1

Semi-Quantitative Evaluation of Access and Coverage

(SQUEAC)

for Out patient Therapeutic programme

Final Report

Shahrak, Lal Wa Sarjangal and Chaghcharan Districts of

Ghor Province, Afghanistan

Date: 16th November 2020 to 06th December 2020

Authors: Dr. Muhammad Khalid Zakir, Dr. Sayed Rahim RASTKAR and

Dr. Alain Parfait Bimenyimana

Funded by: Global Affairs Canada (GAC)

AFG

HA

NIS

TAN

2

Acknowledgement

Action Against Hunger (AAH) international would like to thank the concerted efforts of the

following stakeholders in the successful completion of the SQUEAC survey in Ghor Province:

Coordination of Humanitarian Assistance (CHA) Ghor provincial office for providing

quantitative data as well as EPI micro plan and village list.

The SQUEAC assessment team for demonstrating a high-level commitment and

professionalism throughout the exercise.

The communities of Shahrak, Lal and Chaghcharan districts for providing consent and

participating in various stages of the assessment at village and health facility levels.

The MoPH/PPHD, PND and AIM-WG for fully participating in the planning phase, their

engagement in validating the protocol and assessment findings.

Global Affairs Canada (GAC) for their financial support.

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Acronyms

ACF/AAH Action Contre la Faim / Action Against Hunger AIM-WG Assessments & Information Management Working Group ARCS Afghan Red Crescent Society AVDA Afghanistan Volunteer Doctors Association BHC Basic Health Centre BPHS Basic Package of Health Service CBHC Community Based Health Care CHA Coordination of Humanitarian Assistance CHC Comprehensive Health Center CHS Community Health Supervisor CHW Community Health Worker Cin Current SAM cases in the program Cout Current SAM cases not in the program DH District Hospital FGD Focus Group Discussion FHAG Family Health Action Group GAM Global Acute Malnutrition HFs Health Facilities HP Health Post HSC Health Sub Center IIs Informal Interviews IMAM Integrated Management of Acute Malnutrition Km Kilometer LoS Length of Stay LQAS Lot Quality Assurance Sampling MAM Moderate Acute Malnutrition MHTs Mobile Health Teams MIAR Monthly Integrated Activities Report mm Millimeter MoPH Ministry of Public Health MUAC Mid-Upper Arm Circumference NNS National Nutrition Survey NSIA National Statistics and Information Authority OJT On-Job Training OPD Out-Patient Department PH Provincial Hospital PHC Primary Health Care PNO Public Nutrition Officer PPHD Provincial Public Health Department Rin Recovering SAM cases in the program RUSF Ready to Use Supplementary Food RUTF Ready to Use Therapeutic Food SAM Severe Acute Malnutrition SQUEAC Semi-Quantitative Evaluation of Access and Coverage SSIs Semi-Structured Interviews UNICEF United Nations International Children’s Emergency Fund

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UNOCHA United Nation Office for the Coordination of Humanitarian Affairs WHZ Weight for Height Z-score WVI World Vision International

Table of Contents

Acknowledgement .......................................................................................................................................... 2

Acronyms........................................................................................................................................................... 3

1. Introduction.............................................................................................................................................. 7

1.1. Geographical Area ................................................................................................................. 7

1.2. Nutrition situation in the Province .................................................................................... 7

1.3. Health and Nutrition services ............................................................................................. 8

1.4. COVID-19 situation in Ghor ............................................................................................... 8

2. Executive summary ................................................................................................................................ 9

3. Survey Justification .............................................................................................................................. 10

4. Objectives ............................................................................................................................................... 10

4.1. Overall Objectives ............................................................................................................... 10

4.2. Specific Objectives .............................................................................................................. 10

5. Methodology .......................................................................................................................................... 11

Survey Team Composition .................................................................................................................. 12

5.1. STAGE ONE ............................................................................................................................................ 12

5.1.1. Quantitative data analysis .......................................................................................................... 13

5.1.1.1 Admissions over time .......................................................................................................... 13

5.1.1.2 MUAC at admission ............................................................................................................. 16

5.1.1.3 Discharge outcomes ............................................................................................................ 17

5.1.1.4 Nutrition programs reporting tools .................................................................................. 19

5.1.1.5 Length of stay ........................................................................................................................ 21

5.1.1.6 Defaulters over time ............................................................................................................ 22

5.1.1.7 Time to default ...................................................................................................................... 22

5.1.2 Qualitative data collection and analysis .................................................................................. 23

5.1.2.1Introduction .......................................................................................................................... 23

5

5.1.2.2Data compilation and analysis .......................................................................................... 24

6. STAGE TWO .......................................................................................................................................... 27

6.1. Introduction ............................................................................................................................... 27

6.2. Hypothesis testing: distance to the OPD-SAM sites ........................................................ 27

6.3. Prior building ............................................................................................................................. 30

6.3.1. Introduction .......................................................................................................................... 30

6.3.2. Weighted scores ................................................................................................................... 33

6.3.3. Simple scores ....................................................................................................................... 33

6.3.4. Histogram prior .................................................................................................................... 33

6.3.6. Mind Map .............................................................................................................................. 34

6.3.6. Concept Map ........................................................................................................................ 34

6.3.7. Prior mode ............................................................................................................................ 35

7. STAGE THREE: WIDE AREA SURVEY ............................................................................................. 37

7.1. Minimum sample size of villages for the wide area survey ............................................. 37

7.2. Wide area survey Methodology ............................................................................................ 38

7.3. Coverage estimations .............................................................................................................. 38

7.4. Results of the wide-area survey ............................................................................................ 39

7.5. Reasons for not being in the program .................................................................................. 40

Survey limitations and challenges .............................................................................................................. 40

8. Conclusions and recommendations .................................................................................................. 41

9. Annexes ................................................................................................................................................... 47

List of Figures

Figure 1: map of the Ghor province ............................................................................................................. 7

Figure 2: Acute Watery Diarrhea prevalence among children under five, Oct, 2019 - Sep,2020 in

5 OPD SAM sites, Lal, Shahrak and Chaghcharan districts of Ghor province - (n=135593 Cases).

........................................................................................................................................................................... 14

Figure 3: Admissions over time for OPD SAM program from Oct 2019 to Sep 2020, in 5 OPD

SAM sites, Lal, Shahrak and Chaghcharan districts of Ghor province - (n=1026 SAM Cases) ..... 15

Figure 4: Admissions over time for OPD SAM program from Oct 2019 to Sep 2020 in 5 OPD

SAM sites, Lal, Shahrak and Chaghcharan Districts of Ghor Province. ............................................. 15

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Figure 6: OPD- SAM Program Admissions over time per health facility, Oct 2019 to Sep 2020, in

Lal, Shahrak and Chaghcharan districts of Ghor province - (n=1026 SAM Cases) ........................... 16

Figure 7: MUAC at admission, 5 OPD SAM sites, Oct 2019 to Sep 2020 of in Lal, Shahrak and

Chaghcharan districts of Ghor province (n=1026 cases from Treatment cards) .............................. 17

Figure 8: Discharge overtime, Treatment Cards Data - 5 OPD SAM sites, in Lal, Shahrak and

Chaghcharan districts of Ghor province, Oct-2019 to Sep- 2020 (n=929 cases) ............................ 18

Figure 9: Discharge overtime, MAIR Reports Data - 5 OPD SAM sites, in Lal, Shahrak and

Chaghcharan districts of Ghor province, Oct-2019 to Sep-2020 (n=1109 cases) ........................... 18

Figure 10: Discharge Outcomes per Health Facility (Treatment Follow-up Cards) - 5 OPD SAM

sites, Oct- 2019 to Sep- 2020, in Lal, Shahrak and Chaghcharan districts of Ghor province

(n=929 cases) .................................................................................................................................................. 19

Figure 11: Length of Stay for cured cases - 5 OPD SAM sites, Oct- 2019 to Sep- 2020 ............... 21

Figure 12: Trends in defaulting, data from beneficiary treatment cards in 5 OPD SAM sites, Oct-

2019 to Sep- 2020 (n=499 cases) .............................................................................................................. 22

Figure 13: Time to default, 5 OPD SAM sites, Oct- 2019 to Sep- 2020 (n=499 cases) ................. 23

Figure 14: Concept Map ............................................................................................................................... 34

Figure 15: Parameters Calculation ............................................................................................................. 36

Figure 16: prior distributions on the Bayes calculator ........................................................................... 36

Figure 17: Wide Area Survey results ......................................................................................................... 39

Figure 18: Reasons of uncovered SAM cases .......................................................................................... 40

List of Table

Table 1: Health Facilities Covered in this Assessment. .......................................................................... 13

Table 2: Common errors in nutrition program, 5 OPD SAM sites, Oct-2019 to Sep- 2020, Ghor

province. .......................................................................................................................................................... 20

Table 4: Explanation of Boosters ................................................................................................................ 24

Table 5: Explanation of Barriers .................................................................................................................. 26

Table 6: Small area survey’s data collection plan .................................................................................... 29

Table 7: Simple and weighted scores of Boosters and Barriers ........................................................... 31

Table 8: Histogram Believe Individual Level ............................................................................................. 33

Table 9: Histogram Believe Team Level .................................................................................................... 34

Table 10: Prior Mode Calculation ............................................................................................................... 35

Table 11: Total SAM cases found during the wide-area survey ........................................................... 38

Table 12: Table of Recommendations ....................................................................................................... 43

Annexes

Annex 1: Participants list of Ghor SQUEAC assessment. ...................................................................... 47

Annex 2: Seasonal Calendar of Ghor province ........................................................................................ 47

Annex 3: Villages list, Selected for wide area survey. ............................................................................ 48

Annex 4: HFs list of Ghor province ............................................................................................................ 49

Annex 5: Ghor province Boosters, Barriers and Questions (BBQs) ..................................................... 51

Annex 6: Ghor province Boosters, Barriers and Questions (BBQs) ..................................................... 53

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Annex 7: common symbols used for the SQUEAC Assessment in Ghor Province. .......................... 55

Annex 8: Admission Criteria of OPD-SAM/MAM .................................................................................. 56

1. Introduction

1.1. Geographical Area

Ghor is one of the 34 provinces of Afghanistan, located in Hazarajat region in central Afghanistan,

towards the north-west, the borders of the provinces are Sar-e-pul and Faryab to the north, Herat

and Badghis to the west, Helmand and Farah to the south, Bamyan and Daikundi to the east. The

population of the province is around 738,2241.The province is subdived in ten districts namely:

Dolaina, Dawlatyar, Charsada, Pasaband, Shahrak, lal WA Sarjangal, Taiwara, Tolak, Saghar and

Chaghcharan (the capital of the province).

Most of its residents speak Dari Language

but the residents of Lol-o- Sari Jangle

district, sharing border with Bamyan

province, have Hazaragi accent.2

According to the latest UN-OCHA report

(Weekly Humanitarian Update: 19 - 25 April

2021), Ghor is among the provinces which

are experiencing frequent population

movements and forced displacements;

currently, 87,383 people are internally

displaced in the Ghor province due to

ongoing conflicts but also due to seasonality

and natural disaster.

1.2. Nutrition situation in the Province

According to the latest SMART survey conducted in 2016, findings showed that the prevalence of

Global Acute Malnutrition (GAM) based on WHZ was 11.0% (8.6-14.0 95% CI). GAM rate based

on MUAC was 14.3% (11.2-18.0 95% CI). The rate of SAM (WHZ<-3 score and/ or oedema) was

2.5% (1.6- 4.0 95% CI). The prevalence of stunting among children 6-59 months was 51.3% (46.6-

56.0 95% CI), out of which, 18.2% (15.4-21.4 95% CI) was severely stunted.

In September 2016, the DOPH and CHA with support from AAH Afghanistan, conducted a

SQUEAC training and assessment in Chagcharan, Shahrak, Lal WA Sarjangal and Dolaina Districts

of Ghor Province. The assessment for OPD-SAM program estimated a single coverage of 28.0%

1 CSO population update 1397. 2 Pajwak Afghan News Election 2019. 3Conflict Induced IDP Report – UNOCHA

Figure 1: map of the Ghor province

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[CI 95%: 18.3% - 40.7%] in the targeted districts. The current SQUEAC has also been conducted

with the technical support of AAH in close coordination with the PPHD and the BPHS/

SEHATMANDI implementer (Coordination of Humanitarian Assistance - CHA).

1.3. Health and Nutrition services

A local NGO, Coordination of Humanitarian Assistance “CHA”, is implementing the BPHS

SEHATMANDI project in Ghor province and the EPHS is implemented by the directorate of public

health (DoPH). The BPHS covers a total of 94 health facilities providing health services (2 DH, 1

CHC+, 7 CHC, 26 BHC, 40 SHC, 10 FHH, 1 Prison Health Center, and a total of 7 mobile health

teams and 479 health posts offering Primary Health Care (PHC) package) in all the 10 districts of

Ghor province. The provincial hospital is directly supported by the DoPH. A total of 36 health

facilities provide OPD SAM, 2 provide IPD SAM and 44 OPD MAM. A7 MHTs have OPD

SAM/MAM as well in the province.

To increase the coverage of Health and Nutrition services in the province, and mostly to reach

vulnerable people in hard to reach areas, in Ghor province, as in other provinces, the mobile teams

strategy has been adopted. In total, 7 mobile teams were functioning at the time of this

assessment, among them, 3 run by Action Against Hunger (AAH).

1.4. COVID-19 situation in Ghor

The COVID-19 pandemic in Afghanistan is part of the worldwide pandemic of coronavirus disease

(SARS-CoV-2) (The virus was confirmed to have spread in Afghanistan when its 1st case was

confirmed on 24th February 2020 in Herat. To note that Ghor Province shares border with Herat

province. According to Ghor provincial public health directorate report, the first case of COVID-

19 was detected on March 27th 2020. According to the COVID-19 pandemic in Afghanistan

report, from the 27th March 2020 to the 1st November 2020, in Ghor,1,313 tests were realized,

with a total of 557 positive cases, giving a positivity rate of 42%. In the same period, among the

confirmed 557 cases, 184 have recovered and 13 related deaths were noted. Since November 1st

2020, no new case has been reported for Ghor province, due mostly to lack of testing capacity.

Considering the epidemiological situation on COVID-19 in Ghor province, and the necessity to

continue the provision of life-saving programs, AAH in coordination with provincial authorities and

other partners, decided to conduct this assessment, with strengthened preventive measures to

mitigate the risk of COVID-19 transmission.

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2. Executive summary

The nutritional situation in Afghanistan remains worrying, most of the provinces of Afghanistan

have high rates of acute malnutrition above the WHO emergency thresholds4. Since 2010, the

Basic Package of Health Services (BPHS)5 system has included the treatment of malnutrition,

however, the response remains inadequate6. Strengthening the nutrition component of the

BPHS/EPHS (Essential Package of Hospital Services) remains a challenge for the Ministry of Public

Health (MoPH) and the implementing partners. In order to assess the coverage of nutrition

services, Action Against Hunger (AAH) in partnership with the MoPH conducted a nutrition

program coverage assessment using SQUEAC methodology in the three accessible districts

(Shahrak, Lal and Chaghcharan) of Ghor province. The 3 districts were selected considering the

access in terms of security, but as well based on the population needs. The survey was conducted

from the 16th November to the 06th December 2020.

The SQUEAC methodology was used in this assessment to estimate the coverage of OPD-SAM

program among children U5. The methodology uses qualitative and quantitative techniques and

uses triangulation method. The findings of the assessment revealed that the OPD-SAM program

single coverage was estimated at 31.6% (23.2% - 41.8%) which is below7 the recommended

SPHERE minimum thresholds for rural settings (>50%)8.

However, this estimated coverage is higher than the coverage found during the 2017 SQUEAC

survey in the same province (but not in the same districts), when the OPD-SAM program coverage

was of 28.0% (95% CI: 18.3%-40.7%).

During the assessment, interviews with key stakeholders, key community groups, health facilities

staff, caregivers of SAM cases in program and caregivers of SAM cases not in the program revealed

positive (boosters) and negative (barriers) factors influencing the OPD-SAM program coverage.

The Boosters/Positive Factors found during the assessment include the presence of community

nutrition program, good perception of the program by beneficiaries, few cultural barriers, with

mothers allowed to take their children to health services.

The Barriers/Negative factors highlighted by this investigation consist of lack of physical access to

the health facilities, related to long distances, with a complex geographical situation of the

province, insecurity, lack of transportation means and fees. The health system is understaffed, with

poor supply chain occasioning stockout of nutrition commodities. The COVID 19 pandemic related

restrictions and stigma weighed also in the healthcare seeking behaviour.

4 National Nutrition Survey 2013 5 A Basic Package of Health Services for Afghanistan – (2010/1389) Islamic Republic of Afghanistan, Ministry of Public Health 6 See Afghanistan: Back to the reality of needs, (ACF International, 2014) and European Union Final Report Nutrition Assessment (August 2014). 7 The SPHERE minimum thresholds for rural settings (>50%).

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The discussions with stakeholders namely CHA, WVI, UNICEF, ARCS and PPHD provided a road

map on key actions to undertake in order to improve the OPD-SAM coverage and overcome the

highlighted barriers/negative factors.

The key recommendations include:

1. Wherever the access is granted, to expand the number of MNHTs to the

inaccessible/remote areas.

2. For the DoPH and BPHS implementer, to strengthen the supportive supervision for HFs.

3. Ensure a regular supply of the nutrition commudities to avoid stockout.

4. Conduct initial/refresher training on update IMAM guideline for all the HFs staff.

5. Strengthen nutrition education at HFs and community level.

6. Strengthen follow-up and referral system between communities and health facilities

7. Strengthen reporting and feedback system of nutrition program

3. Survey Justification

In 2017, AAH, in coordination with a local NGO, Coordination of Humanitarian Assistance (CHA,

BPHS implementer in Ghor province), conducted a SQUEAC assessment in Ghor province to

assess the OPD-SAM program coverage. The assessment was mainly focused on 4 districts: Lal,

Dolaina, Shahrak, and Chaghcharan city. That assessment found OPD-SAM program coverage at

28.0% (95% CI: 18.3%-40.7%) which is below the SPHERE standard recommendation (>50% for

rural area). The aim of the 2020 assessment was to assess the progress made in terms of coverage,

identify boosters and barriers for SAM program and agree on how to address the barriers and

strengthen the boosters. Considering the deterioration of the situation in the province, mostly

related to a fragile security context, natural disasters and the impact of the ongoing COVID 19

pandemic, AAH in collaboration with all stakeholders intervening in nutrition in Ghor Province,

conducted this SQUEAC assessment to evaluate the SAM coverage and to formulate

recommendations that can help to improve the situation.

4. Objectives

4.1. Overall Objectives

The overall objective of the assessment was to investigate the OPD-SAM program coverage in

catchment area of the 6 HFs where a nutrition program is implemented by Action Against Hunger

in Shahrak, Lal and Chaghcharan Districts of Ghor province and to provide recommendations for

improving programme access and uptake.

4.2. Specific Objectives

• To assess the coverage of OPD-SAM treatment program in the catchment area of the 6

supported health facilities in Shahrak, Lal and Chaghcharan Districts of Ghor Province.

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• To assess the end line situation and impact of the program implemented by Action Against

Hunger in the targeted areas in Ghor province.

• To identify the boosters and barriers affecting the SAM program coverage.

• To develop recommendations and an action plan to improve service uptake/access in

collaboration with service implementers, Ministry of Public Health and other relevant

stakeholders.

• To build the capacity of implementing partners staff and MoPH provincial staff on the

SQUEAC methodology.

5. Methodology

The SQUEAC assessment methodology has been used to estimate the coverage of the OPD-

SAM program coverage in 3 districts of Ghor province (Shahrak, Lal and Chaghcharan), to identify

boosters and barriers, therefore to provide recommendations and develop a joint action plan for

improving the coverage. The SQUEAC assessment included the following stages:

Stage 1: Review of available routine program data of the 12 last months from 5 Health facilities

providing OPD-SAM services, in the selected 3 districts.Collection and analysis of additional

quantitative data from the same selected health facilities. This was combined with the analysis of

qualitative information from community members and health facility staff and the identification

of negative and positive factors affecting coverage.

Stage 2: Development and testing of hypotheses to confirm /deny assumptions related to the

location of areas of high or low coverage and the reason for low coverage. The findings from

these tests were incorporated into the survey team’s prior modes for the OPD-SAM, which was

then used to calculate the required sample size for Stage 3.

Stage 3: A wide-area survey to determine an estimation of overall program coverage for the OPD-

SAM using Bayesian techniques. The wide- area survey took 5 days to survey 30 villages randomly

selected.

The survey was conducted from 16th November 2020 to the 06th December 2020 starting from

the preparation phase up to survey implementation.

Considering the current situation of the COVID-19 pandemic, the following measures were

applied with accordance to the recently released interim guideline for conducting population

level survey and HHs level data collection in the context of COVID-19:

Introduction, consent, interviews, and measurements were done in an open area with enough space for proper physical distancing, considering also family's privacy.

All enumerators were <60 years of age and without known comorbidities.

All survey team members were provided with face masks and gloves. Each team carried a safety box/bag and safely dispose used personal protective equipment at the end of the data collection.

The survey teams offered a face mask to the key informants who were attending interview.

During the interview, the interviewer and respondent maintained a distance of at least 1-

12

meter even if wearing a mask

All team members have sanitized their hands immediately before starting interview using soap and water or alcohol-based hand sanitizer with at least 60% alcohol when hand washing point was not available.

During the small and wide area surveys, new MUAC tapes were used for each household and the previously used ones were left to the household after the completion of the household questionnaire.

The survey team managed to prevent congregation of others (household or community members) around the place of interview considering the social distancing and privacy.

Well-functioning vehicles with enough space for sitting were hired for the survey teams and were disinfected regularly. Face masks and hand gloves were also provided to all drivers.

Survey Team Composition

The core survey team was composed of one Surveillance Program Manager supported by the

Deputy Surveillance Head of Department from AAH Kabul main office. Technical support was

also provided by ACF HQ Health and Nutrition regional technical advisor, France, and SMART

expert, ACF Canada. Data collection was supervised and led by five team supervisors, 4 nutrition

supervisors from AAH and 1 nutrition officer from CHA Each team was made of one male and

one female enumerators.

At the beginning of the assessment, one day technical training was delivered to the 5 team

supervisors about the SQUEAC methodology. This was followed by a two-days training for all

the 15 team members on the first stage of the qualitative data collection in the community and

an explanation of each of the key stages of a SQUEAC survey. A three-day training was

conducted to all the 15 survey team members for stage 2 and stage 3.

5.1. STAGE ONE

In stage one, the assessment teams used the last 12 months (October 2019 to September 2020)

already existing routine and contextual information both directly and indirectly related to the

program from the five selected HFs. The data of six health facilities were initially planned to be

included, Lofra health facility was not reachable by the team to collect their program data and

analysis it, so it has been excluded from the survey.

Qualitative information was generated from interviews done with key informants at community

levels and health facility staff. Quantitative and qualitative triangulation of data by sources and

methods were used to identify areas of low and high coverage.

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5.1.1. Quantitative data analysis

The program data was collected and analysed from 5 Health facilities providing OPD-SAM services

in the three selected districts of Ghor Province. The information collected includes admissions

over time (all admissions by WHZ, MUAC and Oedema), morbidity, admissions per health facility,

program exits (cured, deaths, defaulters, referrals and non-response), MUAC measurement on

admission, and average length of stay (ALoS) in the program.

5.1.1.1 Admissions over time

The assessment technical team analyzed ODP-SAM data from a) the Monthly Integrated Activity

online database and provincial level Reports “MIARs” of 12 months of activities from October

2019 to September 2020, b) 1026 OPD-SAM treatment cards, and c) register books of the

selected health facilities.

The assessment covered 5 health facilities in three districts of the Ghor province, as illustrated in

the table below.

Table 1: Health Facilities Covered in this Assessment.

Pro

vin

ce

District Facility Name

Fa

cility

Co

de

Fa

cility T

yp

e

Co

ve

rag

e

Po

pu

latio

n

Ty

pe

of

Se

rvice

s

Gh

or

Chaghcharan

Provincial Hospital

2116 PH 34923 OPD-SAM

Ghor Qand 1749 BHC 11256

OPD-SAM

Lal wa Sarjangal

Qala e Pichi 2179 BHC 7028 OPD-SAM

Talkhak 2177 BHC 7775 OPD-SAM

Shahrak Jilga Mazar 2480 BHC 9415 OPD-SAM

The analysis revealed dissimilarities in the number of SAM admissions between provincial/online

OPD-SAM MAIR, Register Book Data and OPD-SAM treatment follow up cards. The total number

of OPD-SAM admissions for a period of 12 months was 1101 cases of children U5 according to

the MAIR reports and 1102 cases on the online database, while it was 1026 cases according to

OPD-SAM treatment follow up cards and 1022 admissions over time as per the OPD-SAM register

books.

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A difference of 75 cases between OPD-SAM follow-up card data and the MIARs may be

attributed to huge discrepancies in the reports and in particular the lack of capacity of the

in-charge/staff to observe optimal quality assurance in following SAM admission protocol.

For this reason, the analysis in this SQUEAC assessment is mainly based on OPD-SAM

treatment cards since only the cards can prove that indeed OPD-SAM services were

offered to the beneficiaries.

The analysis of SAM admissions from OPD-SAM treatment cards shows a clear image of the

number of cases admitted within a period of 12 months as highlighted in Figure 1. The analysis of

admissions indicated a decreasing trend of admission after October in each year attributed to the

weather and the starting of snowing and rainfall season. Meanwhile the complexity of the

geography and lack of transportation for beneficiaries, was a cause to reduce the access of

health/nutrition services for the beneficiaries ; the same geographical complexity disrupts the

supply chain, occasioning several days of stock out of nutrition commodities in the Health

Facilities. Our findings show that most of the health facilities faced stock out of RUTF in the month

of November 2020, due to delayed supply and therefore the staff in charge had to put on hold any

new admissions.

Ghor has a very cold, snowy winter seasons [November to May] leading to decreased movements

and transportation in the province, compromising the access of the population to health and

nutrition services.

Analyzing the morbidity, the diarrhea prevalence was also very high in accordance with the health

facilities top 10 diseases list over the summer months. The figure 2 bellow illustrates the

prevalence of acute watery diarrhea during the last 12 months.

Figure 2: Acute Watery Diarrhea prevalence among children under five, Oct, 2019 - Sep,2020 in 5 OPD SAM sites, Lal, Shahrak

and Chaghcharan districts of Ghor province - (n=135593 Cases).

0

5000

10000

15000

20000

1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep 1-Oct 1-Nov 1-Dec

15

As waterborne diseases, including diarrhea, are among direct causes of malnutrition, the high

number of admission in OPD SAM services during the months of June to August may be associated

with high diarrheal disease prevalence during this period.

Figure 3: Admissions over time for OPD SAM program from Oct 2019 to Sep 2020, in 5 OPD SAM sites, Lal, Shahrak and Chaghcharan districts of Ghor province - (n=1026 SAM Cases)

Note: M3A3 is where medians of sets of three successive data points (M3) have been taken. The

results are then smoothed by taking the arithmetic means of sets of three successive smoothed

data points (A3). The more times you apply a moving average, the more smoothing applied to the

data. This allows for a greater long-term analysis of admissions. Variations over the data period

can be analyzed without the abnormal fluctuations distorting the data set.

Figure 4: Admissions over time for OPD SAM program from Oct 2019 to Sep 2020 in 5 OPD SAM sites, Lal, Shahrak and Chaghcharan Districts of Ghor Province.

0

50

100

150

200

Nu

mb

er o

f ad

mis

sio

n

Month

Total Admissions M3A3

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A comparison between the events calendar in a year-period, mostly related to the weather, and

the performaces of the programs, shows that the hard weather conditions have a negative impact

on the demand and utilization of health and nutrition services, with low admistion from January to

May 2020.

Analysis of OPD-SAM treatment cards revealed that Ghor Qand BHC and Ghor PH had the highest

number of SAM admissions in the considered period as highlighted in Figure 6. This is related to

the fact that these health facilities had OPD-SAM treatment services for more than one year(well

known by beneficiaries) and these health facilities are located in the center of the province, whith

a better security situation and highly populated area.

The low admission in Talkhak and Qala e Pichi BHCs might be attributed to, apart their small

catchment area, to low awareness of the communities, geographical complexity, and lack of

transportation for the beneficiaries.

Figure 5: OPD- SAM Program Admissions over time per health facility, Oct 2019 to Sep 2020, in Lal, Shahrak and

Chaghcharan districts of Ghor province - (n=1026 SAM Cases)

5.1.1.2 MUAC at admission

According to the IMAM guidelines for Afghanistan, admissions for OPD-SAM treatment can be

done with any of the three criteria: WHZ (<-3SD), MUAC (<115mm), or Oedema (+ or ++).

In the targeted health facilities, the most used criteria were MUAC and WHZ (respectively 36.8%

and 30.2% of all admissions), while oedema as admission criteria was used in 0,2%. The data

analysis show that, for 32.74% of the cases, the admission criteria was not specified on the patient

card. The majority of SAM children (515 cases=50.1%) were admitted with MUAC measurement

between 110mm and 114mm, with a median MUAC at 111mm, revealing early admission of SAM

cases to the program. Early admission to the program can be a result of the active screening, case

finding, and outreach activity of the community health worker, health and nutrition mobile team

in the field, and strong community mobilization and sensitization programs at the provincial level.

0

100

200

300

400

500

Ghor PH Ghor Qand BHC+ Talkhak BHC+ Qala Pichi BHC Jilga Mazar BHC

Total admissions

17

Wrong admissions of 21.0% (204 out of the total) SAM cases with a MUAC ≥115mm were also

observed in the OPD-SAM treatment card. Children with MUAC ≥125mm were also admitted to

the OPD-SAM, while Z-score was >-3SD. Such problem shows a lack of adherence to admission

criteria as per the IMAM guideline. (See figure 7 below about MUAC at admission)

Figure 6: MUAC at admission, 5 OPD SAM sites, Oct 2019 to Sep 2020 of in Lal, Shahrak and Chaghcharan districts of Ghor province (n=1026 cases from Treatment cards)

5.1.1.3 Discharge outcomes

The discharge outcomes include recovery, default, death and non-response rates. The SPHERE

threshold for cure rate in OPD SAM is >75%, while death and defaulter rates must be <10% and

<15% respectively.8

The beneficiary cards were analyzed to determine the status of each beneficiary as the discharge

outcome was not notified in most of the beneficiaries’ cards of all included health facilities mostly

in Jilga Mazar and Ghor Qand BHCs.

Defaulter rate: 53.18% (494 cases) which is more than triple above the SPHERE threshold of

<15% in the reporting period from October 2019 to September 2020. Defaulting seems to be

a major challenge to the program as the rates are extremely high. Searches on the causes for

defaulting from the caregivers of defaulted children showed that the the rush weather during

winter, long distances to access the HFs, and lack of transportation to reach the OPD-SAM

services, followed by the poor economic conditions of the HH and the insecurity in the districts

were the main defaulting causes. Most of the families in Ghor province are busy with

husbandry and farming and agricultural activities. They are not able to pay transport fees . The

poor supply chain, occasioning several days of stockout, has also as consequence

8 Sphere Handbook , 2011

≥125 123 121 119 117 115 113 111 109 107 105 103 101 99 97 95 93 91

0

50

100

150

200

250

MUAC (mm)

Nu

mb

er

of

adm

issi

on

s

MUAC at admission

Med

ian

Early Admission

18

Cure rates: 46.29% (430 cases) which was below the SPHERE threshold (≥75%) in the

reporting period from October 2019 to September 2020.

An overall 0.54% non-response rate was observed in OPD-SAM beneficiary treatment card data.

There were 5 non-response cases, all of them were recorded in Ghor Qand (2 cases) and Qala e

Pichi BHC (3 cases).

Figure 7: Discharge overtime, Treatment Cards Data - 5 OPD SAM sites, in Lal, Shahrak and Chaghcharan districts of Ghor province, Oct-2019 to Sep- 2020 (n=929 cases)

Figure 8: Discharge overtime, MAIR Reports Data - 5 OPD SAM sites, in Lal, Shahrak and Chaghcharan districts of

Ghor province, Oct-2019 to Sep-2020 (n=1109 cases)

0%10%20%30%40%50%60%70%80%90%

100%

Cured Defaulter Death Non-response

<15% SPHER standards for default

>75% SPHER standard for cured

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cured Defaulter Death Non-response

<15% SPHER standards for default

>75% SPHER standard for cured

19

To check the quality of the program data and the reporting system of 5 health facilities offering

OPD SAM services, the nutrition program monthly reports in the IMAM database were analyzed9.

This has shown different information regarding the program outcomes, with a higher cured rate

being reported in the IMAM database compared to the one found when referring to the patients

cards. This further shows a gap in the reporting system, and supervision of activities is highly

recommended to streamline the reporting system for accurate reporting.

Figure 10 depicts the discharge outcomes of OPD-SAM services in the targeted 5 health facilities.

Figure 9: Discharge Outcomes per Health Facility (Treatment Follow-up Cards) - 5 OPD SAM sites, Oct- 2019 to Sep- 2020, in

Lal, Shahrak and Chaghcharan districts of Ghor province (n=929 cases)

The discharge outcomes data in the IMAM database were also analysed per health facilities:

Talkhak and Qala e Pichi BHCs are among the health facilities with the highest cure rates and the

lowest defaulter rates. These health facilities are located in very populated rural areas. The

following elements were confirmed by the community during the qualitative research: there was

no RUTF shortage during the last 12 months, no cultural restrictions on mothers to take their

malnourished children to health facilities, most of the villages in the catchment area of these health

facilities had active male and female CHWs.

5.1.1.4 Nutrition programs reporting tools

For all the 5 health facilities whose nutrition program reporting tools were checked and analysed

in the first stage of this SQUEAC Assessment, poor information recording/ filing system with a

significant discrepancy in the data was observed. The national IMAM guidelines specify that

routine visits in OPD-SAM should be weekly or biweekly (exceptionally in specific circumstances).

Typically, a weekly-based arrangement of visiting was being used for the treatment of

malnourished children, and some of the HFs were also doing biweekly arrangement of visits , so

that, using of the both mentioned arrangement of visiting (weekly & Biweekly) was making hard

to analyze average length of stay and identify the number of visits as well. On the other hand, the

9 This is the data used by MOPH for planning and evaluation of the program

0%

20%

40%

60%

80%

100%

120%

Ghor PH Ghor Qand BHC+ Talkhak Qala- e- Pichi Jilaga Mazar

Cured Defaulter Death Non-response

20

admission/discharge criteria were unmarked among the high number of treatment follow-up cards,

which shows the lack of understanding on how to fill the treatment cards.

Table 2: Common errors in nutrition program, 5 OPD SAM sites, Oct-2019 to Sep- 2020, Ghor province.

No Common Errors in the Documents

Description

1 Wrong criteria at Admission

Children were admitted to the OPD-SAM program with MUAC >115

mm, while the Z-score was also >-3SD. In some of the treatment cards,

the admission criteria were not marked, which made hard to know the

exact admission criteria by which the children were admitted to the

program

2

Unmarked Criteria and Wrong discharge as ‘cured’

In some of the treatment cards, the discharge outcome criteria were

not marked, which made hard to know the exact discharge criteria by

which the children were discharged from the program (especially in

Ghor PH where it was frequently missed). In a big number of

treatment follow-up cards, discharge criteria were not marked or it

was marked wrongly. The number of unmarked cured (UC), unmarked

defaulter (UD) and unmarked referred (UR) were very high : 237 out of

1026 cases which become 18.2% of all the data in all the included HFs.

Marking uncured malnourished children as cured in their recovering

phase was also among the common mistakes present in a big number

of malnourished children follow-up cards. This shows an inappropriate

application of the IMAM guideline. For instance; there were children

marked cured with a MUAC<=12.5 mm - >11.5mm as these cases

were at the recovery phase of the treatment.

3

No decimal for

MUAC

measurement

expressed in

mm

MUAC measurements, reported in mm, was often expressed without

decimal To remind that the decimal number is also needed to prevent

measurement bias among the screening of malnourished children.

Here 34.8% children were admitted to the OPD-SAM program with a

MUAC recorded in mm without any decimal.

4

Poor filing

system, and

poor data

management

The filling system in all the HFs selected for the assessment was not

good, as the data in register books or treatment cards must be clearly

arranged by month and quarter. Unfortunately, the data arrangement

in these HFs was disorganized, which make difficult the review of the

data as well as following the malnourished children. On the other

hand, the process of avoiding duplication is difficult to implement

because a number of treatment cards was found with same ID

number. Improper handwriting, lack of attention and inaccuracy in

writing of the date, lack of attention to use the same format of data

21

(solar/Gregorian) and most of the dates and other phrases not

readable were also notified.

5 Data

discrepancies

The analysis of the quantitative data revealed that a number of the

treatment follow- up cards were not entered in the registration books.

Thereforediscrepancies among the treatment cards and registration

books were observed, as it should be the same in both sources.

Weobserved significant differences between the source of the data

(eg: in total 1026 children were admitted to the programme according

to treatment cards, 1022 according to the register book and 1102

were reported in the online nutrition database). Such findings show

the low capacity of the employees as well as weak supervision from

the HF staff.

5.1.1.5 Length of stay

The length of stay until discharge as cured refers to the number of weeks of treatment a

beneficiary stays in the program until completely cured.

The average length of stay in the program was 8 weeks. In comparison with the 16 weeks

maximum length of stay in Afghanistan, all indications show the beneficiaries would have stayed

a bit longer in the program if the exit criteria of cured (WHZ ≥-2SD and/or MUAC 125mm with

no Oedema) were respected. The analysis of malnourished children's treatment follow-up cards

shows that 5.4 % of children were unmarked cured when they were exited from the program, it

means the discharge out of these children was not specified.

Figure 10: Length of Stay for cured cases - 5 OPD SAM sites, Oct- 2019 to Sep- 2020

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

0

2

4

6

8

10

12

Length of stay (weeks)

Co

un

t

Weeks in programme before discharge cured - all health centres

22

5.1.1.6 Defaulters over time

In accordance with the IMAM guideline of Afghanistan, children absent from the treatment for

three consecutive visits are considered as defaulters. Defaulting is known as a massive barrier to

maintain the program coverage efficiently and within the standard quality threshold. The

program's inability to retain the beneficiaries will have a negative effect, as the cases will worsen

or even die in the community.

As it is portrayed in Figure 12 below, the defaultin rate in the program was continuously high, that

should have brought program to make recommendations to improve the situation. Defaulting rate

over the past 12 months showed an upward trend with peaks, reported to be linked to shortage

of nutrition supplies and some seasonal trends, corresponding to the beginning of the winter

season.

Figure 11: Trends in defaulting, data from beneficiary treatment cards in 5 OPD SAM sites, Oct- 2019 to Sep- 2020 (n=499 cases)

5.1.1.7 Time to default

The median length of stay in the OPD-SAM program for defaulter’s cases was 2 weeks as

illustrated in Figure 13. The analysis of the defaulters’ data showed a high number of children

defaulting early in the program, with a great number of children defaulting after the first and

second visits. Caregivers of the defaulters mentioned long distances, and poor economic situation

as factors limiting their adherence to the program. Most of defaulters were found in villages where

there is no community nutrition services with FHAGs and CHW to raise awareness in the

communities. Some of the caregivers have also mentioned poor communication from the program,

explaining that they were not aware on the date of the following visit. The lack of a continuum of

services, connecting the nutrition program to the communities and for being able to track and

follow up the defaulters in the community is even worsening the situation.

0

10

20

30

40

50

60

70

80

90

100

Oct-19 Nov-19 Dec-19 Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20

NU

MB

ER

OF

DE

FA

ULT

ER

S

MONTH

Defaulters over time

Total Defaulters M3A3

23

Figure 12: Time to default, 5 OPD SAM sites, Oct- 2019 to Sep- 2020 (n=499 cases)

5.1.2 Qualitative data collection and analysis

5.1.2.1 Introduction

Five teams, each team with one supervisor and two enumerators (one male & one female) collected

the qualitative data. This was done over three days in 4 OPD-SAM sites as well as in 15 purposively

selected villages within the health facilities’ catchment areas of two districts (Chaghcharan and

Lal). Villages were chosen based on distance from the OPD-SAM site (both far and close).

Additionally, geographical differences were also respected for semi-urban and rural villages.

EPI data, with a list of villages was used to sort all the villages into three categories; secured, semi-

secured and unsecured. All the unsecured areas were omitted at the beginning of the assessment.

The techniques used include Semi-Structured Interviews (SSI), Focus Group Discussions (GD),

observation, and Key Informant Interviews (KIIs). The standardized SSI questionnaires were

translated to local Language Dari for better performance and guidance of the teams. During the

three days for qualitative data collection, our teams did 29 SSIs, 9 FGDs, and 14 KIIs.

For SSIs and FGDs, the teams focused on caregivers of defaulters, “Malik”, “Mullah”, caregivers of

children in program, men and women, teachers, head of health “Shura”, CHS, CHWs, nutrition

counsellors and health facility worker in charge of the nutrition programs. The term “Mullah” refers

to the religious leader while “Malik” refers to the village elder. Both Mullah and Malik are members

of the community health Shuras in the CBHC program. Multiple KIIs were conducted with the

nutrition officer of the BPHS, Nutrition assistant of WVI, and Nutrition Program Manager of AAH

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

0

20

40

60

80

100

120

140

Length of stay (weeks)

Co

un

tWeeks in programme before defaulting - all health centres

Median

Early Defaulter

24

office in Ghor province. When all the reported issues were discussed in detail and recorded, the

other KIIs were done with the in charge of the health facility.

The two principles of SQUEAC, triangulation, and sampling to redundancy were applied. At the

end of each day, all information was discussed, analysed, and classified as booster or barrier, and

the sources that reported the information were notified. To verify the information as a true barrier

or booster, it needs to be verified by several sources and methods. The Boosters, Barriers, and

Questions (BBQ) tool was also employed to enable the investigation of more information, which

came up as questions after each day's analysis.

5.1.2.2 Data compilation and analysis

The triangulated findings of the qualitative investigation were arranged in an overall list of boosters and barriers and organized by theme. The key observations are summarized below.

Table 3: Explanation of Boosters

BOOSTERS EXPLANATION

Good appreciation of the quality

of services

As the nutrition program is being implemented for the last

few years in the province, most of beneficiaries included in

the qualitative research mentioned that they have a good

appreciation of the nutrition program. This influenced

positively the healthcare seeking behavior

Strong community nutrition

program through CHW/FHAG

Surveillance activities at community level, with a network

of CHW screening children and referring them to health

facilities; the same CHW are raising awereness in the

community as it was mentioned by beneficiaries during

interviews.

This continuum of services helps the program to maximize

its coverage and helps the communities to have timely

access to the program.

Good awareness at community

level on the causes of

undernutrition

Most of the key informants as Mulas (the religious leaders),

school Teachers, Maliks (village elders), and the caregivers

of malnourished children who participated in the

qualitative data collection process, have shown a good

level of understanding on the main causes of malnutrition

and its prevention

No stigma associated to

malnutrition

Most of the residents interviewed in Ghor province stated

and confirmed that there is no stigma related to

malnutrition in the communities.This is a good factor for

early diagnosis, community mobilization and adherence to

treatment

25

Villages located near to HF have

good access and also women are

allowed to seek health services

Fortunately, some of the caretakers who were located near

the HFs confirmed their good access to the program, which

can boost the enrolment of malnourished children timely in

the program and their adherence.

Furthermore, as per afghan cultures/norms the women are

not allowed to travel alone for seeking health cares, but

fortunately, in Ghor province, the women were allowed to

seek health services and take their malnourished children

to receive treatment with or without Mahram (a person

who accompanied women for outside of the home) which

can increase admission and reduce defaulters.

Strong Referral System at the

villages which have CHWs and

FHAGs

The project implemented by AAH in the province has

trained health staff working in health facilities and

established a network of community health workers

involved in nutrition activities. This enabled a continuum of

nutrition services from community level to health facility,

with a good referral system.

Availability of IEC materials in HF

Considering the low literacy level especially in females,

adapted education sessions using IEC materials (posters…)

are very important to raise awareness of the caregivers and

their adherence to the nutrition program.It is good that this

was done in the visited Health Facilities

Providing Nutrition services

through Mobile Teams

Considering the existing low coverage of health and

nutrition services, the physical barriers to access to health

services, including long distances, hard weather conditions

in winter, lack of transport and transportation fees,

insecurity, mobile health teams are really important to

bring health and nutrition services in hard-to-reach areas.

Training and raising

Health/Nutrition Educations at

community

Over the last 3 years, AAH had capacity building activities

for health staff, CHWs, and FHAGs in the Lal, Dolatiyar,

and Chaghcharan districts. As result, 408 members of

Family Health Action (FHAG) groups were trained in 42

villages fo the province, strengthening the community

nutrition component as it was confirmed through

qualitative research.

Supporting of 6 HFs by Action

Against Hunger (AAH)

AAH with the support of 6 HF in three areas (Lal,

Chaghcharan, and Shahrak) in the province, plays a major

role in strengthening the health and nutrition system,

mainly in: 1- capacity building, 2- supportive monitoring, 3-

Distribution of IEC materials, 4- food demonstration at HF

level and community). The above measures were necessary

to complete the community nutrition package.

26

Table 4: Explanation of Barriers

BARRIERS EXPLANATION Quality of care at Health

Facility

Interviewees complained of poor quality of care when visiting

health facilities. This has a negative effect on their adherence to

the program.

Lack of community

nutrition program in all

areas

In villages where there was no ongoing community nutrition

program to raise awareness of the population, the level of

nutrition program was low, as well the adherence of

beneficiaries.

Absenteeism of HF staff

disrupting the health and

nutrition services

As some of the HFs are out of reach because of insecurity and

road blockage due to hard weather conditions and therefore less

supervised by the upper level, beneficiaries complained about

the absenteeism of healthcare workers.

Selling/Miss use of RUTF

At family level, the findings revealed the practice of sharing

RUTF with non-malnourished children, or even selling it; this has

a negative impact on the children admitted in the program, as the

quantity of RUTF is prescribed in specific quantity that can help

them to recover.

Poor Economic/lack of

local Transportation

Beneficiaries living in remote and hard to reach areas with poor

economic status mentioned the lack of local transportation

means and cost of transport as the strongest barrier to attend

the nutrition services and adhere to the treatment;.

Using traditional/arbitrary

treatment for Malnutrition

Due to lack of knowledge and awareness in the communities,

some caregivers prefer to give traditional treatment to

malnourished children or take them to healers;

Nutrition commodities

weak supply chain with

RUTF stock out/Shortage

RUTF stock out was the strongest barrier and has interrupted the

normal treatment stream of malnourished children in the month

of November 2020. The RUTF shortage is directly associated

with a very high defaulter rate, low cured rate and long duration

of stay. Nutrition commodities shortage, mostly the RUTF, can

seriously affect the quality of the program and the adherence of

beneficiaries

Lack of specific nutrition

staff in Provincial Hospital

Evidence from HFs staff and key informants interviews, and also

the SQUEAC assessment technical team's observations have

revealed that some of the health facilities didn’t have nutrition

counselor especially at provincial hospital: this affects the quality

of services and time dedicated to nutrition program.

Physical barriers to access

to Health facilities

Most of the beneficiaries and HFs staff complained about the

insecurity and ongoing clashes in the area where the

beneficiaries are receiving health and nutrition services. Apart

27

insecurity, long distances, lack of transportation means and fees

are among other factors blocking beneficiaries to have access to

the health system.

COVID- 19 Pandemic

The high spread of COVID- 19 strongly affected the economy of

the Afghan people, during the lockdown and the movement

restrictions that affected the trade, and was at origin of high

prices of 1st necessity items. The pandemic came to weight on an

existing weak health system, and reduced drastically the

utilization of health services, because of both restrictions in

movements and fear to attend health facilities (stigma,

misinformation, non-well informed health staff…)

6. STAGE TWO

6.1. Introduction

Analysis of quantitative and qualitative data from stage one revealed that the coverage of health and nutrition services was uneven. Some villages or areas had a higher coverage than other villages.

Therefore, Stage 2 was undertaken following 2 objectives:

1. To test our ideas for areas of potential high and low coverage 2. To confirm that coverage is uniformly low throughout the villages located far from the

health facilities and have little knowledge of the nutrition program.

The teams were trained for two days in active and adaptive case finding as well as anthropometric measurements (MUAC, weight, height/length) and oedema screening. Structured questionnaires to use for both covered and non-covered cases were developed and translated from English to Dari and the teams were trained for their use.

6.2. Hypothesis testing: distance to the OPD-SAM sites

During Stage one, distance to OPD-SAM sites to be a factor that potentially had an effect on

coverage was tested.

Distance to OPD-SAM services might not only affect coverage but also awareness of the

communities. The qualitative research revealed a higher level of knowledge about the program in

areas near OPD-SAM sites. On the other hand, interviews with community members (both men

and women) from uncovered cases highlighted that long distances to OPD-SAM sites were an

inhibiting factor.

Based on first stage findings, it was assumed that the areas far from the health facilities have low

coverage of nutrition services with few eligible SAM children in the program. Inhabitants of these

areas have less information on the nutrition program and treatment of malnourished children and

28

an opposite of this was assumed for the areas near to health facilities. These are the hypothesis to

test:

Part A: In areas close (within two-hours walking distance) to OPD-SAM services, coverage of the

OPD SAM program and awareness of the communities is high (more than 50%).

Part B: In areas far (beyond two-hours walking distance) from OPD-SAM sites, coverage of the

OPD SAM program and awareness of the communities is low (less than 50%).

Methodology:

As these hypotheses are related to the spatial distribution of coverage, to test these hypotheses,

a ‘small-area survey’ was conducted in 5 villages close (less than two hours walking distance) to

OPD SAM sites (Masjid Hazrat e Muhammad, Masjid Family Ha, Masjid Abobaker, Shur e

Muhammad Abad, Masjid Naw Abad). For comparison, 5 villages far from OPD SAM sites (beyond

two hours walking distance:Sar e Pul Taimani Ha, Jari Zard, Mullah Abdul Ghafoor village, Dahan

e Sokhta, Abdul Ghafar) were assessed. A complete CBHC village profile was used to categorize

villages as far (more than 2 hours walking distance from health facility) and as near (less than 2

hours walking distance). Then 5 villages were randomly selected from each category to build the

sampling frame of the small area survey.

Active and adaptive case finding was the method used for case finding.

A case was defined as “a child matching the admission criteria of the OTP SAM services” :children

aged between 6 to 59 months from the purposively selected villages, defined as SAM cases using

MUAC, W/H, Z-score and Oedema measurements.

When a case was found, the caregiver was asked whether the child was already in the program or

not. If the malnourished child found in a village was already in the OPD-SAM program, it was

classified as a “covered case”; if not in the program the child was considered as a “non-covered

case”.

For the awareness component, 10 househoulds were randomly selected in each villages and

caregiver of the child was interviewed based on awareness questionniare.

In each village, a guide was identified to take the team around the village and ensure each

household with a child aged 6-59 months was surveyed.

The LQAS (Lot Quality Assurance Sampling) tool was used to analyze the data. The Lot Quality

Assurance Sampling technique involves comparing the number of Covered cases found (Cin) with

a threshold or “decision” value (d).

If the number of covered cases (Cin) found exceeds a threshold value (d) then coverage is classified

as being satisfactory; coverage exceeds the standard.

If the number of covered cases found equals or less than a threshold value (d) then coverage is

classified as being unsatisfactory; coverage does not exceed the standard. The following formula

29

was used to classify coverage accurately and reliably, despite the small sample size, as satisfactory

(i.e., coverage meets or exceeds the standard) or unsatisfactory (i.e. Coverage does not meet or

exceed the standard): d = Decision rule; n = Sample size; p = Coverage standard.

In each type of village tested (far or near to OPD SAM site), a decision rule (d) was calculated based

on the total number of cases found (n) and the coverage standard appropriate to the context.

The total number of covered cases found in the small-area survey is then compared to d. [Threshold

value].

For this test, 50% was selected as the appropriate coverage standard in rural settings as per the

Sphere minimum standard for coverage of the OPD SAM site.

Results:

During this test, only active SAM cases were included. Therefore, recovering cases were excluded

from the results (shown in Table 6).

Table 5: Small area survey’s data collection plan

SUBJECT Village C-In C- Out Mothers Aware Mothers

Not Aware SUSPECTED LOW COVERAGE & AWARENESS VILLAGES

Sari Pul e Taimani 0 1 0 10

Jari Zard 1 0 3 7

Mullah AbdGhafoor 0 2 9 1

Dahan e Sokhta 0 4 5 5

Abdu Ghafar 0 1 2 8

TOTAL 1 8 19 31

SUSPECTED HIGH COVERAGE & AWARENESS VILLAGES

Masjid Hazrati Moh 3 1 8 2

Masjid Jami Familly 2 1 7 3 Masjid Hazrati Abubakr

1 0 6 4

Shura e Muh Abad 2 1 8 2

Masjid Naw Abad 0 1 10 0 TOTAL 8 4 39 11

Analysis

SUBJECT HIGH COVERAGE

VILLAGES LOW COVERAGE

VILLAGES AWARE NOT AWARE

SAMPLE SIZE (in)/MOTHERS

12 9 58 42

d = P

100 n x

30

COVERED CASES (in)/MOTHERS

8 1 39 19

COVERAGE STANDARD (P)

50% 50% 50% 50%

DICISION RULE (d)

=|12×50÷100|=6 =|9×50÷100|=4.5 d=|50×50÷10

0|=25 d=|50×50÷10

0|=25

INTERPRETATION

C-in (8) > d (6). The hypothesis is

validated

C-in (1) ≤ d (4.5). The hypothesis is

validated

(39) > d (29). The

hypothesis is validated

(19) ≤ d (21). The

hypothesis is validated

The test proved that both hypotheses were validated; In the villages located near OPD SAM site

the coverage and awareness of the community are high (more than 50%) and in the villages

located far from OPD SAM site coverage and awareness of the community are low (less than

50%).

The survey teams referred all the children who were SAM and not covered by the treatment

program to the nearest treatment site.

6.3. Prior building

6.3.1. Introduction

One important aspect of SQUEAC is the ability to combine the existing information with a small

sample to get the coverage estimate. The existing information collected in the survey gave just a

feeling of how coverage was likely to be. The Bayesian technique is used to correctly represent

the belief about coverage. The ‘Prior’ (the mode of the probability density) was developed based

on findings of Stage One and Stage Two, to assume the most likely coverage rate that the OPD-

SAM program expects.

To develop the prior in Ghor SQUEAC assessment, five methods were used to ensure

triangulation, which is an important principle in SQUEAC methodology: the average of the simple

scores, the average of the weighted scores, the median of the Histogram believe, the average of

Mind map and the concept map. The investigation team went through the boosters and barriers

(identified during Stage 1) and scored each one according to their relative impact on coverage. A

score between 1 and 5.5 (low and high effect) was allocated to each barrier and booster (100/the

maximum list of barriers (18) = 5.5). This shows that prior generated from the simple and weighted

scores is by the equal importance of each barrier. The process of scoring of boosters and barriers

is shown in the table below:

31

Table 6: Simple and weighted scores of Boosters and Barriers

Number Boosters Simple Score

Weighted Score

Barriers Simple Score

Weighted Score

1 Good understanding/Positive opinion regarding treatment of malnourished children

5.5 4 Miss behavior of HF staff/lack of transparency (RUTF and RUSF distribution)

5.5 5.5

2 Active and Trained of CHW 5.5 5 Lack of Health Educations to disseminate the key nutrition messages both at HF and community level

5.5 5.5

3 Good understanding on causes of malnutrition

5.5 4 Low commitment of HF staff 5.5 4.5

4 No Stigma about Malnutrition and They know sign and symptoms of Malnutrition

5.5 4.5 Selling/Miss use of RUTF 5.5 5.5

5 Availability of community level screening which has CHWs and FHAG

5.5 3.5 Poor Economic/lack of local Transportation

5.5 5.5

6 Villages located near to HF has good access and also women are allowed to seek health services

5.5 5 Lack of screening at community level 5.5 4

7 Strong Referral System at the village have CHWs and FHAG

5.5 5.5 Using traditional/arbitrary treatment for Malnutrition

5.5 4.5

8 Class room and Refresher training for the HFs staff (Nutrition Training)

5.5 3 RUTF Shortage 5.5 5

9 Active Supervision by MOPH, PPHD, CHA, Action Against Hunger

5.5 3 Geographical Complexity/So Cold weather/heavy snowing in Fall and Winter Season

5.5 5.5

32

10 Health/Nutrition Educations Though HFs, Mobile team of WVI, and CHWs/FHAG trained by Action Against Hunger

5.5 5.5 Long distance 5.5 5.5

11 Availability of IEC materials in HF 5.5 3 Women are not allowed to seek Health services without Mahram

5.5 5

12 Providing Nutrition Services through Mobile Teams by WVI

5.5 4 Poor filing system 5.5 3.5

13 Development and trained FHAG at 42 villages

5.5 3 High Defaulters: Lack of Default tracking and Follow up System

5.5 5

14 Supporting 6 HFs by AAH, Through Supportive supervision, training and providing IEC materials

5.5 4 Unavailability or poor quality anthropometry measurement tools

5.5 4.5

15 Lack of specific nutrition staff in PH 5.5 5.5

16 Insecurity 5.5 5.5

17 COVID- 19 Pandemic 5.5 5.5

18 Staff turn over 5.5 4.5

Calculation of the prior mode 77 57 99.0 90.0

77 57 1.0 10.0 Prior Mode =

𝑆𝑢𝑚 𝑏𝑜𝑜𝑠𝑡𝑒𝑟+(100−𝐵𝑜𝑟𝑟𝑖𝑒𝑟𝑠)

2

33

6.3.2. Weighted scores

The scores given to each factor depends on the number of “confirmed” qualification stated by the

different sources, methods, locations and the potential impact on coverage. To estimate the

possible significance of boosters and barriers, it is considered that by which methods and from

how many sources it is confirmed. A factor confirmed by fewer sources and few methods, with a

low weighted score is considered to have low significance, while those confirmed by several

sources, methods, locations and with a high weighted score are considered to have high

significance. Each booster and barrier were given a score ranging from 1 to 5.5.

The total sum of the boosters was added to the lowest possible coverage (0 + 57) = 57.0%

The total sum of the barriers was subtracted from the highest possible coverage (100–90.0)

=10.0%.

Prior mode; from the weighted boosters and barriers (57.0% + 10.0%)/2 = 33.5%.

6.3.3. Simple scores

All factors were given a score ranging from 1 to 5.5 based on the assumption of impact on

coverage.

The total sum of the simple boosters was added to the lowest possible coverage (0 + 77.0) = 77.0%.

The total sum of the simple barriers was subtracted from the highest possible coverage (100 –

99.0) = 1.0%.

Prior mode; from the simple boosters and barriers (77% +1.0%)/2 = 39.0%

6.3.4. Histogram prior

A histogram prior was developed collectively with all survey team members in the classroom as a

starting point for the prior development. Each coverage value (x axis) was discussed and a belief

of whether coverage is likely to be that value was determined (y axis). A prior mode (most likely

value for coverage) was determined at 61.53% for the OPD SAM program.

Table 7: Histogram Believe Individual Level

Coverage Perception by the Survey Teams

T# Individual Perception Team Perception

Team 1 35% 32%

20%

40%

Team 2 30% 30%

26%

35%

Team 3 45% 35%

33%

28%

Team 4 30% 32%

34

40%

25%

Team 5 45% 30%

10%

35% Table 8: Histogram Believe Team Level

Team 1 Team 2 Team 3 Team 4 Team 5

32% 30% 35% 32% 30%

Median= 31.67%

6.3.6. Mind Map

Another method which was used to estimate a prior is to count the total number of positive and

negative factors on the mind map constructed during Stage 1 of the SQUEAC. This includes

observations made during the quantitative data analysis and all of the positive and negative factors

identified during the qualitative data investigation. A total of 17 positive and 39 negative factors

were identified.

Prior mode from the Mind Map is 17%+(100−39%)

2= 39.0%

6.3.6. Concept Map

Following the finalization of the barrier and booster table, the teams worked together to draw

concept maps for barriers and boosters to illustrate the links between factors and how they link

them to the coverage.

Figure 13: Concept Map

35

By counting the links between boosters and barriers, it was possible to calculate another prior

estimation; it was possible to identify 15 positive and 27 negative links:

- Concept map prior estimation for OPD SAM = (0+15)+(100−27)

2= 44.0%

6.3.7. Prior mode

The average of these prior estimates for the OPD SAM program was calculated to produce an average prior mode (see Table 7).

Table 9: Prior Mode Calculation

No Prior contributing element OPD SAM program

1 Prior From Simple Scores 39%

2 Prior From Weighted Score 33.5%

3 Histogram Believe 31.67%

4 Mind Map 39%

5 Concept Map 44%

Average Prior Mode 37.43%

The prior mode value of 37.43% plotted for the OPD-SAM program using Bayes SQUEAC

Coverage Estimate Calculator (version 3.01). As the baseline SQUEAC assessment was done in

September of 2017 in Ghor province, and there was very little uncertainty about the value of prior

mode then + and -20 percentage point was used.

Therefore, for OPD SAM, with a prior mode of 37.43%, the minimum probable value was 17.43%

(37.43-20) and the maximum probable value 57.43% (37.43+20).

The conjugate analysis method used in SQUEAC requires the prior distribution to be summarized

by two numbers called shape parameters, αprior and βprior. These are calculated using the mode and

the minimum and maximum probable prior values as follows:

36

Figure 14: Parameters Calculation

Prior Mode For OPD SAM α Prior 19.3

β Prior 32.3

With the Alpha and Beta shape parameters, it was possible to plot the prior distributions on the

Bayes calculator.

Figure 15: prior distributions on the Bayes calculator

Prior Mode 37.43% Input the % value, and the rest will be converted to proportions.

Uncertainty 20% Input the % value without + or - signs, and the rest will be converted to proportions.

Minimum

Probable Value0.17

Maximu

m

Probable

Value

0.57

μ 0.37

σ 0.07

α prior 19.3

β prior 32.3

Now, set the α prior and β prior given above to the Bayes calculator to get the sample size.

Enter the (1) prior mode by averaging priors obtained by different methods (e.g. simple BBQ,

It is important to note that

the following formulae

require the value to be

converted into proportions,

not percentages.

37

The sample sizes required to complete the conjugate analysis were therefore, calculated to be 50

SAM cases for the wide area survey.

7. STAGE THREE: WIDE AREA SURVEY

The principal objective of Stage three is to provide an estimate for coverage across the selected

area. This firstly requires the development of likelihood, though a wide area survey, and then, the

use of a Bayesian conjugate analysis, combined with the prior and the likelihood to produce the

posterior coverage estimate. A two-stage sampling procedure was used to first select the village

to sample, then to carry out the survey in the community. It involved calculation of a sample size

of villages to be visited for the wide area survey.

In the first stage, the EPI village list was reviewed in coordination with the security and nutrition

focal points of AAH and CBHC officers of CHA in the province to exclude all the villages not

accessible due to poor security and geographical difficulties. Then the team has selected 15

villages using systematic Random Sampling method.

As the second step of the wide area survey, screening of children aged from 6 to 59 months using

weight-for-height z-scores, MUAC and oedema criteria was done through Active/Adaptive case

finding technique.

7.1. Minimum sample size of villages for the wide area survey

The sampling frame used in the survey consisted of the 4 selected health facilities catchment area.

The calculation of minimum sample size (villages) was based on the following parameters: n=50

(SAM cases) based on the sample size generated by the Bayes calculator, an average village

population of 41110, the percentage of children aged 6 to 59 months =16.2%11 and a SAM

prevalence of 2.5%12.

𝑁 𝑣𝑖𝑙𝑙𝑎𝑔𝑒𝑠 = ⌈𝑁

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑖𝑙𝑙𝑎𝑔𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑠 ×% 𝑜𝑓 𝑐ℎ𝑖𝑙𝑑𝑟𝑒𝑛 6 − 59 𝑚𝑜𝑛𝑡ℎ𝑠

100 ×𝑃𝑟𝑒𝑣𝑒𝑙𝑎𝑛𝑐𝑒

100 ⌉

𝑁 𝑣𝑖𝑙𝑙𝑎𝑔𝑒𝑠 = ⌈50

411 ×16.2100

×2.5100

⌉ = 30

Equation 1: Calculation of village sampling

A total of 30 villages was calculated based on equation 1 as illustrated above.

10 Source: Based on EPI micro plan update villages list- BPHS- Ghor Province. 11 Source: Based on SMART- Aug-2016 12 Source: Ghor SMART survey, 2016 Prevalence of SAM cases in the province.

38

The villages were selected through systematic random sampling since there was an updated list

of villages provided by the CBHC department of BPHC project in Ghor province.

7.2. Wide area survey Methodology

The wide area survey data collection took place during four days in the 30 selected villages.

Exhaustive screening of children 6-59 months old was done in all the villages through active

adaptive case finding (door to door). There were five teams composed of one supervisor and two

enumerators (one female and one male). Verification of the presence or absence of oedema,

MUAC<115mm and WHZ<-3SD was done. All cases found in the survey AND not covered in the

SAM treatment program were referred to the nearest OPD-SAM site with a referral slip. To

ascertain the reasons why those children were not in the program, their caregivers were

interviewed using a standard questionnaire.

7.3. Coverage estimations

A total of 561 children aged under five years were screened and a total of 43 SAM children were found.

Out of 43 total active SAM cases that were identified during the survey, 6 cases were already enrolled in the program. No case of edema was identified. 27 SAM cases were not in the program and 5 recovering cases in the program were found.

The most reliable, and widely suited coverage estimator currently available is the single coverage estimator and should be used for estimating SAM treatment program coverage: The estimates coverage using active SAM cases as well as recovering cases in the program and recovering cases not in the program. The following formula is used where Cin= covered SAM cases, Cout= uncovered SAM cases, Rin = recovering cases in the program, and Rout = recovering cases, not in the program:

Equation 2: Calculation of single coverage

𝑆𝑖𝑛𝑔𝑙𝑒 𝑐𝑜𝑣𝑒𝑟𝑎𝑔𝑒 =𝐶𝑖𝑛 + 𝑅𝑖𝑛

𝐶𝑖𝑛 + 𝑅𝑖𝑛 + 𝐶𝑜𝑢𝑡 + 𝑅𝑜𝑢𝑡

The Cin, Cout and Rin are all collected during the wide-area survey however Rout must be estimated. The number of recovering cases not in the program (Rout) is calculated using the formula below.

Equation 3: Calculation of Rout cases

𝑅𝑜𝑢𝑡 = 𝑘1 𝑥 (𝑅𝑖𝑛 𝑋

Cin + Cout + 1

Cin + 1− 𝑅𝑖𝑛)

The results of the wide area survey and the result of the calculations for Rout are presented in Table 11.

Table 10: Total SAM cases found during the wide-area survey

Subject SAM cases

Cases not in the program (Cout) 27

39

Cases in the program (Cin) 6

Recovering cases in the program (Rin) 5

Recovering cases not in the program (Rout) )estimated( 5

Total cases 43

7.4. Results of the wide-area survey

During the wide area survey, a total of 43 SAM cases (including 4 estimated Rout cases) were

identified in the 30 selected villages in the selected area of Ghor province. The denominator for

the single coverage estimate was 11 for SAM and the numerator was 43 SAM (Cin + Rin). Using the

Bayes calculator, the conjugate analysis was completed with the Prior parameters calculated for

the OPD SAM 31.6% (23.2% - 41.8%) with (p-value=0.2431) and (z-test=1.17).

The p-value for the final conjugate analysis is more than 0.05 indicating that the final estimate is

valid and can be reported as there is no conflict between the prior and the likelihood.

Figure 16: Wide Area Survey results

40

The posterior is seem between likelihood and prior. The curve in the posterior is tall with short

skinny tails illustrate the leptokurtic distribution and indicate that the wide-area has reduced the

uncertainty of the survey. This coverage estimate at 31.6% (23.2%-41.8%) is below than coverage

standard for rural contexts (>50%) for the OPD SAM program.

7.5. Reasons for not being in the program

The survey sought to get reasons why some children with SAM were not covered by the program.

This was done by interviewing all caregivers of children not covered by the program. The most

reported reason was financial insufficiency for transportation and lack of transportation, which

was immensely common in the far villages. Distance to the health facilities and other factors are

shown in figure 18 below.

Figure 17: Reasons of uncovered SAM cases

Survey limitations and challenges

• Insecurity: The insecure and unassessible villages were not assessed. They were excluded

from the sampling frame from the designing of the assessment plan to not jeopardize the

security of the survey teams on the field a well as the targeted population. This represents

a biais in the selection of the sampling for these surveys.

• Geographical complexity: Some of the areas in the province were hard to reach for both

survey teams and community members ; this is mostly related to the absence of roads, and

the blocage due to heavy snow in winter.

• No timely data check: The survey teams were not able to submit their data to the survey

manager on time due to the remoteness. Data were therefore analyzed at second stage

after completing the field data collection.

• Lack of suitable accommodation in the field if the team was staying for the night.

0 1 2 3 4 5 6 7 8 9 10

Lack of finances for the journey cost

Lack of transportation

Too far; Walking distance (>1hour)

Lack of support / mahram

Staff in Health Facility are rude and not welcoming

A familly member was sick

heavy snow and cold weather

Reasons for Uncovered Cases- Wide Area Survey

41

• Due to inaccessibility/insecurity, the AAH technical team was not able to do regular

supportive supervision from survey team in all the target areas.

• Lack of access to the Treatment cards & Registration book of Lopra BHC due to poor

coordination in advance with the HF. Therefore, the performances of this center was not

properly assessed.

• Due to difficulties to have access to the Ghor Qand BHC, the quantitative data of this HF

was not received timely and the analyzing process was delayed.

8. Conclusions and Recommendations

These SQUEAC findings portrayed a clear picture of the factors affecting the coverage of OPD

SAM programs and shown an estimated single coverage for the OPD-SAM program at 31.6%

(23.2% - 41.8%). The coverage estimate is below the SPHERE thresholds for rural settings that

must be of >50%. This means that 68.4% of all SAM cases are not able to have access and utilize

SAM services in these three districts (Chaghcharan, Lal, and Shahrak) of Ghor province.

However, this estimated coverage is higher than the coverage found during the 2017 SQUEAC

survey, which was 28.0% (95% CI: 18.3%-40.7%).

In Ghor province, both MAM and SAM programs are running for the last few years under different

implementing agencies. In the three targeted districts, 18 health facilities were offering OPD-SAM

services out of the total 43 health facilities in the province.

The assessment has helped not only to identify the main barriers and boosters to access nutrition

services but also to investigate these in more depth, allowing for the development of

recommendations and actions to overcome the barriers and to build on the boosters. Factors such

as poor supply chain of nutrition supplies, RUTF missuses at household level, COVID- 19 pandemic

impact on the health system, HR (Health facilities understaffed and high staff turnover),

geographical and climate complexity (cold weather, heavy snowing in fall and winter season), low

awareness of the program, and insecurity in most parts of the targeted districts were the biggest

barriers found during the qualitative data collection.

Apart the above-mentioned factors, long distance and lack of transportation means and money to

pay the related costs in all catchment areas of the health facilities especially in Shahrak, Lal and

some parts of Feruzkoh) districts are key factors hindering OPD-SAM coverage.

Despite this, there were numerous positive factors influencing the current OPD-SAM coverage

such as: good perception of the OPD-SAM services, absence of stigma, good awereness of the

communities related active community nutrition program workers (run by CHWs) in some of the

villages, and the improvement in cultural barriers: mothers were allowed to seek health services

for their undernourished children. Moreover, the trainings conducted with the support of AAH on

the IMAM guideline for HF staff improved the quality of services,.

42

The AAH technical team for the SQUEAC assessment in partnership with the PPHD, CHA (BPHS-

IP), WVI, UNICEF, ARCS and other nutrition sector stakeholders at the provincial level developed

key recommendations to foster improvements of OPD-SAM coverage in the assessed districts

based on these SQUEAC survey findings. The key recommendations quoted include:

Expand the number of MNHTs to the inaccessible/remote areas as well the coverage of

community nutrition program.

Strengthen supportive and formative supervision for HFs and plan trainings according to

the findings.

Ensure regular supply of the nutrition commodities, especially for RUTF.

Strengthen nutrition education at HFs and community level.

Strengthen follow-up and referral system between communities and Health Facilities for

detected undernourished cases

Strengthen reporting and feedback system of nutrition program

More details related to proposed recommendations are provided in the table 12 below.

43

Table 11: Table of Recommendations

Subject Recommendation Findings Actions to be taken Responsible people

When to do it

Level of priority

Nu

trit

ion

Pro

gra

m D

ocu

me

nta

tio

n a

nd

Re

po

rtin

g a

nd

ap

plic

atio

n o

f IM

AM

pro

toco

ls

Strengthen supportive and formative supervision

The analysis of supervision missions reports revealed that the capacity of nutrition workers need to be continuously built, so that the staff can be familiar with the IMAM guidelines

Increase supportive and formative supervision missions

PNO, CHA and

other implementation

partners

Starting from January,

2021

High

Increase the capacity of HFs staff in reporting

The analysis of treatment tools including patients treatment cards revealed the necessity of capacity building for health staff.

Conduct regularly trainings for Health staff in addition to formative supervision

PNO, CHA and other

implementation partners

As per the visit books of the supervisors checked by the survey teams, some of the health facilities were not supervised.

Ensure supervision visits are done regularly and well recorded in visit books

AAH, UNICEF, CHA,PNO

Starting from January,

2021

High

44

The low capacity regarding crowd control, screening, at waiting area, was highlighted, which compromise the respect of basic IPC measures

Conduct initial/refresher training on IMAM and IPC for all the HFs staff

PNO, CHA and other

implementation partners

High P

rofe

ssio

nal

ism

an

d b

eh

avio

r o

f H

Fs

staf

f

Increase the number of staff for conducting nutrition activities

During the assessment period, it was observed that some of the HFs did not have a nutrition counselor; a high turnover of staff was also noted

Ensure that each HF providing nutrition services has a dedicated staff. Pay efforts for retention of staff in HF

PNO, CHA and other

implementation partners

Starting from January,

2021

High

Work toward changing behavior

Most of the survey teams observed and heard from key informants among qualitative research that, the HF staff did not have always good communication and often playing missing behavior

Send formal letter through BPHS IP to HFs to ensure the presence of staff and appropriate behaviors toward patients

PPHD, CHA Starting from January,

2021

medium

Conduct BCC Training for HF staff

Strengthen the follow up and direct observation through BPHS supervisor when the HF staff is screening the patients (to ensure acceptable behavior toward these patients)

45

Aw

are

ne

ss a

nd

co

mm

un

ity a

pp

roac

h

Strengthen the community health and nutrition program activities and coverage

In some areas, there was no active community health workers.

Expand CHWs network and support the CBHC program at the community level in which the CHWs are not available

PNO, CHA and other

implementation partners

Provicial

CBHC plan for 2021

High

Increase the number of FHAGS to all villages as this is essential to strengthen referral and community nutrition activities

PNO, CHA and other

implementation partners

Starting from January,

2021

High

Reinforce the health and nutrition Educations and counseling sessions

The level of awereness of communities on health and nutrition matters is poor.

Increase the number of sessions of health and nutrition promotion at both community and HF levels

PNO, CHA and other

implementation partners

Starting from January,

2021

High

Disseminate IEC Material among all the HFs and HPs

PNO, CHA and other implementation partners

Starting from January,

2021

High

Strengthen the counseling sessions through Nutrition counselor

PNO, CHA and other implementation partners

Starting from January,

2021

High

Ge

ogra

ph

ical

C

om

ple

xity

/So

C

old

w

eat

he

r/h

eav

y sn

ow

ing

in

Fal

l an

d W

inte

r S

eas

on

an

d la

ck

of

tran

spo

rtat

ion

Strengthen the nutrition commodities supply chain

Recurrent stocks out of essential nutrition commodities are recorded (among other factors, the geographical complexity and lack of

Ensure that the forecast of supply of RUTF & RUSF is based on consumption and the stock replenished every 6 months

PNO, CHA and other

implementation partners

Starting from January,

2021

medium

46

acess to HF during winter season)

Revise the schedule of visits for children admitted in the program

Reduce the defaulter rate with visit done on a bi-weekly basis

Organize visits of the malnourished children on a biweekly basis

PPHD, CHA Starting from January,

2021

Low

Increase the coverage of nutrition services

Hard-to-reach areas are underserved by health facilities

Expand the number of MHTs to the inaccessible areas

PNO, CHA and other implementation partners

2021

provincial nutrition plan

High

The OPD SAM services are not available in all health facilities, creating long distances to access the services

Expand the OPD-SAM sites to HSCs

PNO, CHA and other

implementation partners

2021 provincial

nutrition plan

High

Fo

llow

up

sy

ste

m

Strengthen the continuum of services linking the community level to health facilities

Lack of effective referral and counter referral system was highlighted

Strengthen the link between the community network of community health workers and the health facilities

PNO, CHA and other implementation partners

Starting from January,

2021

High

Put in place a mechanism for defaulters follow up in the communities

AAH, UNICEF, CHA,PNO

Starting from

January, 2021

High

47

9. Annexes

Annex 1: Participants list of Ghor SQUEAC assessment.

Name Position Responsibility in SQUEAC

1 Dr. Muhammad Khalid Zakir Nut-Surveillance-SMART- PM

Leading SQUEAC assessment

2 Mr. Hidayatullah Amin Data Management Officer Data Entry Support

3 Mr. Aman Ullah Amani Nutrition Officer- BPHS Project Supervisor

4 Mr. Shah Nawaz Enumerator

5 Ms. Malalai Enumerator

6 Mr. Ghulam Sarwar Hariq Supervisor

7 Ms. Zainab Enumerator

8 Mr. Amanullah Enumerator

9 M. Mirza Nezami Supervisor 10 Ms. Shagufa Enumerator 11 Mr. Javed Rahimi Enumerator 12 Dr. Allah Daad Noorzad Supervisor 13 Mr. Ahmad Shah Enumerator 14 Ms. Meena Enumerator 15 Mr. Joma Khan Jaheer Supervisor 16 Ms. Nazia Ayoubi Enumerator

17 Mr. Abdul Sami Enumerator

Annex 2: Seasonal Calendar of Ghor province

48

Annex 3: Villages list, Selected for wide area survey.

HF Name Village Name Distance Population

1 ARCS BHC 785 7 اطراف مسجد جامع فامیلی ها

2 ARCS BHC 785 7 شوراي محمدآباد

3 ARCS BHC 785 15 شوراي ساحه گدام

4 Qala Pichii BHC 140 36 ده میرداد

5 Qala Pichii BHC 90 25 رزد سنگ وحول کهنه / شخ سنگک روغن قل

6 Qala Pichii BHC بالا و پایینکاریز 38 210

7 Qala Pichii BHC 140 43 آبرک روغن قل و قلعه

8 Qala Pichii BHC 84 23 دهن آبک و آبک

9 Qala Pichii BHC 140 27 دهن شور قل و بوم شورقل

10 Qala Pichii BHC 105 32 ده پیتاب شورقل و گم آب

11 Qala Pichii BHC 126 29 قریه میانه و سربغوندی

12 Qala Pichii BHC 210 32 آبرک و خوک کشته

13 Talkhak BHC و سفلی دهن سرخک علیا 33 720

14 Talkhak BHC 269 32 دهن آب پران وزیرقاش / جوی نو ده شان

15 Talkhak BHC 175 25 گنده جوی

16 Talkhak BHC 237 10 سروار بورگوج / زیر درخت

17 Talkhak BHC سفلارشک علیا / رشک 18 170

18 Talkhak BHC 245 26 شینیه علیا و نودیره

19 Ghor PH 1018 37 پشت جوي

20 Ghor PH 375 14 زیر جوي عمومي

Disease Oct-19 Nov-19 Dec-19 Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20

ARI

Pneumonia

Peptic Disorders Low Very High Low Very High

Diarrhoea

OPD-SAM

OPD-MAM yes

Cultivation

collection

Rainfull High

Snowing Low High

Cold Temperature Low High High Low

IDPs

conflicts High

Security issues

Childhood Top

Diseases

Nut- program

(RUTF/RUSF shortage)

Harvesting

Climate

High Very High High low

High High

High High High low

HighLow

the stock out of RUTF was only observed in the moth of November- 2020

High

High

very High

very High

Very High Low

Very High

yes

High

very high low

High

49

21 Ghor PH 1065 25 مسجد ابراهیم

22 Ghor PH 285 33 جر درختي ها

23 Ghor PH 923 26 فامیلي هاي سرپل دره قاضي

24 Ghor PH 788 25 مسجد حضرت خدیجه

25 Ghor PH 825 35 مسجد خالد بن ولید

26 Ghor PH 788 28 دهن جر زرد

27 Ghor PH 405 18 پشته افغان بسیم

28 Ghor PH 375 22 جر كلاغ ها

29 Ghor PH 398 23 مسجد جامه تیلك

30 Ghor PH 263 26 قریه امام حسین

Annex 4: HFs list of Ghor province

District HF Name OPD-SAM OPD-MAM IPD-SAM

Feruzkoh

Barakhana Yes Yes NA

Shawije Yes Yes NA

Zartali NA Yes NA

Prison Health NA NA NA

Ghor Qand Yes Yes NA

Ghalmin Yes Yes NA

Morghab Yes Yes NA

Lafra Yes No NA

Asparf NA NA NA

Dahor NA NA NA

MHT NA NA NA

Raghskan NA NA NA

Maidan Yes Yes NA

Ghalak Yar Folad NA Yes NA

Pahlosang NA Yes NA

Jandak NA NA NA

Ashtar khan NA NA NA

Sufak NA NA NA

TaqaiTemor NA NA NA

Charsada

Charsadah Yes Yes NA

Qalai Gohar NA Yes NA

Khafak NA NA NA

Dah Haji NA Yes NA

Dawlatyar Dowlat yar Yes Yes NA

Pusti Noor NA Yes NA

50

Dar e Kashraw Yes Yes NA

Shenye NA NA NA

Sharshar Lukayimazar NA Yes NA

Dolaina

Dolaina Yes Yes NA

Khajagan NA Yes NA

Sia chob NA NA NA

Qala-E-Naqshi NA Yes NA

Dahak Mirzakamaludin NA NA NA

Shajoy NA NA NA

Dehak Sukhtah NA NA NA

Dolaina MHT NA NA NA

Lal Wa Sarjangal

Lal Bazar Yes Yes Yes

Karman Yes Yes NA

Garmab Yes Yes NA

Qalai pechi Yes Yes NA

Safaid ab Yes Yes NA

Khameshor Yes Yes NA

Qaiqanak NA NA NA

Taka ghal NA NA NA

Talkhak Yes Yes NA

Naw e Qabristan NA NA NA

Safid Choshma NA NA NA

Chaparqul NA NA NA

Safid Guli NA NA NA

Pasaband

Sangan Yes Yes NA

Siny Yes Yes NA

Passaband Yes Yes NA

Talmastan NA NA NA

Nowrak NA NA NA

Dahan Jamal NA NA NA

Kakuri Yes Yes NA

Safid Bozz NA NA NA

Saghar

Saghar Yes Yes NA

Okhri Yes Yes NA

Jowaja Mirzadah NA NA NA

Fask NA NA NA

Tagaab Baluchi NA NA NA

Shahrak Ghar allah yar NA Yes NA

51

Manar jam Yes Yes NA

Shahrak Yes Yes NA

Kamenje Yes Yes NA

Jalga Mazar Yes Yes NA

Sartaidah NA NA NA

Khoja Bor NA NA NA

Surpan NA NA NA

Dahan e Hassar NA NA NA

Sarchashmah NA NA NA

Shahrak MHT NA NA NA

Tay Wara

Char der Yes Yes NA

Sar Holing Yes Yes NA

Tay Wara Yes Yes Yes

Sardah NA NA NA

Pay Hassar NA NA NA

Ashoqan NA Yes NA

Nili NA NA NA

Kilgo NA NA NA

Zerrni Yes NA NA

Detay NA NA NA

Charrah NA NA NA

Tagab Ashnan Yes Yes NA

Dai NA NA NA

Tolak

Ghow kosh Yes Yes NA

Dorrodi Jawaja Yes NA NA

Tulak Yes Yes NA

MHT NA NA NA

Dara -i-Magas NA NA NA

Annex 5: Ghor province Boosters, Barriers and Questions (BBQs)

52

Meth

odolo

gy: 28

Boosters Location Sources Methods No of responses

1 Good understanding/Positive opinion regarding treatment of malnourished children

JM,DK,KT,U-SHC,DQ,QP-BHC,ZB,MJ

G,A,I,D,F,M,G,B,N,

SSI,FGD,II 1,1,8,1,1,1,1,1,7,1,1,1,1,1,1,1,1,1,6,5,1,1,1

2 Active and Trained of CHW JM,MH,U-SHC,QP-

BHC E,D,I,P,Q,L SSI,FGD 1,1,1,1,1,6,1,1,1,1,1,1,1,1

3 Good understanding on causes of malnutrition

JM,DK,PH,MH,MJ,SQ,U-SHC,DQ,DP,ZB

B,I,C,A,D,F,G,M,H

II,SSI,FGD 1,1,1,1,1,8,1,1,5,6,7,1,1,1,

4 No Stigma about Malnutrition and They know sign and symptoms of Malnutrition

DK,Gh-BHC,SQ,GQ-BHC,DQ,DP,ZB,KT, U-

SHC A,B,I,D SSI,II,FGD

1,1,8,5,1,1,1,1,1,1,1,5,1,1,1,1,1,1,1,1,1

5 Availability of community level screening which has CHWs and FHAG

DK,DP,QP-BHC,U-SHC,MJ,SQ

C,G,D,A,G,M,i

SSI,II,FGD 1,1,1,1,1,1,1,1,1,1,6

6 Villages located near to HF has good access and also women are allowed to seek health services

DK,U-SHC,MJ,SQ,DQ,QP-

BHC,ZB C,N,D,A SSI,II,KII 1,1,1,1,1,1,1,1,1,1,1,1,1

7 Strong Referral System at the village have CHWs and FHAG

DK,MJ,QP,PH A,D,P,Q,L SSI,KII,II 1,1,1,1,1,1,1,1,1,1,1,1,1,1

8 Class room and Refresher training for the HFs staff (Nutrition Training)

PH,U-SHC,QP-BHC,MJ D,E SSI,KII,II 1,1,1,1,1,1,1,1,1,1,1,1,1

9 Active Supervision by MOPH, PPHD, CHA, Action Against Hunger

PH,U-SHC,QP-BHC D SSI,KII 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

10

Health/Nutrition Educations Though HFs, Mobile team of WVI, and CHWs/FHAG trained by Action Against Hunger

PH,MH,U-SHC,MJ,GQ,DQ,QP-

BHC,DP,ZB

D,A,I,F,M,G,J,P,Q,L

SSI,FGD,II,KII 1,1,1,1,1,8,1,7,1,1,1,10,1,1,8

53

11 Availability of IEC materials in HF PH,GQ-BHC,GQ,QP-

BHC, D,O Obs,KII,SSI 1,1,1,1,1,1,1,1,1,1,1,1,1,

12 Providing Nutrition Services through Mobile Teams by WVI

U-SHC,DP,ZB D,I,A,I,G,P,Q,

L SSI,FGD,KII 1,1,1,6,1,1,8,1,1,1

13 Development and trained FHAG at ## villages

U-SHC,PH D,D,P,Q,L SSI,KII,II 1,1,1,1,1,1,1,1,1,1

14 Supporting 6 HFs by AAH, Through Supportive supervision, training and providing IEC materials

U-SHC,SQ,DQ,ZB A,J,P,Q,L SSI,II,KII 1,1,1,1,1,1,1,1,1,1,1,1,1

Annex 6: Ghor province Boosters, Barriers and Questions (BBQs)

S/No Barriers Location Sources Methods No of responses

1 Miss behavior of HF staff/lack of transparency (RUTF and RUSF distribution)

JM,DK,SQ,KT,DP,ZB,GQ-BHC

G,I,C,A,H,O,J FGD,SSI,Obs 5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,

2

lack of Health Educations to disseminate the key nutrition message both at HF and community level

JM,KT,PH,DQ G,I,M,B,N,A FGD,II,SSI 5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,

3 low commitment of HF staff JM,GQ-BHC,ZB M,H,O II,Obs 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

4 Selling/Miss use of RUTF JM,DK,KT,DP,SQ M,I,B,G II,SSI,FGD 1,1,1,1,8,1,1,1,1,1,1,1,1,1,1,1,

5 Poor Economic/lack of local Transportation

JM,DK,PH,MJ,KD B,A,I,E,F SSI,II,KII 1,1,1,1,1,1,1,1,1,1,1,1,1,

6 lack of screening at community level JM,DK,SQ J,A,B,I SSI,FGD 1,1,1,5,1,1,1,1,1,1,1,1,1

7 Using traditional/arbitrary treatment for Malnutrition

Dk,KT,DQ, MH, MJ, ZB I,J,B, M, A SSI,GD,I 1,8,1,1, 1,1,1,1,7,1,1,1,

54

8 RUTF Shortage Dk,MH,U-SHC,MJ,GQ-

BHC,DQ,DP B,A,I,D,G,P,Q

,L II,SSI,FGD 1,1,8,1,8,1,1,1,1,1,10,1

9 Geographical Complexity/So Cold weather/heavy snowing in Fall and Winter Season

DK,PH,U-SHC,QP-BHC ,ZB

B,D,A II,SSI,KII 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

10 long distance DK,DQ,DQ,MJ,JM,PH,

GQ-BHC,SQ,QP B,F,M,G,I,E,A

,D SSI,FGD,II 1,1,7,1,5,1,1,1,1,1,1,1,

11 women are not allowed to seek Health services without Mahram

DK,PH,DQ C,A,J SSI,II,KII 1,1,1,1,1,1,1,1,1,1,1,1

12 Poor filing system PH,QP-BHC,GQ-

BHC,JM-BHC O, L,P,Q,L Obs,KII,II 1,1,1,1,1,1,1,1,1,1,

13 High Defaulters: Lack of Default tracking and Follow up System

MH,U-SHC,GQBHC,MJ,PH

E,D,P,Q,L SSI,II,KII 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

14 Geographical Complexity/So Cold weather/heavy snowing in Fall and Winter Season

GQ-BHC D,O,P,Q,L SSI,KII,II 1,1,1,1,1,1,1,1,1,1,1,

15 lack of specific nutrition staff in PH ACF,PH P,Q,L SSI,KII, Obs 1,1,1,1,1,1,1,1,1,1,1,1,1,1

16 Insecurity Dk,MH,U-SHC,MJ,GQ-

BHC,DQ,DP B,A,I,D,G,P,Q

,L SSI,KII,II

1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

17 COVID- 19 Pandemic Dk,MH,U-SHC,MJ,GQ-

BHC,DQ,DP B,A,I,D,G,P,Q

,L SSI,KII,II

1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

18 Staff turn our PH ,P,Q,L KII,II 1,1,1,1,1,1,1,1,1,1,1,1

55

Annex 7: common symbols used for the SQUEAC Assessment in Ghor Province.

13 BHC, CHC and PH are Health facilities and others are villages

Location13 Symbols Methods Symbols Sources Symbols

Ghor PH G-PH Focus Group Discussion FGDs Care taker of Malnourished children in the program A

Ghor Qand BHC+ GQ-BHC Semi-Structured Interview

SSI Care taker of Malnourished children not in the program

B

Talkhak BHC+ T-BHC Observation Obs Care taker of defaulter children C Qala Pichi BHC QP-BHC Informal Interview II Heath Facilities Staff D Jilga Mazar BHC JM- BHC Key Informant Interview KII CHW (M/F) E Provincial Hospital PH

Mula F

Dahan Kasi DK Malik G Kandak Topchi KT Teachers H Maidan e Hawayee MH

Community members I

Jari Mariha JM Dahia J Ushturkhan BHC U- BHC Village elder K Qala e Pichi BHC QP- BHC AAH Technical Team L Ghor Qand BHC GQ-BHC Head of Shura M Dara e Qazi DQ Male Care taker of malnourished children N Deh Pitab DP Survey Team O Zardak Bom ZB BPHS Nutrition Officer P Manijer M Provincial Nutrition Officer Q Shur Qol SQ

56

Annex 8: Admission Criteria of OPD-SAM/MAM

Admissions criteria for OPD-SAM/MAM

OPD MAM OPD SAM

MUAC ≥115 mm and <125 mm Bilateral Pitting Oedema (+1+2)

WHZ ≥-3 and <-2 MUAC <115 mm

WHZ <-3

Appetite Preserved

Alert