KURIGRAM, BANGLADESH NOVEMBER, 2013

LOVELY AMIN

ACKNOWLEDGEMENTS

I would like to thank the team of Terre des hommes, Dhaka and Kurigram for the support they have provided throughout the mission as well as their active participation in the SQUEAC assessment for Kurigram CMAM programme.

I would like to convey a special thanks to Dr. Ehsnul Matin, and Fahmida Afreen and Mohammed. Monsurul Hoq for assisting me during the SQUEAC training and the survey. I am grateful to all participants of the SQUEAC training and the survey that includes the, staff from Ministry of Health, WFP and RDRS, Bangladesh for their active and lively participations throughout the entire exercise. My gratitude also goes out to the various members of the community: the mothers, Community Nutrition Promoters (CNPs) and the Traditional leaders, the Traditional Birth Attendants (TBAs) and the Traditional healers as well as the OTP and SC staff of the visited health centres.

Lastly, but not the least CMN would like to thank it’s funders, ECHO and USAID for funding the CMN project. This project made it possible to conduct this coverage assessment and trained some health and nutritional professionals of Tdh, WFP and RDRS of Kurigram on SQUEAC methodology.

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EXECUTIVE SUMMARY

Introduction Bangladesh, one of the worlds’s most densely populated countries1 in the world. Preliminary figures from the 2011 census put the population at over 150 million people. The country consists of 7 divisions, 64 districts, and 545 Upazilas/Thanas2 (BBS, 2012a). Kurigram is one of the districts in the northern region of Bangladesh in Rangpur division.

The area of Kurigram district is 2,296.10 km² with approximate population of 1,782,2773. Kurigram recognise among the Districts with the most extreme levels of poverty in Bangladesh4. In terms of MDG progress, Kurigram is flagged among districts making “no progress” per child risk measure ranking5. The general, health statistics for the population in Kurigram District are a sobering experience6789.

Methodology To assess the service quality and programme coverage of Community based Management of Acute Malnutrition (CMAM) programme implemented by Tdh’s in Kurigram, a coverage assessment was carried out from November 17th to 30th 2013. The assessment utilised a three stage investigation model of Semi- Quantitative Evaluation of Access and Coverage (SQUEAC) methodology was used. This model includes: i) collecting and analysing the qualitative and quantitative data; ii) develop and test the hypothesis by conducting a Small Area Survey; and iii) conduct a ‘Wide Area Survey’ to estimate the final programme coverage rate for both Supplementary Feeding Programme (SFP) and Out-patient Therapeutic Programme (OTP).

Main Results

Stage -1

 The OTP admissions The CMAM programme admissions data of showed that malnourished children that were admitted in SFP 87% and in OTP 80% were successfully treated and cured.

1 GoB: Bangladesh Country Investment Plan, A Road Map Towards investing in Agriculture, Food Security and Nutrition (CIP), updated June 2011 2 Bangladesh Bureau of Statistics (BBS), 2012a 3 2001 national population census 4 BBS, World Bank, WFP: Updating Poverty Maps of Bangladesh, 2009 5 UNICEF, Assessment of district performance in making progress towards MDGs in Bangladesh 6 Multiple Indicator Cluster Survey Bangladesh 2006, Key Findings, BBS-UNICEF, Dhaka (May 2007); http://www.reliefweb.int/rw/rwb.nsf/db900SID/MYAI-7WJ55E?OpenDocument 7 Tdh Bangladesh’s project reports from the field (2010-2011) 8 Situation Assessment and Analysis of Children and Women in Bangladesh, UNICEF Bangladesh, September 2009 9 Household Food Security and Nutrition Assessment in Bangladesh, November 2008-January 2009, (WFP, UNICEF, IPHN), March 2009.

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 Communities’ knowledge and attitudes: From the qualitative assessment most of the community members were found to have knowledge of the CMAM programme. However, there was insufficient formal introduction or active mobilisation activities carried out to get the community to fully understand and to participate in this programme.

Stage – 2  Hypothesis testing and results After collecting and analysing the data in stage one, a hypothesis was generated and tested in stage two. The hypothesis that was generated; the ‘CNCs with high admissions have high coverage and CNCs with low admissions have low coverage’.

The results determined that area with ‘high admissions’ were found to have ‘high coverage’ hence this part of the hypothesis was ‘confirmed’. Areas with ‘low admissions’ were found not have ‘low coverage’. Therefore this part of the hypothesis was ‘not confirmed’.

Stage – 3  Coverage Estimation (results from wide area survey) In stage three survey data allowed to perform the final coverage estimation, after the ‘Wide Area Survey’. The ‘point’ coverage rate is estimated for MAM at 71.4% with Credible Interval (CI- 63.2% - 78.7%), for SAM at 61.0% with Credible Interval (CI- 45.7% - 74.4%). These estimate lies within the SPHERE standard for rural area, >50%.

 Main Barriers The main barriers found in the assessment are: insufficient community mobilisation, communities’ poor participation in CMAM programme, staff work load, inadequate IYCF practice and insufficient use of CMAM protocol especially on home visits for defaulters, sick and absent cases.

 Key Recommendation  Organize one day CMAM programme inception/ training for the programme key stakeholders.  Regular meetings with key stakeholders such as village leaders, religious leaders, and TBAs  Task analysis: day/staff calculation for optimal task allocation  Design a session plan on IYCF and implementation of the plan for community/mothers  Rearrange CNCs according to need to avoid distance from home to CNCs.  Discussion between program partners such as WFP to reduce waiting period for identified cases.

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CONTENTS

EXECUTIVE SUMMARY------3 ABBREVIATIONS ------6 1. INTRODUCTION------7 1.1 COUNTRY CONTEXT ------7 1.2 CONTEXT OF KURIGRAM------8 2. PURPOSE ------10 2.1 SPECIFIC OBJECTIVES ------10 2.2 EXPECTED OUTPUTS ------10 2.3 DURATION OF THE ASSESSMENT ------10 2.4 PARTICIPANTS ------10 3. METHODOLOGY ------11 3.1 STAGE 1 ------11 3.2 STAGE 2 ------13 3.3 STAGE 3 ------14 4. RESULTS ------17 4.1 STAGE 1------17 4.1.1 PROGRAMME ROUTINE DATA ANALYSIS ------17 4.1.2 QUALITATIVE DATA COLLECTION AND FINDINGS ------23 4.2 STAGE 2 SMALL AREA SURVEY------27 4.2.1 FINDINGS OF SMALL AREA SURVEYS ------27 4.3 STAGE 3 WIDE AREA SURVEY------29 4.3.1 FINDINGS OF WIDE AREA SURVEY ------29 4.3.2 COVERAGE ESTIMATION ------31 4.3.3 BARRIER TO THIS PROJECT ------32 4.3.3.1 THE BARRIERS AFFECTING THE COVERAGE ------34 5. DISCUSSION ------35 5.1 PROGRAMME ROUTINE DATA ------35 5.2 PROGRAMME CONTEXTUAL DATA------36 5.3 WIDE AREA SURVEY------37 6. CONCLUSION------38 7. RECOMMENDATIONS------39 7.1 SPECIFIC RECOMMENDATIONS ------39 7.2 ACTION PLAN------40 ANNEXES------41 ANNEX 1: SCHEDULE OF SQUEAC TRAINING AND ASSESSMENT ------41 ANNEX 2: LIST OF PARTICIPANTS ------42 ANNEX 3: SQUEAC QUESTIONNAIRES FOR CONTEXTUAL DATA COLLECTION ------43 ANNEX 4: X-MIND------45 ANNEX 5: SEASONAL CALENDAR ------48 ANNEX 6: SQUEAC SURVEY QUESTIONNAIRES ------49

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ABBREVIATIONS

ACF Action Contre la Faim/ Action Against Hunger CI Credible Interval CNC Community Nutrition Centre CNP Community Nutrition Promoter CMAM Community based Management of Acute Malnutrition CMN Coverage Monitoring Network FGD Focus Group Discussion GAM Global Acute Malnutrition ICDDR,B International Centre for Diarrhoeal Disease Research, Bangladesh KII Key Informant Interview LoS Length of Stay MAM Moderate Acute Malnutrition MUAC Mid-Upper Arm Circumference OTP Outpatient Therapeutic Programme RUTF Ready to Use Therapeutic Food SAM Severe Acute Malnutrition SNU Specialised Nutrition Unit SSI Semi Structure Interview SQUEAC Semi Quantitative Evaluation of Access and Coverage TBA Traditional Birth Attendants Tdh Terre des hommes UNICEF United Nations Children’s Fund WHO World Health Organisation

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1. INTRODUCTION

1.1 COUNTRY CONTEXT

Despite the progress on key Millennium Development Goals (MDG) indicators reported by the Government of Bangladesh (GoB) in the past decade, especially situation of Mother and Child Health and Nutrition in Bangladesh remains alarming. The maternal mortality rate still stands at 3.2 per 1,000 live births. The rate of institutional delivery is only 15% and facilitation of skilled birth is 18%.10 The survival and development of many Bangladeshi children is continuously threatened by malnutrition, disease, poverty, illiteracy, abuse, and exploitation.11 Bangladesh is also burden by one of the highest malnutrition rates in the world, 30% of women are thin; 43% of children are stunted and 17% wasted12. To make matter worse, household vulnerability to the effects of natural disaster is exacerbated by deteriorating access to natural resources (water, land), resulting poor access to food and poor provisions of sanitation. In this context, women and children of Bangladesh represent the most vulnerable segments of the population.

1.2 CONTEXT OF KURIGRAM

Kurigram District is located in the northern region of Bangladesh in Rangpur division. It is bordering with India. The area of this district is 2,296.10 km² with approximate population of 1,782,277 (2011 national population census). Kurigram recognise among the Districts with the most extreme levels of poverty in Bangladesh13.

In Kurigram, one in three families is food insecure compared to 1:4 nationally14. The vulnerability is particularly acute in the lean season occurring in September-November (monga period), due to a chronic lack of employment opportunities in the area.

In terms of MDG progress, Kurigram is flagged among districts making “no progress” per child risk measure ranking.15 The general, health statistics for the population in Kurigram District are a sobering experience6789. Based on Bangladesh Demographic and Health Survey, 2011;

 Nearly 20% of under-5 children are affected by moderate or severe acute malnutrition (national: 16%).  The maternal mortality rate remains 3.2 per 1,000 live births.

10 UNICEF, November 2009 11 GoB, Planning Commission: Moving Ahead, National Strategy for Accelerated Poverty Reduction II FY 2009-2011, 2008 12 GoB: Bangladesh Country Investment Plan, A Road Map Towards investing in Agriculture, Food Security and Nutrition (CIP), updated June 2011 13 BBS, World Bank, WFP: Updating Poverty Maps of Bangladesh, 2009 14 WF P, UNICEF, IPHN: Household Food Security and Nutrition Assessment in Bangladesh, 2009 15 UNICEF, Assessment of district performance in making progress towards MDGs in Bangladesh

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 The neonatal death rate lies above 40 per thousand live births (national: 37); in fact, neonatal deaths account for over one half of all under-5 deaths.  The exclusive breastfeeding rate is only 38%.  Acute Respiratory Infection (ARI) rate more than 40%.  Deliveries are attended by trained personnel in less than 15% (national: >20%).  The prevalence of Reproductive Tract Infection (RTI) is above 50% (national: 35.4%).  More than 80% marriage is accounted to be early marriage, is the highest in in the country (national: >70%).

In addition, the local population are facing with poorly performed public health system although Bangladesh’s national health plan aims at increasing availability of essential and equitable services.

Terre des hommes Lausanne (Tdh) has been operating in Kurigram since 1974, and currently offers comprehensive health services for women, infants and young children living in three rural Unions and one peri-urban slum area. The health service targeted Goghadaha, Thanahat Union and Kurigram Municipality covering population of approximately, 160,630. The programme serves the community thorough 2 maternal and child health centres, 2 community-based static clinics and 19 satellite clinics. The comprehensive health package includes safe motherhood, reproductive health, integrated management of childhood illness, reducing waterborne diseases and CMAM services. Terre des hommes’s 25-bed Specialized Nutrition Unit (SNU) serves as inpatient care of severely acute malnourished children with complications. The programme also includes treatment of Severe and Moderate Acute Malnutrition (SAM and MAM) through OTP and SFP respectively. The Tdh CMAM service follows the national CMAM protocols to treat acute malnutrition.

The anecdotal knowledge on mothers’ nutritional status has been accumulated through 15 years of experience at Tdh’s Specialized Nutrition Unit (SNU) in Kurigram, the clinical setup presents in Kurigram managing cases of children with SAM. SNU nurses reported that the profile of mothers whose children are wasted and admitted to the programme is often teenage girls with low BMI’s16.

The Community-based Management of Acute Malnutrition (CMAM) programme started as a pilot project in Bangladesh, 2004 which discontinued later. Despite the resistance in recent years CMAM approach has been used by some national and international organisation to treat acute malnutrition. In 2011 the National CMAM guidelines has been developed and approved by MoH of Bangladesh17. ICDDR,B took initiative to produce local RUTF with GoB approval and with the support of UNICEF. According to ICCDDR,B the local RUTF will soon go through acceptability and efficacy test.

16 Improving Mother and Child Health & Nutrition in Kurigram District of Bangladesh, A project proposal to Swiss Solidarity, Tdh, 2010 17 National Guidelines for Community Based Management of Acute Malnutrition in Bangladesh,2011

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There were no coverage assessment was carried out to this programme therefore, a coverage assessment and training on the coverage assessment methodology was commissioned by the Coverage Monitoring Network (CMN). The CMN project is a joint initiative by ACF, Save the Children, International Medical Corps, Concern Worldwide, Helen Keller International and Valid International. The programme is funded by ECHO and USAID. This project aims to increase and improve coverage monitoring of the CMAM programme globally and build capacities of national and international nutrition professionals; in particular across the West, Central, East & Southern African countries where the CMAM approach is used to treat acute malnutrition. It also aims to identify, analyse and share lessons learned to improve the CMAM policy and practice across the areas with a high prevalence of acute malnutrition. The project is mainly focus on building skills in Semi Qualitative Evaluation of Access and Coverage (SQUEAC) methodology as well as asses the programme quality and measuring the programme coverage.

To assess the programme quality and coverage of Kurigarm CMAM programme, the SQUEAC methodology has been used. The main objective of the SQUEAC methodology is to improve the routine monitoring activities, and identify the potential barriers to access services. The findings ultimately intend to facilitate optimum coverage of the programme.

A team of health and nutrition professionals of Tdh’s, the Ministry of Health, WFP and RDRS Bangladesh were trained in the SQUEAC methodology. The aim of the exercise was to build the local capacity and to continue with the coverage monitoring assessment in the county/division in coming months and years (Figure 1).

Figure 1: The SQUEAC training Kurigram, November, 2013

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2. PURPOSE OF THE ASSESSMENT

The SQUEAC assessment was conducted in Kurigram with the aim to provide training and build the skills of key nutrition staff of Tdh and their partner organisations, WFP and RDRS on the SQUEAC methodology. In addition, consultant facilitates to evaluate access and coverage of CMAM programme using SQUEAC methodology. Providing technical support to Tdh’s CMAM programme in Kurigram on various issues; how to improve the collection and utilisation of the programme’s routine monitoring data. How to improve programme quality and improve overall programme coverage?

2.1 Specific Objectives 1. Train and enhance competencies of technical staffs of Tdh, MoH and other stakeholder’s to undertake future SQUEAC assessment independently. 2. Assess the programme data quality whilst in the field and during data entry and analysis during SQUEAC survey implementation in Kurigram. 3. Identify factors affecting access to CMAM services in Kurigram and find possible solutions to these barriers using data gathered from those cases found with acute malnutrition and not admitted in the programme at the time of the survey. 4. To estimate point coverage in the target areas (i.e. Kurigram Municipalty, Thanahat and Gogadaha Union) of Kurigram. 5. Develop in collaboration with Tdh specific recommendations to improve acceptance and coverage of the programme.

2.2 EXPECTED OUTPUT  Train staff on SQUEAC methodology  Implementation of coverage assessment in Kurigram  Produce final coverage survey report for Kurigram SQUEAC

2.3 DURATION OF THE ASSESSMENT & THE TRAINING 17th to 28th November 2013 (Annex 1).

2.4 PARTICIPANTS A total of 16 staff were trained in the SQUEAC method of which, 13 were from Tdh Kurigram, 1 from MoH, Bangladesh, and 1 from WFP and 1 from RDRS, (Annex 2).

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3. METHODOLOGY

Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) methodology was used to assess the CMAM programme coverage and qualities of Tdh’s programme in Kurigram, Bangladesh. The SQUEAC18 methodology was developed to provide an efficient a n d accurate method for identifying existing barriers to a cc e s s services, opportunities that can be exploited and assessing coverage in an emergency as well as non-emergency context. This approach places a relatively low demand on logistical, financial and human resources but provides detailed information. To estimate coverage, villages with ‘high admission’ and villages with ‘low admission’ rates were detected and the principle factors preventing higher coverage in targeted areas were identified. For this assessment a three stage investigation model was used. This model includes;

 Stage 1, analysis of qualitative (contextual data) and quantitative (programme routine monitoring data) data, compare with SPHERE minimum standard19.  Stage 2, conduct a ‘Small area survey’ in the communities with the highest and lowest admissions in the OTPs/CNCs  Stage 3, conduct a ‘Wide area survey’ to estimate programme coverage rate and compare with SPHERE minimum standard.

3.1 STAGE 1

Quantitative and qualitative data analysis to understand barriers/boosters to coverage

In stage one, existing programme routine monitoring data which have been collected and compiled from August 2012 to July 2013 were gathered and analysed. In addition, to the routine programme data qualitative data was collected by the teams from the CMAM programme area of Kurigram municipality, Gogadaha and Thanahat union. The data (both qualitative and quantitative) were collected using various methods and from several sources.

The qualitative data collection was aimed at understanding the perception of the target population about the programme, the programme implementers, and their knowledge of malnutrition in the area. A generic questionnaire was developed to guide the data collection from communities on their perceptions of the CMAM programme, care seeking behaviour and common practice of treating malnutrition etc. (Annex 3). The data collectors were then trained on how to conduct the interviews and how to facilitate group discussions. The method used was focus group discussions (FGDs) and Key Informant Interviews (KIIs) see the below table for details. Open ended generic questionnaires were used for FGDs and KIIs.

18 Mark Myatt, Daniel Jones, Ephrem Emru, Saul Guerrero, Lionella Fieschi. SQUEAC & SLEAC: Low resource methods for evaluating access and coverage in selective feeding programs. 19 The Sphere Project Humanitarian Charter and Minimum Standards in Disaster Response, 2004

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The information was collected using the following methods and sources: Methods Sources Key Informants Interview (KII)  Village Leaders, Male & Female  Religious Leaders  Traditional Birth Attendants (TBA)  Village Doctor  Other NGO workers Focus Group Discussions (FGDs)  Caretaker of OTP and SFP children  OTP and SFP staff  Assessment team

Semi Structure Interview (SSI  Mothers of children with SAM who are ‘not in Programme’. Seasonal Calendar (Fit to Context and Seasonality)  Community and the assessment team

Figure: 2 Group discussions with OTP mothers In stage one, information was collected from different sources through various methods. The information gathered was then analysed and triangulated until the questions had been answered. This information was further drawn, summarised, and modified as the assessment proceeded.

The information was plotted on the ‘Mindmap’ which is a graphical way of storing and organising data and ideas around a central theme in this case it was programme ‘coverage’. All those information was simultaneously transferred to the X-Mind programme (Annex 4). Based on the findings from programme routine data and information collected from the communities the barriers and boosters were identified and questions were generated for further investigation. The boosters and Barriers were then weighed and scored to determine the coverage for stage one, which then helps to estimate coverage for final stage.

Seasonal calendar Seasonal calendar was drawn in stage one in order to get a broader picture of programme performance against context. The calendar included agricultural labour, trading, disease, meteorological changes and hunger gaps. Admission and defaulter trends were then compared to the seasonal calendar (Annex - 5) to determine whether the programme was responding to seasonal changes and context-specific factors.

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The calendar was developed with the SQUEAC assessment team and the mothers/caretakers of children attending OTP and SFP, compared, and then a final calendar was developed to compare with the admission and defaulter trends of the programme from August 2012 to July 2013.

3.2. STAGE 2 ‘SMALL AREA SURVEY’

Generally, after stage one data gathering and data analysis generate some question that needs further investigation. In Kurigram SQUEAC one question has been generated: “Does the areas with high admissions in SFP and OTP and also have high coverage, and areas with low admissions for SFP and OTP consequently have low coverage”?

Hypothesis formation Following the question above, a hypothesis was generated: Supplementary Feeding Programme (SFP): Community Nutrition Centres (CNC) with high admission in SFPs has high coverage rates while CNCs with low admissions at SFPs have low coverage rates.

Outpatient Therapeutic Feeding Programme (OTP): Community Nutrition Centres (CNC) with high admission in SFPs has high coverage rates while CNCs with low admissions at SFPs have low coverage rates.

To test the hypothesis, fourteen Para (sub villages) systematically selected and surveyed to see whether areas with high admissions indeed have high coverage and areas with low admissions indeed have low coverage. Using the programme admission data, seven para/subsections were selected from four CNC sites that recorded highest number of admissions. Similarly, seven para/subsections selected from four CNC sites were that recorded the lowest number admissions.

For this assessment it was decided to analyse both SFP and OTP data as the OTP admission in this programme was very low. Therefore in this small area survey both SAM and MAM cases were actively searched for.

In this stage to estimate the coverage classification for hypothesis test, in total fourteen Para were surveyed. The survey was conducted in one day by the eight teams. Sample size was not necessary to calculate in advance for this survey. The survey sample size was the number of SAM and MAM children found by the surveyors in the sampled paras in one day. Based on coverage threshold for rural area noted in SPHERE minimum standard, 50% coverage was defined as adequate coverage.

Pre designed questionnaires were used to record the cases (SAM & MAM), including both current cases and recovering cases (Annex 6a). A separate questionnaire was used for the mothers/caretakers of malnourished child that were not attending the programme to find out and record the reasons for not attending the programme (Annex 6b).

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However, in this survey, a door to door case finding method was utilized to find active cases of SAM and MAM. Therefore almost all children age 6 to 59 months were measured in fourteen surveyed Para.

Case Definition The admission criteria for SAM and MAM of the Kurigram CMAM programme included children age between 6 and 59 months with at least one of the following criteria:

For SAM to be admitted to OTP : 1. A Mid Upper Arm Circumference (MUAC) of <11.5 cm and/or 2. Bilateral pitting oedema and/or 3. WHZ Score <-3 SD

For MAM to be admitted to SFP: 1. A Mid Upper Arm Circumference (MUAC) of <12.5 cm

In this SQUEAC survey, the case definition used for Kurigram was “a child matching o n e o f the admission criteria of the OTP or SFP” MUAC and bilateral pitting oedema. T h u s , in this SQUEAC survey, a case is defined as a child with a MUAC of <11.5cm and/or presence of bilateral pitting oedema for SAM; and a MUAC of <12.5 cm for MAM.

Local names for malnutrition in Kurigram For the SQUEAC assessment local names were used for case (SAM) finding. Malnutrition is known as Shukna Bacha Marasmus is known as Haddi-shar/chikon bacha Nutritional Oedema is known as – fhula bacha, depdepha bacha.

Semi Structure Interview (SSI) Semi structured interviews were used as part of the small and wide area surveys for the mothers/caretakers of malnourished children (both SAM and MAM) who were not attending the programme. A list of questions or ideas was developed and used in interviewing the main stakeholder (mothers/caregivers) of the programme (Annex 6b).

3.3. STAGE 3 ‘WIDE AREA SURVEY’

Stage three is the final stage of the SQUEAC survey, when the assessment teams actively look for acute malnourished children from the selected sampling frame to see if they are in programme or not in programme. In this stage, a Bayesian-SQUEAC technique was used to estimate the sample size. This technique includes an estimation of the prior and prediction of coverage before conducting a Wide Area Survey to calculate a minimum sample size (active cases to be found) for the survey. Ultimately, the survey data uses to estimate the programme coverage.

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Setting of the ‘Prior’ The ‘Prior’ is generally set using the prior information such as information from stage one and two to make an informed assumption about the most likely coverage value and then express it as a probability density.

Prior for SFP coverage survey: Figure: 3 Prior for SFP coverage, Tdh, Kurigram Based on the findings from stage one and two the assessment team decided to calculate the sample size for the ‘Wide Area Survey’, (3rd Stage), assuming that the SFP programme coverage is likely to be around 65%. With this assumption the ‘mode’ was set at 65%, with speculation of lowest possible coverage 40% and highest possible coverage 90%. The prior was then described using the probability density Alpha prior=20.6 and Beta prior= 11.1 using Bayesian-SQUEAC software (see Figure 3).

Prior for OTP coverage survey: Figure: 4 Prior for SFP coverage, Tdh, Kurigram Using similar process prior was set for OTP coverage. It was assumed that the coverage for OTP is going to be little lower than the SFP therefore the ‘mode’ was set to at 60%, with the speculation of lowest possible coverage 40% and highest possible coverage 80%. The prior was then described using the probability density Alpha prior= 18.7 and Beta prior= 12.8 (Figure 4)

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Estimation of Sample size and sampling frame: The Wide-Area Survey sampling covered the entire programme catchment areas by adopting a spatial sampling method. A two-stage sampling procedure was employed to estimate the sample size and sampling frame.

Sample size requirements were calculated, using simulation with the Bayesian-SQUEAC calculator.

For SFP: to provide a coverage estimate with a 95% credibility interval and ±8% precision, therefore the Bayesian SQUEAC calculated minimum sample size was, n =87, current MAM cases, either in programme or not in programme.

For OTP: to provide a coverage estimate with a 95% credibility interval and ±14% precision, therefore the Bayesian SQUEAC calculated minimum sample size was, n =30, current SAM cases, either in programme or not in programme.

Sampling area selection To estimate number of para/sub-village to be sampled following data was used: i) the proportion of the population living in the survey area, ii) percentage of population age less than five years old (according to census report) and iii) prevalence of MAM (4.5%) and SAM among those age group in the survey area (from the latest iv) prevalence of MAM (4.5%) among those age group in the survey area (from the latest nutrition survey report) of to find 87 MAM and 30 SFP cases.

Spatial Representation In order to achieve spatial representation, a map of the Kurigram municipality, Thanahat and Gogahada union, showing all villages and CNCs was drawn. The map was divided into equal sizes of a quadrant, the Kurigram map that yielded 40 squares, Thanahat and Gogahada yielded 22 and 12 squares respectively. In total, 16 quadrats for Kurigram, 12 for Thanahat and 8 for Gogadaha union were selected to cover all three target areas, excluding quadrats made up of less than 50% landmass. All selected quadrants areas were further divided into a list of its composite para/sub-villages and to identify comparable primary sampling units and to ensure that sampling could be completed within the specified time period. Name of the Para/sub-village in each square (Quadrant) was listed separately. One sub-village closest to the centre of each of the quadrants was selected as a sampling area for the survey.

To find SAM, MAM cases and recovering cases of SAM and MAM, a door to door case find was used, which was similar to the ‘Small Area Survey’. This method allowed for the inclusion of all, or nearly all, current SAM & MAM cases in all 40 sampled para/sub-sections. As anticipated that almost all children in the 40 para has been measured within two days of wide area survey to find both active and recovering SAM and MAM cases. After surveying 40 para by 8 to 11 team 11 SAM and 93 MAM cases were found. Cases that were ‘not in the CMAM programme’ were referred to the nearest SFP or OTP, as appropriate.

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4. RESULTS

4.1 STAGE 1 PROGRAMME ROUTINE DATA & CONTEXTUAL DATA

Data collection: In this stage quantitative and qualitative data was collected and analysed. The routine programme monitoring data was gathered and analysed using CMAM programme data base. The qualitative information was collected from the key informants using different methods in line with the SQUEAC assessment guidelines.

4.1.1 Programme Routine data analysis (dataset)

The programme routine data used was from August 2012 to July 2013 for the SFP programme. The full year data for OTP was not available therefore some sample data was collected and analysed for some indicators and reported on by percentage and in actual number as appropriate.

Admission data  Admissions trend and seasonal calendar (disease, hunger gap etc.)  Admissions by MUAC (MUAC status)  Admission and age of children

Programme performance indicators  Cured  Defaulters’ trend and seasonal calendar (labour period, migration etc.)  Death  Non responded  Transferred cases  Length of Stay before cured discharged

Defaulter’s data: Defaulter trend and labour calendar

SQUEAC utilises programme’s routine monitoring data that are accessible and directly related to programme’s quality of service to assess three things: i) the accuracy and appropriateness of the data related to the coverage & programme performance, ii) whether or not a programme is responding well to the demands of its context, and iii) whether there are specific areas within the programme’s target area expected to have either relatively low or high coverage. This data is also analysed separately for comparison with the changing and seasonal context of the targeted area.

Then the routine data is compared to international standard indicators (SPHERE) related to the context of the implementation area. This is t o assess the programme’s capacity to respond to changes in demand for its services.

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Admissions data

OTP Admissions and Seasonal Trend: Diseases and Hunger Gap The SFPs in Kurigram that implements by Tdh have admitted 2231 children with 87% successfully cured, from August 2012 to July 2013. During the same period in OTP 104 children were admitted and 80% of them successfully got cured. The low number of admission in OTP was due to programme closer from January to April 2013, for short supply of RUTF.

OTP admission and seasonal trends The graph below showing admission trend for SFP and OTP and compared with the seasonal calendar. The assessment team in consultation with the community identified the different seasons of the year and the season of the peak of childhood diseases. According to the seasonal calendar below, ARI, pneumonia diarrhoea and skin disease are linked with winter season. However, the peak season for malnutrition seems to be November to January which is correlated to increased illness during winter season and hunger gap/monga. The figure below (Figure 5), indicated that the programme admissions in some extent follow the seasonal disease pattern and seasonal variation i.e. monga season.

Figure: 5 Pattern of Admission in SFP & Diseases and hunger gap Calendar, Kurigram

# of admission Smooth SAM and MAM Tdh Kurigram, November 2013

300

250 MAM 200 SAM

150 # of # children 100

50

0 Aug-12 Sept -12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 April-13 May-13 June-13 Jul-13 Rainy season Winter season Dry season Rainy Dysentery ARI Pneumonia Chicken pox Skin disease Diarrhoea Sore Hunger/Monga Diarrhoea eyes

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Admission to OTP by age group

From the admission data of Tdh CMAM programme, July 2012 to October 2013, it was found that over 76% of children who were admitted to SFP and OTP were aged between 6 to 24 months. From 43 to 59 months there were fewer admissions. This pattern of admissions and age group in Kurigram follow the general trend of communities where infant and young child feeding practice is inadequate (Figure: 6).

Figure: 6 CMAM prog. admission and age group, Tdh Kurigram, Nov. 2013

OTP and SFP admission by age group, Tdh Kurigram, July '12 Oct. '13 1,400

1,200

1,000 SAM

800 MAM

600

# of # Children 400

200

0 6-12 13-18 19-24 25-30 31-36 37-42 43-48 49-59 Age by Month

MUAC at the time of admission in SFP and OTP The CMAM programme’s admission MUAC data allows the programme team to understand the timeliness of care-seeking behaviours of communities as well as the pro-activeness of the community health and nutrition worker on early screening and referring of cases to the CMAM programme. The admission MUAC for both OTP and SFP was analysed and median admission MUAC was calculated for both.

OTP Admission on MUAC: Figure: 7 Admission based on MUAC in OTP (<11.5cm), Kurigram The median MUAC of OTP admission was found to be 11.3 and 78% children was admitted in OTP with MUACs between 11.4cm to 11.1cm. There were no cases admitted with oedema during this period. It is therefore indicated that the programme identifies children early, refer and admit them also the communities are seeking/accepting early treatment for their children.

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SFP Admission on MUAC: The admission criteria used by Tdh SFP was only MUAC. The median MUAC of SFP admission was found to be 12.3cm and about and 65% cases were admitted with MUAC between 12.4cm to 12.1cm. Therefore it is indicative of early case findings and case management in supplementary feeding programmes.

Figure: 8 Admission based on MUAC in OTP (<11.5cm), Kurigram

Programme performance indicators The programme performance indicators are the number of children who exited from OTP (number of exit cured, defaulter, and death etc.), compared to the number children who entered the programme. Percentages were used to assess the effectiveness of the programme from August 2012 to July 2013 compared with the SPHERE minimum standards.

The graph below showing the performance of the Tdh Kurigram SFP programme and the data were compared with the SPHERE standards (Figure: 10).

Indicators SFP OTP SPHERE Cured 87% 80% >75% Defaulter 4% 10% < 15% Death 0.08% 0% < 10% Non respondent 9% 10% Transferred 0.04% 0%

SFP and OTP performance data from Kurigram determined that all performance indicators are within the SPHERE minimum standard. The SFP and OTP data shows that the cure rates are high (87% and 80%) and the defaulter rate is low (4%), see figure below.

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Figure: 9 Programme Performance Indicators, Kurigram

Performance indicators, Smooth TDH Kurigram, Aug 2012 to July 2013 100

80 % Cured Discharged % Death 60 % Non 40 responder # of # Children % Defaulted 20

0 Aug-12 12-Sep Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 April-13 May-13 June-13 July-13

Length of Stay (LoS)

Length of Stay (LoS) in OTPs is an important performance indicator to assess the average period needed by the programme to cure a child from SAM or MAM.

The Tdh Kurigram OTP programme shows that the median length of stay for SAM cases admitted in Kurigram OTPs was 9 weeks, which is little above than the expected median length of stay in OTP. It is also calculated that 40% of children are discharged cured from the programme by 4 to 8 weeks.

Figure: 10 Length of Stay in OTP, Tdh Kurigram, Nov 2013

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Defaulters’ data

Analysis of defaulter’s data vs. Labour demand trends for SFP

Defaulters in CMAM programme are classified as uncured cases that have discontinued the treatment. In Kurigram programme the numbers of defaulters were examined to determine if it is worryingly high and if it follows the seasonal context over time.

The graph below indicates that there is some relation with defaulter rate and seasonal activities. The high defaulter rate was found in months of September and October and this may associate with the seasonal migration. Defaulter’s rate again increased in April which may have some link with harvesting activities. However based on the available data, the overall rate of default was 10%, which is within the SPHERE standards (figure below 10). This means once mothers are in programme most of them continue with the treatment of their children.

Figure: 11 OTP Defaulter and Labour demand calendar # of Defaulter SFP prog. THD Kurigram, Nov, 2013 14

12

10

8

6 # of # children 4

2

0 July-12 Aug-12 Sept. '12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 April-13 May-13 June-13

Rainy season Winter season Dry season Planting Harvesting Planting Harvesting

Migration

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The database and OTP record keeping: The OTP data provided by the team were useful and allowed the analysis of multiple indicators of the CMAM programme. The data were found consistent enough however, some data were missing to get a comprehensive analysis on different indicators.

As part of field data collection, in some selected OTPs and SFPs the admission cards and registers have also been examined by the assessment team and some information was compared with the compiled database provided by the team. While conducting these checks in OTPs and SFPs some inconsistencies were found and noted. Out of all cards cheeked by the team 88% of SFP cards 98% OTP cards were found to be filled correctly. The cards that were incorrectly filled were found with following errors: admission date not matching with the beneficiary’s cards. Admission criteria recorded incorrectly, absent date not marked correctly.

4.1.2. QUALITATIVE DATA COLLECTION Qualitative data were collected from the eight villages from three Union of Kurigram districts. Four village were selected near to CMAM service centres and another four was selected from a far away from CMAM service centre including one village from Char area, the riverine island. The aim of collecting qualitative data is to allow further detailed development of the coverage hypotheses and an in- depth analysis of the existing information and routine programme data described in the previous section. This data also provides vital information concerning the underlying causes of low or high programme coverage, including key barriers and accessibility of the services. The data was then separated and levelled using the BBQ (Boosters, Barriers and Questions) approach. These three issues recorded separately and analysed: (1) Boosters, (2) Barriers and (3) Issues that need more investigation listed as questions. Findings of qualitative data that there was no difference in knowledge and attitudes towards the CMAM programme in areas far away from CMAM service centre and areas near to CMAM service centres. Also there were no major difference observed in knowledge and attitude between the communities in char area and the main land.

Findings from the qualitative assessment

The sources:

1. Village Leaders In total 13 village leaders were interviewed individually from 9 sub-sections. Of these 8 were male leaders and 5 were female leaders. Using the village selection criteria for this assessment about 50% leaders were interviewed from the village that are near to the CMAM service. There were no marked difference found between the leaders on their knowledge and their involvement of CMAM programme including the leader from the char area.

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2. The Religious Leader Nine religious leaders were interviewed between near and far away villages from the OTP service centres. Most of them are aware about the programme and their knowledge on malnutrition found to be good. However, they mentioned that they were not briefed on the programme officially.

3. Traditional Birth Attendants Using key Informant Interview technique 6 TBAs were interviewed from selected villages far away and nearby CMAM service centre. It was found that most of them are aware about the programme and they referred children to the CMAM programme. Their sources of information on this programme are various Tdh’s activities and the beneficiaries of the CMAM programme.

4. Village Doctors Nine village doctors were interviewed from eight selected village between nearby and far-away of CMAM service centre. The interview also revealed that 50% of the village doctors treat children who have malnutrition. Most of them treat their children with Zinc, Dompridone, vitamins, and China’s medicine.

5. NGO workers Two NGO workers were also interviewed during the assessment; both of them were informed about the programme by Tdh staff. They also said they refer children to CMAM programme when they find them with malnutrition.

6. Health Centre staff (CNPs, GMP, supervisors) Altogether 14 health centre staff who are directly involved in implementing the CMAM activities were interviewed in six different health centres. Their knowledge about CMAM protocol was good. However, some of them have mentioned about their high workload and long geographical distance they covered.

7. OTP mothers/caregivers Forty five mothers of children that were admitted to CMAM programmes at the time of the assessment were interviewed. Most mothers/caregivers found to have correct knowledge on the cause of malnutrition of their children.

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The main findings from various sources:

Issues Description

Knowledge of the After interviewing and conducting FGDs with various community members it was CMAM programme determined that all most all of the community members are aware about the CMAM programme but their participation in the programme is inadequate. Some of the key

informants reported that they were not formally introduced to CMAM programme by the implementing agencies. Therefore their involvement in the programme was limited.

Knowledge about The question on knowledge of malnutrition included the causes and general signs of malnutrition malnutrition. Most community members seemed to know the basic signs of malnutrition. Regarding the causes of malnutrition, most were able to cite some of the correct causes such as disease, poor care practice practise, early marriage etc. There was no stigma around malnutrition was reported by anyone during the qualitative data collection.

Village Doctors, Key community leaders/stakeholder were claimed that they were not formally TBAs, Religious informed about the programme. However, they came to know about this leader were not programme informally from the beneficiaries and from the programme team. The formally introduced religious leaders (Imams) were mentioned that if they were formally known about on the programme the programme they would have informed the community during the Friday prayer.

High work load for In FGDs the workload of the CNPs and other support staff of the CMAM field staff. programme were mentioned by the SFP/OTP staff. It was also discuss with the programme team that each CNPs are allocated with 1500- 3000 House Hold and each supervisor are allocated to supervise 3-12 staff.

CMAM protocol not The CMAM programme data showed that information on defaulters, absent, home followed properly visits are not recorded on cards, registers. The team mentioned that the CMAM on home visit i.e. programme team are not giving enough attention to home visit for defaulters or to defaulter, absent, follow the sick children at home. This was again due to work load and lack of sick. proper planning

Common practice of Almost all key informants and the assessment participants were mentioned about early marriage the practice of early marriage and giving birth at early age. These young mothers hence early give birth of premature children also do not know how to take care of young pregnancies children.

Some village doctors In Kurigram some Village Doctor were found to be treating malnutrition. However, treat malnutrition these practises are reducing as services for acute malnutrition are available at community level.

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Boosters and Barriers The scoring was done by the assessment team based on the weight of each element. The scale used rating from 0 to 5.5 to score for both ‘barriers’ and ‘boosters’ (Figure 2). The team scored each booster and barrier separately as it was expected that the scoring would differ among the groups. However in this case the scoring did not differ in great extent. The final scoring for each booster and barrier was agreed and assigned by using the average score. These average score for each category were added to “build up” the coverage score. The scores of Boosters are added to zero (i.e. lowest possible coverage) and the scorers of berries are “subtracted” from 100% (i.e. highest possible coverage). Using the averages scores from boosters and barriers the expected coverage values with upper and lower expected values of coverage were then set to test (Table-1).

Table: 1 Boosters & Barriers, TDH Kurigram, November, 2013 Boosters Values Values Barriers

Knowledge of malnutrition 3.5 1.5 Knowledge of malnutrition Knowledge of CMAM programme 3.0 2.0 Role in the programme Knowledge of malnourished children in the 3.25 1.75 area Lack of training Role to the CMAM programme 2.5 2.5 work load of staff Community received information from Tdh 3.75 2.5 Lack of BCC Appreciation of the programme 2.5 3 Insufficient community mobilization Involve and participation in the programme 2.5 2.75 Long distance between GMC and CNC Stigma on malnutrition 4.25 3 Inadequate follow up/home visit Strong M&E 3.5 2.25 Gap between referred and admission Complete CMAM package 4.75 1.5 Understanding of Default and non - responder and readmission Social campaign and BCC 2.5 1.75 Appreciation by the community Community training 1.75 2.5 Lack of proper Supervision Good staff training 3.25 2.25 Lack of coordination between stakeholders Staff commitment 4 Supervision and Feedback 2.5 Less staff turnover 3 Good Material Supplies 4.25 Good coverage of Small Area Survey 3.25 Added to Minimum Coverage (0%) 58+0 100- Subtracted from Maximum 29.25 Coverage (100%) 58+ 70.75= 128.75 ÷2 Coverage speculation 64% Alpha prior value (SFP) 20.6 11.1 Beta prior value Alpha prior value (OTP) 18.7 12.8 Beta prior value

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4.2 STAGE 2 ‘SMALL AREA SURVEY’

A small area survey was carried out to test the hypothesis that was generated in stage one after gathering and analysis the qualitative and quantitative data.

Hypothesis OTP routine data on admission and qualitative information indicated that some OTP and some SFP sites have high admission. Also some OTP and SFP sites have low admission. Form the admission data it has been hypothesised that; OPTs and SFPs that have high admission have high coverage rates while OTPs and that have low admissions have low coverage rates.

To test the hypothesis eight CNC sites were selected systematically and surveyed to see whether areas with high admissions indeed have high coverage and areas with low admission indeed have low coverage. The survey sample size was the number of children with acute malnutrition found by the surveyors. A coverage threshold of 50% for rural area (based on SPHERE standards) was defined as adequate coverage.

4.2.1 Findings of Stage 2 Assessment

Out of 32 SFPs/OTPs, 4 SFPs/OTPs with low admission and 4 SFPs/OTPs with high admissions were selected. High and low admission was defined by number children under the age of five years in the area vs. the percent of children under the age of five years admitted to the OTPs with SAM. See table below:

Table: 2 CNCs with high and low Admission CNC % of U 5 children CNC % of U 5 children Low Admission admitted with High Admission admitted with Union MAM SAM MAM SAM Kurigram Pal para 3% 0% Shouhardho para 67% 5% Kani para 7% 1% Char Velacopa 52% 8% Gogadaha Laxmir Khamar 14% 0% Char Rawlia 79% 5% Thana hat Chilmari 14% 1% Razar vita 20% 0%

Active cases found In eight surveyed for ‘Small Area Survey’ in total 44 MAM and 5 SAM cases were detected, which some were found in programme and some ‘not in programme’.

Table: 3 Active SAM and MAM cases found ‘Small Area Survey’ STATUS TOTAL CASE FOUND IN PROG. NOT IN PROG.

MAM 44 28 16

SAM 5 3 2

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Decision rule for MAM Decision rule MAM CNC/Para with High coverage CNCs/Para with Low coverage

In SFP high admission area 22 MAM cases were In SFP low admission area 22 MAM cases were detected and 14 cases were found in programme. detected and 8 cases were found ‘not in Out of 22 children 11 children need to be in programme’. Out of 22 children at least 12 programme for 50% coverage confirmation. children need to be ‘not in the program’ for confirmation of less than 50% coverage.

As 14 is >11 this part of hypothesis was confirmed. As 12 is >8 this part of hypothesis was Therefore CNCs with high admissions do have confirmed. Therefore CNCs with low higher coverage. admissions do not have low coverage.

Decision rule for SAM Decision rule SAM CNCs/Para with High coverage CNCs/Para with Low coverage

In OTP high admission area 3 SAM cases were In OTP low admission area 2 SAM cases were detected and 2 cases were found in programme. detected and 1 case was found in programme. Out of 3 children 1.5 children need to be in programme for 50% coverage confirmation. As 1 is = to 1, this part of the hypothesis cannot be confirmed due to the low number of SAM As 2 is <1.5 this part of hypothesis was confirmed. cases found Therefore CNCs with high SAM admissions do have higher coverage.

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4.3. STAGE -3 ‘WIDE AREA SURVEY’

The Wide Area Survey was carried out to estimate the programme‘s likelihood coverage (see methodology section: 3). For this survey 40 subsections/para was selected from three union to find the sample by using same case findings method used in ‘small area survey’ (table: 5).

4.3.1 Findings of Wide Area Survey

Cases found in different communities: From the 283 targeted para 40 (Kurigram 20, Gogadaha 9, Thanahat 11) para/sub-sections were selected and surveyed for case findings of both SAM and MAM.

Children identified with SAM: Forty para was surveyed but only SAM cases found in 11 para using MUAC measurement. Out of those 11 cases 7 were found to be in programme while 4 cases found are not in programme.

Table: 4 Tdh Kurigram CMAM programme SQUEAC wide area survey results for SAM –November, 2013 # Cases in # Cases NOT in the the # Recovering Cases CNC sites Village Para programme programme In the Prog Ghogadaha CNC Khamar Khamar 1 0 0 Kachirchar Kachirchar 1 1 1 Kamar khali Kamar khali 1 0 0 Rashulpur Rashulpur 1 0 1

MCHC Chilmari Kostari Kostari 0 1 1 Boro kustari Boro kustari 0 1 0 North dakua North dakua North dakua para para para 1 1 0

MCHC Kurigram Boishno para Boishno para 0 0 1 Ekotapara Ekotapara 0 0 1 Sawdagorpara Sawdagorpara 1 0 0 Tapu vela kupa Tapu vela kupa 1 0 0 Total 7 4 5

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Children identified with MAM: Forty para was surveyed, 93 MAM cases found from 30 para using MUAC measurement. No MAM cases found in ten para. Out of those 93 cases 68 were found to be in programme while 25 cases found are not in programme.

Table: 5 Tdh Kurigram CMAM programme SQUEAC wide area survey results for SAM –November, 2013 CNC site Village Para/Subsection Total # Cases in # Cases # MAM the prog. NOT in Recovering cases the prog. Cases In found the Prog Bozratabokpur CC Filamari Filamari 2 1 1 0 Kesamotbanu CC Shorkarpara Shorkarpara 7 5 2 0 Kesamotbanu CC Shordarpara Shordarpara 0 0 0 1 Laxmirkhamer CC Shovondaha Shovondaha 3 3 0 2 Moratary CC Moratary Moratary 7 4 3 1 FWC Ghogadaha Khamar Khamar 1 1 0 0 Kachirchar CC Kachirchar Kachirchar 10 6 4 0 Kusraprara Purbo macha Purbo macha 5 3 2 0 bandha bandha FWC Ghogadaha Moddho kamar Moddho kamar 1 0 1 0 haillah haillah Rasulpur CC Rasulpur Rasulpur 4 4 0 4 Chilmari OPD Kustari Kustari 1 0 1 0 Choto kustari Choto kustari 3 0 3 0 Macha bandhacc Kani para Kani para 1 0 1 0 Khusrapara Khusrapara Khusrapara 5 4 1 0 Uttor dakua para Bagdobarpar Bagdobarpar 0 0 0 2 Uttor dakua para Uttor dakua para 2 2 0 6 Puraton station Munshi para Munshi para 3 3 0 2 para Kurigram-OPD Boishno para Boishno para 0 0 0 2 Noya gram Noya gram 1 1 0 0 Sowdagorpara Sowdagorpara Sowdagorpara 6 6 0 0 Powerhouse para Kobiraj para Kobiraj para 3 2 1 0 Puraton station Puraton station Puraton station 2 2 0 0 para para para Sowdagorpara Tanari para Tanari para 5 5 0 0 Hamid para Hamid para Hamid para 1 1 0 1 Ekota para Ekota para Ekota para 4 3 1 1 Karimer khamar Karimer khamar Karimer khamar 7 7 0 0 Char velakupa Tapu vela kupa Tapu vela kupa 6 3 3 0 Nazira Munshi Munshi para Munshi para 2 1 1 1 para Mondol para Bepari para Bepari para 0 0 0 1 Mondol para Mondol para 1 1 0 5

Total 93 68 25 29

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4.3.2 COVERAGE ESTIMATION

To estimate the programme coverage rate data from the ‘Wide Area Survey’ the Bayesian-SQUEAC prior and survey data was used. In Bayesian-SQUEAC calculator the survey data was inserted in pre-set prior (mode, alpha prior, beta prior, pre-set precision) to estimate the final coverage. For this survey only point coverage was estimated and reported.

Point Coverage

Number of current (MAM/SAM) cases that are attending the programme Number of current (MAM/SAM) cases that are attending the prog. + number of current (MAM/SAM) cases not attending the programme

Estimation of SAM Coverage: Using the Bayesian-SQUEAC Calculator: ‘Coverage’ as denominator (11) and numerator (7) was inserted to Bayesian-SQUEAC calculator while same Alpha and Beta values have been (α 18.7 β 12.8) and precision 14% used from the pre-set ‘Prior’. The ‘Point’ coverage is estimated at 61.0% rate with Credible Interval (CI- 45.7% - 74.4%), z= 0.21, P value=0.8329. Therefore the z-test revealed that there is a no conflict between the ‘prior’ and the ‘posterior’. See graph below:

Figure: 12 Point coverage SAM, Kurigram Baysien-SQUEAC graph

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Estimation of MAM Coverage: Using the Bayesian-SQUEAC Calculator: ‘Coverage’ as denominator (93) and numerator (68) was inserted to Bayesian-SQUEAC calculator while same Alpha and Beta values have been (α 20.6 β 11.1) and precision 8% used from the pre-set ‘Prior’. The ‘Point’ coverage is estimated at 71.4% rate with Credible Interval (CI- 63.2% - 78.7%), P value=0.4545. The z-test revealed that there is a no conflict between the ‘prior’ and the ‘posterior’. See graph below:

Figure: 13 Point coverage MAM, Kurigram Baysien-SQUEAC graph

4.3.3 BARRIERS TO ACCESS IDENTIFIED BY WIDE AREA SURVEY

Wide area survey interviewed the mothers/caretakers of SAM and MAM cases who found to be ‘not attending the programme. The interview included if they know the condition of their children and if they know the programme that can treat acute malnourished cases. See Table 6 below reported knowledge for both groups of SAM and MAM cases:

Table: 6 Mothers/caretakers knowledge of the status of their children and programme, Kurigram Questions Yes - # (%) No - # (%) SAM MAM SAM MAM Is your child malnourished 1(25%) 13(52%) 3 (75%) 12(48%)

Do you know programme that can help your child 4(100%) 18(72%) 0(0%) 7(28%)

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Reasons that made mothers/caretaker of SAM cases for ‘not to attend’ the programme: Findings of the ‘Wide area survey’ in Kurigram, out of 11 active SAM cases 4 cases were found to be ‘not attending in the programme’. When those 4 mothers/caretakers were asked if they know about the nutritional status of their children, 25% of the mothers/caretakers said they know while 75% mother/caretaker said they do not know. All mothers (100%) said that they were aware of the programme.

Figure: 14 Reasons given by the mothers of SAM cases being ‘not in programme’

Reasons given by mothers of SAM cases for 'not been in programme, Kurigram, Nov 2013

Migrated to this area

Not aware about child condition

0 0.5 1 1.5 2 2.5 3 3.5 # of respondents

Reasons that made mothers/caretaker of SAM cases for ‘not to attend’ the programme: Out of the 25 mothers/caretakers of MAM cases that were ‘not in programme’ among those 12 mothers/caretakers were found not to be aware of the condition of their children. Out of 13 mothers/caretakers who were aware about the condition of their children, 4 were not aware about the facilities which can treat their children and 4 were non-responder cases, 2 were migrated in the area recently. Reaming mothers were cited other various reasons for not taking their children to the health facilities (see Figure 14).

Figure: 15 Reasons given by the mothers for being ‘not in programme’ Reasons given by mothers of MAM cases for 'not been in prog, Kurigram, Nov 2013 Not aware about child's condition

Not aware about prog.

Non responders

Migrated to the area

Father sick

Child couldn't take solid food

Gardian have no trust on the…

0 2 4 6 8 10 12 14 # of respondents

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4.3.3.1 THE MAIN BARRIERS AFFECTING THE PROGRAM

Key Barrier Identified Effects on access and coverage Inadequate community sensitization Findings from the contextual data indicated that the community sensitization on CMAM programme is not adequate to attain highest programme coverage.

Insufficient role played by some Some communities found are aware about the CMAM community members. programme but they are not involved as they are not clear on their role to this programme such as the religious leaders and TBAs. Village doctors, TBA, Religious leader Programme failed to include them on the programme from were not formally informed about the onset as a result some village doctors were treating programme. malnourished cases other than referring to the CMAM programme.

Insufficient/ ineffective knowledge on IYCF practice in Kurigram found to be insufficient. Early IYCF and practice of early marriages. marriages, young age pregnancies and giving birth to a child at young age were identified as some of the main reason of malnutrition by the community and the programme staff.

Long distance between center and The programme closed down some of the SAM and MAM community facilities due to reduced case load. Therefore some community finds long distance between their village to center when need to attend the programme.

High rate of migration Due to geographical location people in Kurigram face problem such as river erosion and flood lead to poor availability of work and Monga (hunger). So people migrate to different area in search of work mainly male members and some time the entire family.

High work load for field staff. House Distribution of house hold for each staff varies, therefore, Hold ranges from 1500- 3000. frequency of screening varies and early case findings for some Supervisor and supervisee ratio: 3-12 area may have compromised. staff.

Coordination gap among TDH staff in The team also identified that there is coordination gaps different sector. between CMAM team and other field worker. If they can better coordinate their work the coverage may increase further.

Lack of quality supervision This issue has been brought by the team that sometime quality supervision by the manager is not possible due to the ratio of supervisor and supervisee. The ratio rage from 1:3 to 1:12.

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5. DISCUSSION

5.1 PROGRAMME ROUTINE DATA FROM OTP CARDS & REGISTERS

Programme routine data was collected from the OTP cards and SFP registers from August 2012 to July 2013. Issues highlighted below were revealed during data gathering and data analysis.

OTP Record keeping According to the database during the programme period 104 SAM cases and 2231 MAM cases were admitted in various OTP and SFP sites that run by the Tdh in Kurigram. The database was found to be consistent enough for different indicators. However, data on defaulter and absent cases were not recorded properly as they were not followed up regularly.

The OTP registers and cards have also been examined by the team and most information was compared with the compiled database. Most cards and registers were found to be filled properly and very little inconsistencies were observed between cards and registers. This is expected when the programme is completely run by the NGO.

Performance Indicators

Defaulter information From August 2012 to July 2013 data reported 4% children were found to be defaulted from OTP while 10% from SFP. The defaulter rate was found to be very within the SPHERE standards. However, detailed information on defaulted children, such as why the children had defaulted and follow up efforts, was not available. The health facility staff mentioned that there were no regular defaulters follow up visits carried out, therefore no information on defaulters are available. The defaulter information is vital for the quality check of this programme. Therefore it is advised in future defaulter information is recorded and used to ensure that defaulters’ children are followed up.

Length of Stay (LoS) Length of stay is an important indicator to assess how long children are in programme, how they are cared for and how they have responded to the treatment. The LoS data were available only for the OTP admission. The median LoS in the OTP was found 9 weeks which is within the expected LoS in OTP programme. This means that once children are in the programme they get good care and responded to the treatment positively.

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5.2 PROGRAMME CONTEXTUAL DATA FROM THE COMMUNITIES

Insufficient community mobilisation Community mobilisation is one of the key components of the CMAM approach. Findings from the contextual data indicated that the community sensitisation on CMAM programme is not adequate to attain highest programme coverage. Most of the assessed communities found are aware about the CMAM programme. However, not all of them are involved as they are not clear on their roles to this programme which resulted to a low level of community participations.

Issues around Screening, referral and admission Generally the CMAM outreach protocol recommends conducting screening once a month to detect malnourished children from the communities and refer to CMAM programme. In Kurigram the GM worker measures the children 0 to 59 months every month for their allocated area. Also refer cases if identified as acute malnourished. However, due to set date for the OTP and SFP services instant admission may not happen so mothers have to wait with their children to be admitted. This waiting period can be as long as two weeks between case detection and admission. Sometime this period demotivate the mother to report to the CNC for admission. Also within this waiting period child status may get changed for better or worse. This situation is good for attaining optimal coverage; better status could lead to refuse to admission while worse status may lead to complication. The programme needs to work on a strategy to shorten the waiting period.

Village doctors treating acute malnutrition cases Some village doctors were found to be treating malnourished cases using some modern medicines. However, this practice is reducing as more and more village doctors are getting information on CMAM programme. Also regular growth monitoring programme help early case detection and referral to CMAM programme. However, the programme need to address this issue and work with the village doctors, explain the CMAM programme, train them on MUAC measurements, so, they can identify cases and refer them, if needed.

Early marriage and poor IYCF & care-practice From the discussions with community key stakeholder, it was found that one of the causes of acute malnutrition is possibly due to poor IYCF practices. As mentioned before early marriages practise is endemic in Kurigram rural area. Early mirage leads to young age pregnancies hence low birth weight child, moreover young mothers do not know how to take proper care of children. The OTP admissions data also show that more than three quarters of admissions (76%) are between the ages of 6 to 24 months. This indicates poor IYCF practices in targeted communities.

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Specialised Nutrition Unit (SNU) The SNU is completely run by Tdh, a rapid visit to the SNU by the assessment team found the care for children with SAM with complications is excellent. However, for long run this kind of approach may pose question on sustainability. Tdh needs to work on this to ensure government facilities are also strengthen and their capacity is built to provide services for the SAM cases with complication

5.3 WIDE AREA SURVEY

From wide area survey data estimated that the ‘point coverage’ for SAM was 61% and for MAM was 71.4% for Kurigram CMAM programme. This coverage rate is very good for a rural setting. To increase further access to programme and the programme coverage the team needs to focus on community mobilisation and ensure community takes active part in this programme.

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6. CONCLUSION

The CMAM programme that has been implemented in Kurigram by Tdh is a very young and a new programme started in April 2012. The programme achievement is more than satisfactory within this short period.

The routine programme data showed that the programme has admitted and has successfully treated both MAM and SAM cases. The performance indicators (cured, death, and defaulters) are all found to be within the corresponding SPHERE standards.

The community outreach strategy needs to be revisited to increase access to these services. Communities’ involvement and participation of this programme needs to be further increased by sharing information on CMAM in community meetings on a regular basis. Involving community groups and training for some special group like village doctors and skilled TBAs are recommended to gain higher coverage. The outreach strategy also needs to address the issues on case better identification strategy, timely referral and admission, and home visits for sick, absents and defaulters. The programme also needs to work with other likeminded NGOs/partners to address the issue on early marriages and delay pregnancies for young couples.

Survey data collected in Stage 2 and Stage 3, through the Small and Wide Area surveys suggests that coverage is satisfactory following the SPHERE minimum standard set for rural areas. In the coming years, the programme will need to continue to conduct coverage monitoring on a yearly basis to determine if there has been further improvement to service qualities and any change in programme coverage rate.

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7. RECOMMENDATIONS & ACTION PLAN

The SQUEAC exercise identified both boosters and barriers that increased and prevent access to the services of the CMAM programme respectively. However, the barriers that were identified recommendations were made based on them in order to take measures to remove or minimize those barriers to further improve the programme coverage.

7.1 SPECIFIC RECOMMENDATION

Barrier Identified Key recommendation made Inadequate community sensitization - CMAM training for CC management group (13 people in each group). - CMAM training for Ward health committee. - Awareness for Primary school children (govt. and non govt.) - Nutrition fare (breast feeding day) In sufficient role played in some - Regular (6 monthly) meetings with key stakeholders such as communities. village leaders, religious leaders, and TBAs. Village doctors, TBA, Religious leader - Organize one day CMAM programme inception training for the were not trained/formally introduced key stakeholders. to the prog. High work load for field staff. HH ranges Task analysis; day/staff calculation for optimal task allocation. from 1500- 3000. Supervisor: 3-12 staff. - Review field staffs job description. - Ratio of supervisor: supervisee. Insufficient/ ineffective knowledge on - Staff training on IYCF. IYCF - Session plan and implementation plan for community/ mothers in terms of IYCF. Long distance between center and - Rearrange CNCs according to need to avoid distance. community CMAM protocol not followed properly - Refresher training for CMAM staffs. on home visit, default, absent, sick. Difference between ref. date and - Discussion between program partners to reduce waiting period. admission date (waiting period) is maximum 2 weeks. Lack of quality supervision - On the job training for area supervisors. - Effective use of supervision tools. Common practice of early marriage - Plan for integration for other activities. among rural population in Kurigram. High rate of migration. - Identify vulnerable families with mal nourished child and link them with food security livelihood program. Coordination gap among TDH staff - Review the coordination meeting and try to make the meetings more programs focused. Further strengthening between different program staff.

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7.2 ACTION PLAN

Some key actions below that need to be taken forward in order to eliminate or reduce the effect of the key barriers to improve the service quality and increase the programme coverage.

Action Plan from SQUEAC assessment- Kurigram November 2013 Issues/recommendations Time frame Responsible person Resource needed

- CMAM training for CC management group (13 From Q1, 2014 Area Supervisor Fund +Time + people in each group). (AS) planning - CMAM training for Ward health committee. Programme Officer - Awareness for Primary school children (govt. and (PO) non govt.) Programme Officer - Nutrition fare (breast feeding day) (PO) training - Regular (6 monthly) meetings with key Q2 and Q4, AS, PO, PO training Fund +Time + stakeholders such as village leaders, religious 2014 planning+ leaders, and TBAs. Training materials - Organize one day CMAM programme inception From Q2 PO training, Fund +Time + training for the key stakeholders. Director health, planning+ RMO, Training materials Task analysis: day/staff calculation for optimal task Discuss in next Director Health and N/A allocation. MCM Nutrition - Review field staffs job description. (Monthly Director program. - Ratio of supervisor: supervisee. Coordination Meeting) by DHN. - Staff training on IYCF. Training in Q1 PO training, Fund+ training - Session plan and implementation plan for and session Medical team module+ training community/ mothers in terms of IYCF. from Q2 Area supervisor. material. - Rearrange CNCs according to need to avoid On going PC, PO, AS, CNP Planning and distance. implementation of the plan. - Refresher training for CMAM staffs. From Q1, 2014 PC Plan + budget PO - Discussion between program partners to reduce December WFP, Time and waiting period. 2013 TDH, RDRS Planning - On the job training for area supervisors. ASAP PC & Time and - Effective use of supervision tools. PO planning - Plan for integration for other activities. 2014 CP,CPO Planning Staff time - Identify vulnerable families with mal nourished Ongoing Po, Staff time child and link them with food security livelihood (2014) AS, Planning and program. CNP implementation - Review the coordination meeting and try to make Ongoing PC, Staff time the meetings more programs focused. Further (monthly) NC (WASH, Planning and strengthening between different program staff. Garden) implementation

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8. ANNEXES

ANNEX: 1 Schedule for SQUEAC, Nov 17th – 28th 2013, Kurigram, Bangladesh

Date Day Time Activity Venue Facilitator 16 Nov Day 1 Saturday Travel to Kurigram 17 Nov Day 2 Sunday 8:30- 17:00 Class room training & Field Exercise; Collection Kurigram Lovely /THD of some Contextual Data from the field: Prog  Opening Session coordinator  Introductions  Schedules  Going through the methodology  Distribute task to the assessment team 18 Nov Day 3 Monday AM Classroom training & field Exercise; Collection Lovely & of some Contextual Data from the field: Team 9.00 – 2.00  Information collection from OTP  FGD with OTP staff  FGD with OTP mother  KII with Supervisor 19 Nov Day 4 Tuesday 8:00-17.00 Field data collection & data analysis Field Team  OTP data collection (one team) AM/PM  Overview of the SQUEAC methodology  Assessment team’s perception about the prog  Starts up with mindmap 20 Nov Day 5 8:30 – 17.00 Field data collection & data analysis Kurigram Team + (Wednesday )  OTP data collection (1 team) Lovely  Contextual data analysis (qualitative data)  Identification of potential barriers and boosters of coverage 21 Nov Day 6 Thursday 8:00-17.00 Data analysis: Kurigram Team +  OTP data analysis OTP/SC Lovely  Selection of areas with high and low admission PM  Preparation for Small area survey 22 Nov Day 7 Friday Day off 23 Nov Day 8 Saturday Conducting Small area Survey by active case Kurigram Team + findings Lovely 25 Nov Day 10 Monday  Data analysis for Small area survey Kurigram Team +  Preparation for Wide area survey Lovely 26 & 27 Day 11 & 12 8:00-17:00  Conducting Wide Area Survey Field Team + Nov Tuesday & Lovely Wednesday PM Data Compilation 28 Nov Day 13 8:30 – 17:00  Data compilation of wide area survey Team + (Thursday)  Estimations of coverage Lovely  Recommendation  Action plan 29 Nov Travel back to Dhaka Kurigram Team

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ANNEX: 2

Participant’s List for Training and Coverage Assessment of CMAM Prog. Kurigram, November, 2013

Name Designation Organization E-mail ID Phone 1 Akher Ali GoB N/A 01721701151 2 Dipok Kanty Senior Program WFP [email protected] 01714015567 Associate 3 Mohammed Project RDRS [email protected] 01730328257, Hasan Manager 0170837311 4 Sariful Islam Programme Tdh [email protected] 01712011267 Officer 5 Ashraful Bari Area Supervisor Tdh N/A 01714604792 6 Shahinoor Area Supervisor- Tdh N/A 01714763207 Begum Rani CMAM 7 Md. Abdul Programme Tdh [email protected] 01945214479 Kader Officer (M&E) 8 Md. Abdul Monitoring Tdh [email protected] 01716586807 Wadud Officer 9 Moriom Asst Monitoring Tdh [email protected] 01745523032 Sultana Officer 10 Md. Anwar Asst. Monitoring Tdh [email protected] 01719857378 Hossen Officer 11 Dr. Niaz Medical Officer Tdh [email protected] 01976289666 Morshed 12 Rubel Hosen Medical Tdh [email protected] 01722842693 Assistant 13 Monsurul Hoq Epidemiologist – Tdh [email protected] 01766566015 Statistician 14 Fahmida National M&E Tdh [email protected] 01766194875 Afreen Coordinator 15 Rubina Yesmin Area supervisor Tdh N/A 01723257313 16 Rafiqul Alam Area supervisor Tdh N/A 01719514691 17 Dr. Ehsanul Director, H&N Tdh [email protected] 01727411866 Matin

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ANNEX: 3 SQUEAC Assessment/Survey, Interviewing community

Tdh CMAM programme, Kurigram, November, 2013

Guiding questions KIIs & FGDs, with community Key Informants:

(Knowledge and appreciation of the programme)

1. Questionnaire: For Traditional Healer (KII, one from each village)

1. Do you know the programme called OTP? 2. If yes, who informed you? 3. What do you know about malnutrition? 4. Is there any case of malnutrition in your community? 5. Do they come to you for treatment/help? 6. If they do how do you treat them?

2. Questionnaire: For Traditional Birth Attendant/Midwives (KII, one from each Village)

1. Do you know programme called OTP? 2. What do you know about malnutrition? 3. Do you know the causes of malnutrition? 4. Is there any case of malnutrition in your community? 5. Did you refer any children to this programme/CHV? 6. If yes, how many did you refer?

3. Questionnaire: For Village Leader (KII, one from each Village)

1. Do you know the programme, OTP? If yes, who inform you? 2. What is your role in the programme? 3. Is there any child in the programme from your village? 4. What are the causes of malnutrition in your village? 5. In your village any malnourished children that refuse to go to the programme? 6. If they did refuse, what was your role? 7. Is there stigma for malnutrition in your community? 8. Did you refer any cases to the programme? 9. How do you collaborate with the community volunteers?

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SQUEAC Assessment/Survey, Interviewing OTP staff/OTP mothers

TDH CMAM programme, Kurigram, November, 2013

1. Questionnaire: OTP Staff (FGDs- group of 6 to 15 staff)

How CMAM works:

1. What is your role to this programme? 2. What are the Admission criteria for OTP? 3. Who are the beneficiaries of the prog? 4. Do you have enough material/supplies for the work? 5. When is the last time you did the screening 6. Are there many cases of malnutrition in your village? 7. What are the causes of Malnutrition in your communities? 8. How do you collaborate with the health centres? 9. Do you get feedback on your work/report from the HC? 10. Are there any children who refuse to go to OTP? 11. If yes, what do you do with those cases?

What is your appreciation of the programme?

1. Benefit you have seen from the prog 2. Problem you face by involving to this prog. 3. Does the OTP programme cause workload for you? 4. Any suggestion to improve the programme?

Dev. a Seasonal calendar with them, if time allows

2. Questionnaires OTP/SC mothers (FGDs, 12 to 15 mothers/caretakers)

1. How long your child in the programme? 2. How do you know about this programme? : 3. Do you know why your child in the OTP/SC? 4. What was the cause of the condition of your child? 5. Did your child admitted before in OTP/SC (this one) 6. Any of your other children admitted to OTP/SC before? 7. Is this programme helping your child to get better? 8. Will you refer other child in this prog, if you find them with malnutrition (generally use local term)

Draw a Seasonal calendar with group

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ANNEX: 4

X- mind data, Tdh, CMAM programme, Kurigram, November, 2013

Staff training

Refresher

Need based

Inception training

Defaulter

High default

Follow up

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Inadequate information

Home visit

Staff commitment

Low salary

Stressed

Turn over

Supervision

Feed back

M&E

Community participation

Role in the program

Knowledge about CMAM program

Reputation of Organization

Rejection

Default

Rate high

Reason

Discharge info.

Understanding of criteria

Material supply

Work load

Low staff- turn over

Community of char

Good involvement

Good knowledge

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Involve TBA, RL, CL, WL

Short space in CC

Readmission

Floating Topic

Rejection

Stakeholders’ involvement

Training need

Lack of coordination among staff

Referred case tracking

Small Area Survey

In adequate children for at risk children

Over all coverage is high

SAM coverage is low

Referral of SAM children

Lack of follow up of discharge children

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ANNEX: 5

Seasonal Calendar, Kurigram area, Bangladesh, November 2013

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ANNEX: 6a

SQUEAC: Small Area Survey MAM, Kurigram, November, 2013

Date: ______/______/______

Mother’s Name Village MUAC Oedema MAM MAM SFP SEX Age in the NOT in recovering (Months) # Child’s Name prog. the prog. Cases in prog. M F

1

2

3

4

5

6

7

8

9

10

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ANNEX: 6b

Small area survey- CMAM programme, Kurigram, November, 2013

Questionnaire for the guardians of the children (Active SAM cases) NOT in the program

Name of Child: ______Municipal: ______

Village/OTP : ______Union: ______Date:______

1. DO YOU THINK THAT YOUR CHILD IS MALNOURISHED?

YES NO

If answer is NO stop, if answer is yes continue,

2. DO YOU KNOW A PROGRAM WHICH CAN HELP MALNOURISHED CHILDREN?

YES NO If answer is NO stop

If yes, what is the name of the program? ______

3. WHY DIDN'T BRING YOUR CHILD IN FOR CONSULTATION TO THIS PROGRAM?  Too far (What distance to be travelled with foot? ...... how many hours? ...... )  I do not have time/too occupied  To specify the activity which occupies the guardian in this period______ The mother is sick  The mother cannot travel with more than one child  The mother is ashamed to go the program (no good cloths etc…)  Problems of safety  The quantity of services too poor to justify to go  The child was rejected before.  The child of other people was rejected  My husband has refused  The guardians do not believe that the program can help the child (or prefers the traditional medicine, etc.)  Other reasons: ______

4. Was the CHILD ALREADY ADMITTED IN the PROGRAM before?

YES NO

If answer is NO stop, if answer is yes continue,

 Why isn’t s/he registered any more at present?  Defaulted, when? ...... Why? ......  Cured and discharged from the program (When? ...... )  Discharged but not cured (When? ...... )  Others: ______

(Thank the guardian)

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