classifier with 20% and 50% as the thresholds; <= 20% is low; >20% to <=50% is moderate coverage while >50% 8 All the five CMAM sites Katuka, Garko, Maje, Kwanda and Katanga were visited. 9 Villages visited include; Nafara, Dangoli, Tsirma, Jama ‘a Dawa, Kakarawa, Gorumo, Yelwa, and Danfasa. 10 Care-givers, Health Workers (HWs), Community Volunteers (CVs), community leaders, religious leaders, majalisa, teachers, traditional healers, traditional birth-attendants (TBAs), and women group, etc. 11 Semi-structured interview, in-depth interview, observations and informal group discussions 12 This is a potential for enhancing peer to peer referral and less dependence on CVs 13 For instance there are caregivers who sleep-over at CMAM facilities till they are attended.
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Homogenous coverage across the wards in Kiyawa LGA was confirmed. Program failures caused by placing some costs (hidden charges) on OTP cards and routine drugs to be borne by beneficiaries was also confirmed; defaulters were studied and reasons for defaulting were also analyzed. After conjugate analysis of the prior and likelihood survey, a point coverage estimate of 48.5% (41.3% - 55.8%. CI; 95%) 14 was reported. Thus the coverage was significantly higher than that unveiled in the recent SLEAC results for Kiyawa LGA due to reasons explained in detail in the report. Recommendations : key recommendations include provision of data tools for CMAM sites, provision of routine drugs, removal of the hidden charges on beneficiaries to ensure free CMAM services, strengthening of the delivery mechanism of RUTF to HFs, supportive supervision of HWs at CMAM HFs to enhance adherence to CMAM protocol and establishment of innovative ways to improve motivation of CVs.
2. Introduction Jigawa State is located in the Northwest of Nigeria. It is bordered by States of Kano and Katsina in the West, Bauchi in the South, Yobe in the East and shares nn international border with Niger Republic in the North.. The State has 27 Local Government Areas (LGAs) 15 . According to the 2006 census, the State has a total population of 4,348,649 million inhabitants 16 . The population growth of the state is estimated at 3.5 % with about 48 % of the population falling under the age of fifteen. Out of the total population about 2.9 million are considered to be productive adults. Eighty per cent (80%) of the population is found in the rural areas and is made up of mostly Hausa, Fulani and Manga (a Kanuri dialect). The pattern of human settlement is nucleated, with defined population centres 17 . Kiyawa LGA is about 30 km away from Dutse (Jigawa State Capital). It is bordered by Dutse, Birnin Kudu, Buji, Kafin Hausa, and Jahun LGAs, as well as Bauchi State. The people of Kiyawa are mostly Hausa and Fulani. The major occupation is farming; while the religion is predominantly Islam. Kiyawa LGA is under the traditional leadership of the Emir of Dutse, with two district heads in Shuwarin and Kiyawa districts in charge of the traditional affairs of the LGA. At the commencement of implementation of Community-based Management of Acute Malnutrition (CMAM) in Kiyawa LGA in October 2011, 5 CMAM sites were established 18 . The program is supported by UNICEF ‘D’ Field Office, which provides technical support. The health workers 19 run the services at the CMAM Health Facilities (HFs) on a weekly basis. A Nutrition Focal Person (NFP) for the LGA supervises the five CMAM sites and reports to the State
14 Results are expressed with a credible interval of 95%. 15 Auyo, Babura, Biriniwa, Birnin Kudu, Buji, Dutse, Gagarawa, Garki , Gumel, Guri, Gwaram, Gwiwa, Hadejia, Jahun, Kafin Hausa, Kaugama, Kazaure, Kiri Kasama, Kiyawa , Maigatari, Malam Madori, Miga, Ringim, and Roni 16 National Population Commission 17 http://logbaby.com/encyclopedia/history-of-jigawa-state_10024.html#.U_Cq7sIg-P8 18 UNICEF Nigeria uses a model of 5 CMAM sites in each LGA for treatment of malnourished children. This is presently, being reviewed for possible scale-up. 19 HWs are employees of the Gunduma Health System Board -GHSB)
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Nutrition Officer (SNO) who coordinates all nutrition activities in the State. The SNO who reports to the State Director of Primary Health Care, also serves as the linkage to the UNICEF Nutrition Specialists in UNICEF regional Office.
Figure 1: Map of Nigeria (top right) showing Jigawa state and Jigawa state map showing Kiyawa LGA (indicated by arrow). Maps can be downloaded at http://logbaby.com/encyclopedia/history-of-jigawa-state_10024.html#.U_Cq7sIg-P8
Figure 2: Map of Kiyawa LGA showing the Location of the 5 CMAM HFs (HFs)
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SQUEAC has not been carried out since the commencement of CMAM program in Kiyawa to determine access and coverage of the program. However, a recent SLEAC study conducted late 2013 by Valid International reported a coarse estimate of 14.89% (where 7 SAM cases were covered by the CMAM program out of 47 SAM cases found in the LGA during the assessment). Therefore, Kiyawa LGA CMAM coverage was classified as low and was one of the LGAs (Kiyawa) identified for an in-depth investigation through a SQUEAC assessment. The purpose was to gather additional information on positive and negative factors affecting access and coverage of CMAM program. The SQUEAC assessment was undertaken in Kiyawa LGA in the month of July 2014.
3. Objectives The SQUEAC investigation was guided by the following specific objectives;
1. To investigate the barriers and boosters to program and coverage in Kiyawa LGA. 2. To evaluate the spatial pattern of program coverage in Kiyawa LGA. 3. To estimate overall program coverage in Kiyawa LGA. 4. To make relevant recommendations in order to reform and to improve the CMAM program, 5. Build the capacity of SMoH and LGA staff to conduct a SQUEAC assessment.
4. Methodology The SQUEAC methodology was adapted to suit the SQUEAC investigation of Kiyawa LGA CMAM program. The methodology used are explained in detail as follows; Stage 1
Quantitative data: Routine program data, and data from client information recorded in the OTP cards were extracted and analyzed into various plots; admission trends; exit trends; time to travel to site; Length of stay from admission to cure; MUAC at admission; number of visits before default; MUAC at default; defaulters by location. The derived plots indicated some factors that affect the program such as existence of active case finding, met need, far distance and defaulting tendencies. Qualitative data Barriers, boosters and questions: Qualitative information was collected from different sources, using different methods. The information was analyzed into a barriers, boosters and questions (BBQ) to capture the positive and negative factors that affect the program and its coverage. The data was triangulated to adduce evidence. Additional information was
10 collected to confirm the evidence gathered before, until no further information was forthcoming around a certain theme/topic in a process referred as sampling to redundancy. This information was further analyzed into weighted and un-weighted barriers and boosters which were scored according to the perceived weight each barrier or booster had on the program coverage (either negatively or positively). The process of weighing barriers and boosters is discussed in detail in separate section (making the prior section). Concept map: the factors that affect the program were analyzed into a concept maps that showed the relationship between them. The concept maps are annexed in section 9.3 annex 3. Stage 2 data
Based on the information and evidence gathered in stage 1, a small area survey and two small studies were conducted to investigate the spatial pattern of coverage and factors that may be affecting coverage. Small Area Survey The small area survey data was analyzed using simplified Lot Quality Assurance Sampling (LQAS) technique to test a hypothesis. This was done by examining the number of Severe Acute Malnutrition (SAM) cases found ( n) and the SAM cases covered (c) in the program. The threshold value ( d) was used to determine if the coverage was classified as satisfactory or not. Value ( p) was used to denote a minimum standard used as a measure of high, moderate or low coverage 20 . The recent SLEAC assessment coverage classification (with a coarse estimate of 14.98%) indicated that the coverage in Kiyawa LGA was low, that is below 20% 21 . Given this coverage classification in Kiyawa LGA, consideration could have been given to use the 2 standard 3 class classifier to set the values of p1 and p2 as the lower and higher limit of classification of coverage to test spatial coverage hypothesis in the current SQUEAC assessment. However, in Kiyawa SQUEAC assessment the standard ( p) was adapted as 50% 22 for analyses of small area survey data using simplified LQAS. This was because it was highly likely that the coverage could have considerably improved at the time of this SQUEAC investigation compared to the period when SLEAC assessment was implemented. The low coverage unveiled by SLEAC assessment could be attributed to long duration of stock-out of RUTF at the time 23 . In the current SQUEAC investigation, the information gathered in stage 1 gave a picture of a program that was likely to have a high coverage. Therefore, using the
20 SPHERE standards has recommended minimum coverage for Therapeutic programs in rural, urban, and camp settlements. These thresholds are 50%, 70% and 90% coverage for TFP program run in the contexts of rural, urban and camp areas respectively. 21 The two standard three class classifier classifies coverage as follows: Low coverage-20% and below; Moderate coverage- greater than 20% up to 50%; high coverage-above 50% 22 Previously conducted SLEAC coarse estimate was not considered to set the value of “p” in Kiyawa LGA. Therefore, the sphere standard of coverage in a rural setting <= 50% for low coverage; and >50% for high coverage was used. 23 The Wide Area Survey in SLEAC assessment considers the children who are in the program (covered) against the total number of SAM cases found during the survey. Large number of Current (SAM) cases were not covered during SLEAC due to lack of RUTF stocks in HFs at the time; which may have made many beneficiaries stay home till RUTF was available at the HFs
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SPHERE standard of coverage mentioned above is sufficiently sensitive to show disparities in spatial coverage in Kiyawa as the context has changed. Therefore:
The value of (p) used that was used was 50%. The formula for deriving (d) is shown below:
50 = × = × = 100 2 If the number of covered cases exceeded value (d), then the coverage was classified as being satisfactory. However, if the number of covered cases found did not exceed value (d) then the coverage was classified as being unsatisfactory. The combination of the (n) and (d) was used as the sampling plan. The results of the small area survey were shown in table 5 and reasons for coverage failure obtained from the small area survey were plotted in figure 6 in results section of this report. Small Study Two small studies were conducted; that is, a quantitative and a descriptive small study respectively. The small study investigated the number of beneficiaries that were charged for CMAM routine drugs and OTP registration cards and therefore, establish whether this was major cause of coverage failure. The data obtained was analyzed quantitatively using simplified LQAS and utilized the threshold (p) of 50% (as use in small area survey). This way the classification thereof, established whether charging beneficiaries for the mentioned service contributed to coverage failure. In this study, the (n) parameter was number of caregivers with SAM cases that were interviewed. A descriptive small study of defaulters was done to understand the reasons for defaulting and results presented on table 6 and illustrated in Figure 14.The results of the small study are explained in the results section of this report. Stage 3 data
The prior : The tools that have been used revealed a rich set information about coverage. It also identified barriers to access and care, as well as spatial coverage of the program. Therefore the prior of the program was estimated through use of the following tools 24 :
• Belief histogram • Weighted barriers and boosters • Un-weighted barriers and boosters • Calculation of the total positive and total negative factors illustrated in the concept map. The prior was established in a beta prior distribution with prior shaping parameters and plotted on BayesSQUEAC calculator 25 . The beta prior distribution 26 expresses the findings of
24 Each listed process is discussed in detail in the body of the report. The recent SLEAC coarse estimate was not used incorporated while calculating the prior. This was because it was observed that it could possibly bias the result since CMAM sites were closed down at the time coinciding with the SLEAC survey in Kiyawa LGA in 2013. 25 Downloaded free from www.brixtonhealth.com 26 As illustrated in the example in figure 21 in results section of this report.
12 stage 1 and 2 in similar ways to the likelihood survey’s (binomial distribution) as described in a sections below. The BayesSQUEAC calculator also suggested a sample size at 10% precision. The likelihood survey yielded data that was analyzed to give program coverage. The data was organized into the parameters shown in the table 1 below. The binomial distribution of the likelihood results are shown in figure 21 in results section in this report. Table 1: Parameters used in analyses of likelihood survey
Parameters Values Current cases in the program (x) Current SAM cases not in the program (y) Total current SAM cases (x+y= n)
27 Point coverage . CI 95% ( ) = 100 ( + )
The program coverage (posterior).
The process of combining the prior and the likelihood to arrive at the posterior (also referred as conjugate analysis 28 ) was used in arriving at the program coverage in this SQUEAC investigation. This meant that the prior information about coverage (i.e. the findings from the analysis of routine programs data; the intelligent collection of qualitative data; and the findings of small- area surveys, and small studies) collected using the bayesian technique 29 was helpful to provide information about overall coverage of the program (expressed in a beta prior distribution). As such, all the relevant information that was collected in stage 1 and 2 were used together with the survey data that were collected in stage 3 of the SQUEAC investigation to give an overall picture about the program and to unveil the headline coverage. A conjugate analysis which is used to provide the program coverage (as described below) requires that the prior and the likelihood are expressed in similar ways. The conjugate analysis combined the beta distributed prior with a binomial distributed likelihood to produce a beta distributed posterior (see figure XX).
Met need is calculated as: