Nutrition Programme Coverage Assessment Report · nutrition) children was implemented in surrounding villages of health centres to better understand the extent of the coverage of

Coverage Assessment of the Integrated Therapeutic Feeding Program

Supported by ACF Uganda

Final report

Kaabong and Moroto districts Karamoja, Uganda

July 2011

ACF – Coverage assessment of the Therapeutic Feeding program – Kaabong, Moroto and Napak districts – July 2011 2

ACKNOWLEDGMENTS ACF in Uganda would like to thank the following institutions and individuals for their support:

UNICEF for providing financial support;

District Health Offices in Moroto, Napak and Kaabong for collaborating with ACF-USA in the

implementation of Integrated Therapeutic Feeding Program and coverage survey;

The team members (measurers, data recorders and interviewers) involved in the coverage survey;

The parents, caretakers, Village Health Teams (VHTs), and health centres staff for allowing the teams to conduct interviews, and for assisting in locating severe acute malnutrition cases.


TABLE OF CONTENTS EXECUTIVE SUMMARY ............................................................................................................................. 4 .I. INTRODUCTION .................................................................................................................................. 5 .II. OBJECTIVES ...................................................................................................................................... 7 .III. METHODOLOGY ................................................................................................................................ 8 .IV. RESULTS .......................................................................................................................................... 9

.IV.1. Coverage classification based on active case finding ................................................................... 9

.IV.2. Referral of cases...................................................................................................................... 11

.IV.3. Routine Nutrition Program data analysis ................................................................................... 11 .IV.3.1. Rates of admissions in OTCs .............................................................................................. 11 .IV.3.2. Indicators performances: .................................................................................................. 12 .IV.3.3. Overall performances by each OTC .................................................................................... 14 .IV.3.4. Data collected at health units ........................................................................................... 14 .IV.3.5. MUAC at admission ........................................................................................................... 15 .IV.3.6. Sources of referrals .......................................................................................................... 15 .IV.3.7. Information related VHTs’ activities ................................................................................. 16 .IV.3.8. Distance to travel for beneficiaries, VHTs, and defaulters ................................................. 17 .IV.3.9. Length of stay and Weight gain: ........................................................................................ 18

.IV.4. Barriers to access treatment .................................................................................................... 19 .IV.4.1. Moroto District ................................................................................................................. 21 .IV.4.2. Kaabong District ............................................................................................................... 21

.V. CONCLUSION ................................................................................................................................... 22

.VI. RECOMMENDATIONS ....................................................................................................................... 23

.VII. ANNEXES....................................................................................................................................... 24 .VII.1. ANNEX 1: Methodology ............................................................................................................ 24 .VII.2. ANNEX 2: IMAM Coverage survey form ...................................................................................... 28 .VII.3. ANNEX 3: Coverage survey failure form .................................................................................... 29 .VII.4. ANNEX 4: Referral Slip ............................................................................................................ 30 .VII.5. ANNEX 5: OTC sites in Kaabong and Moroto/Napak districts ...................................................... 31 .VII.6. ANNEX 6: Local understanding of malnutrition ......................................................................... 32 .VII.7. ANNEX 7: Active case finding data in Kaabong district .............................................................. 33 .VII.8. ANNEX 8: Active case finding data in Moroto district ................................................................ 34 .VII.9. ANNEX 9: Semi structured interview guide ............................................................................... 35 .VII.10. ANNEX 10: A guide for conducting interviews in the community .............................................. 36


EXECUTIVE SUMMARY

Karamoja is a complex context in which to work. A region that has the lowest development indictors in Uganda, including the highest rates of maternal and child mortality and malnutrition. The region has been

a protracted complex humanitarian emergency, which has received food aid for several decades, creating a level of dependency on international and national inputs rather than independence and coping

mechanisms to self-address issues relating to poor standards of food security and health. Humanitarian actors in the past few years have started to address this issue of dependency by implementing

development programs to strengthen the all layers of Karamoja, targeting programs from the individual and household through to regional authorities.

Action Against Hunger for its part has been engaged in developing the capacity of the health services to integrate the treatment of severe acute malnutrition in three of the districts in Karamoja as well as

activities ensuring food security and livelihoods together with water, sanitation and hygiene areas are addressed.

To better understand the progress of the integration of treatment of severe malnutrition ACF through the support of the District Health Offices conducted a coverage survey to better understand to what extent

the health services are able to reach the population for which it is charged to provide services . The coverage survey was conducted to identify to what extent nutrition treatment services are available and

utilized by the population. Sphere Standards indicate that Inpatient services should reach 20% of the beneficiaries and outpatient nutrition services should reach a minimum of 50% of th e population. The

coverage survey was conducted at the end of the initial year of implementation and was funded through the United Nations Children Fund.

ACF focused the coverage survey on the three districts of its area of support, Moroto, Napak and Kaabong

Districts of Karamoja. Simplified LQAS Evaluation of Access and Coverage (SLEAC) combined with elements of Semi Quantitative Evaluation of Access and Coverage (SQUEAC) methodologies were uti lized to carry

out the coverage assessment.

Using the above methodology, 48 villages were randomly selected, 25 from Moroto/Napak and 23 from

Kaabong. Health centre information including admission trends and performance indicators were used to assess the performance of each of the health centres, active case finding of malnourished (under-

nutrition) children was implemented in surrounding villages of health centres to better understand the extent of the coverage of the health services. Finally structured and semi-structure interviews were used

with health centre staff and beneficiaries to provide qualitative information about the program implementation.

The coverage survey reported on both point coverage and period coverage. Point coverage is the coverage at the time of the survey; alternatively period coverage looked at the coverage for the period of a

treatment. While point coverage was considered as not reaching the Sphere Standards of 50% with 37% and 41%, the period coverage which included recovering children produced better results with a greater than

50% coverage rate, 58.5% and 57.5% for Kaabong and Moroto respectively.

Factors identified as influencing the coverage extracted from interviews included, the distances and

difficulty reaching health services, which included security for women and children. The staffing at health services directly influences the health centres ability to provide comprehensive care and influences

waiting times for carers and patients.

Household responsibilities of especially for mothers‟ impacts on her ability to continue treatments and to

travel distances to access health care.

Karamoja continues to witness an increasing trend in the rates of malnutrition (under-nutrition). While

there has been a small overall improvement in the coverage of services related to malnutrition in Karamoja from the previous coverage service conducted in 2010, there remain considerable factors which

influence the uptake of treatment from families and provision of nutrition related services. While health services continue to improve over time, they also continue to struggle with the burden of work afforded to


them. Structural issues within health services continue to play a key part in the provision of treatment of malnutrition in Karamoja.

District health services and health centres in Karamoja continue to struggle to provide adequate qualified staffing levels in health centres, and nutrition especially severe malnutrition is not considered a life

threatening illness coverage will continue to remain low. The is a need for the continued active input from village health teams to consolidate and strengthen the case detection and follow-up children with

acute malnutrition are identified and are actively follow-up up to ensure compliance of treatment. The external pressures of household responsibilities, distances and security will continue to influence the

uptake and continuity of care of malnourished children in Karamoja.

More inputs into strengthening and developing the communities understanding of malnutrition, its causes

and prevention methods need to continue in Karamoja. At the same time, health service development and reinforcement in Karamoja is essential to address some of the basic causes of malnutrition in the region.

.I. INTRODUCTION

Médecins sans Frontières (MSF) handed over the management of Severe Acute Malnutrition (SAM) to Action

Against Hunger (ACF-International) i) in Kaabong district between August and November 2008, and ii) in Moroto district between October 2008 and April 2009.

Since then, ACF through a capacity building approach has supported District Health Offices (DHOs) in the

implementation of an Integrated Management of Acute Malnutrition (IMAM). In Kaabong district, ACF currently supports district health workers running Outpatient Therapeutic Care (OTC) in 23 Health Centers

(HCs) and Inpatient Therapeutic Care (ITC) in Karanga HC IV and Kaabong Hospital (2 ITCs). In Moroto district, ACF currently supports district health workers running OTCs in 10 HCs and 1 ITC (Moroto Hospital).

In Napak district, ACF currently district health workers running supports OTCs in 10 HCs and 1 ITC (Matany Hospital, Table 2). ACF supports the management of Severe Acute Malnutrition (SAM) - which is led by

health facility staff throughout the districts - by providing technical support to ensure quality.

An assessment was conducted in June/July 2011, in Kaabong, Moroto and Napak districts by ACF and DHOs

to assess the extent of coverage of these community-based therapeutic feeding programs.

Kaabong district comprises of nine sub-counties, covering 7,220 km2, with a population estimate of

266,7071 Moroto/Napak district comprises of eleven sub-counties, covering 14,351 km2, with a population estimate of 369,1312,3 (Table 1).

Table 1: A) Kaabong and B) Moroto/Napak District populations

A) Sub-counties Population

B) Sub-counties Population

Kaabong district

Kaabong Town Council 3,217

Moroto/Napak district

Moroto Municipality3 5,200

Kaabong rural 46,855 Kathikekile+Tapac 49,932

Loyoro 22,385 Rupa 40,404

Sidock 29,903 Nadunget 61,933

Kalapata 48,187 Ngoloriet 28,135

Kathile 33,317 Lotome 29,193

Kapedo 37,222 Lopei 20,720

Lolelia 18,405 Matany 39,605

Karenga 27,216 Lokopo 33,694

Total 266,707 Iriiri 60,315

Total 69,131

1 Kaabong population data World Vision 2009 2 Moroto/Napak Samaritan Purse population data World Vision 2009 3 UBOS population projection 2009


ACF and DHOs of Karamoja have collaborated developing a sustainable Nutrition Surveillance System that monitors the nutritional status of under-five children since December 2009. The 5th round of surveillance

conducted in May 2011 revealed in Kaabong district a prevalence of Global Acute Malnutrition (GAM) equal to 8.5% and a prevalence of Severe Acute Malnutrition (SAM) equal to 2.3% (Table 3). In Moroto/Napak

district, results showed that the prevalence of GAM was 13.3% and the prevalence of SAM was 2.3% (Table 3).

Table 2: OTCs supported by ACF in A) Kaabong and B) Moroto/Napak districts

A) Sub-counties OTC in HCs

B) Sub-counties OTC in HCs

Kaabong Town Council Kaabong TC Hospital

Moroto Municipality Moroto TC

Kaabong rural

Lomeris HC* Kathikekile Kakingol HC II

Lokolia HC-III

Tapac

Tapac HC III

Lomondoch HC II Lopelpel HC II

Lokerui HC* Kasiroi HC*

Loyoro

Lokanayona HC II Rupa

Rupa HC II

Loyoro HC II Rupa Kidepo HC III

Lochom HC-III Nadunget

Lopotuk HC III

Sidock

Kopoth HC II Nadunget HC III

Kakamar HC II Ngoloriet

Kangole HC II

Kalapata HC-III Ngoloriet HC II

Kalapata

Kamion HC-II Lotome Lotome HC III

Lokwakaramoi HC II Lopei Lopei HC III

Kathile Kathile HC-III Matany Morulinga HC II

Narengepak HC* Lokopo Lokopo HC III

Kapedo

Kapedo HC III

Iriiri

Lorengechora HC II

Kalamon HC II Iriiri HC III

Kocholo HC * Amedek HC II

Lolelia Lolelia HC-III Nabwal HC II*

Karenga

Karenga HC-IV

Lokori HC II

Pire HC II

Logangalit HC II

*OTCs opened in April 2011 and not included in the coverage survey

Table 3: Acute Malnutrition (wasting) among 6- to 59-month children, WHO 2006 Standards, no exclusion of outliers, 95% Confidence Interval

Indicator Kaabong Moroto/Napak Karamoja

GAM W/H< -2 z and/or oedema

8.5% (5.8% - 12.3%)

13.3% (8.9% - 19.3%)

12.8% (11.0% - 14.9%)

SAM W/H < -3 z and/or oedema

2.3% (1.0% - 5.0%)

2.3% (0.8% - 5.9%)

2.8% (2.1% - 3.9%)


Figure 1: Trends of SAM observed in Kaabong (blue line) and Moroto/Napak (red line) from December 2009 through May 2011.

Figure 2: Trends of GAM (observed in Kaabong (blue line) and Moroto/Napak (red line) from December 2009 through May 2011

In order to improve the government and communities‟ capacity to manage acute malnutrition, DHO and ACF train health staffs on IMAM and Village Health Teams (VHTs) on community screening and referral

system in Moroto, Napak and Kaabong districts.

Simplified LQAS Evaluation of Access and Coverage (SLEAC) combined to Semi Quantitative Evaluation of Access and Coverage (SQUEAC) methodologies were uti lized to carry out the coverage assessment. The

process included:

Analysis of nutrition program data (rates of admissions and indicators performances since January 2010,

date at which the last coverage survey was conducted, and data obtained at health centres level the month prior the coverage survey),

Conduction of interviews (with lay people, VHTs, OTP staff, and caretakers of beneficiaries) as well as active and adaptive case finding.

.II. OBJECTIVES

To classify and estimate the coverage of the IMAM program in Kaabong, Moroto/Napak districts.

To identify and refer severely malnourished children not covered by the IMAM program.

To identify barriers to service access.


.III. METHODOLOGY

The coverage survey was implemented using a rapid and cost-reduced SLEAC methodology combined with

elements of a SQUEAC approach.

The SLEAC method classifies program coverage for a service delivery unit or Health Centre (HC) and provides the category of coverage (ranging from low to high coverage). The approach is mainly based on

active/adaptive case finding at village level. The component of SQUEAC approach that was used during this assessment included a combination of quantitative (routine program data) and qualitative

(information collected from a variety of informants in the community), and in order to attempt providing a detailed view of barriers to program access (Figure 3).

Figure 3: SLEAC and SQUEAC in assessing program coverage4

Therefore, this programme‟s coverage assessment was based on:

Analysis of routine nutrition program data (admissions, exits, defaulters, home locations of

beneficiaries and VHTs, sources of referral, referral monitoring, MUAC at admission, weight gain, length of stay) to identify areas which suggest high or low coverage.

Conducting informal and semi-structured interviews: Information was collected from target communities, beneficiaries, and health staff to explain and better inform the program data and build on the hypothesis of high or low coverage.

Active and adaptive case finding was conducted to identify nearly all current SAM cases in a sampled village and assess whether cases are currently enrolled in OTCs.

For more in-depth information relating to methodology, village selection and case identification refer to annex 1

4 From the SLEAC manual DRAFT, June 2011


.IV. RESULTS

In Moroto/Napak districts, 25 villages were selected; 18 interviews total were conducted (5 lay people, 5

VHTs, 3 mothers of beneficiaries, and 5 OTP staff interviews); and exhaustive active/adaptive case finding (all manyattas of the selected villages were visited; see data collection and results paragraphs below).

In Kaabong district, 23 villages (randomly selected) were covered; 25 interviews were conducted (8 of lay

people, 6 of VHTs, 7 of mothers of beneficiaries, and 4 of OTP staff); exhaustive active/adaptive case finding (all manyattas of the selected villages were visited; see data collection and results paragraphs

below).

.IV.1. Coverage classification based on active case finding

Kaabong: Point coverage (at the time of the survey) = 37%

Period coverage (representative of a full OTC treatment period of time) = 58.5%

Moroto/Napak: Point coverage (at the time of the survey) = 41%

Period coverage (representative of a full OTC treatment period of time) = 57.5%

Table 4: Coverage survey classification according to SPHERE standards, based on covered SAM cases

Criteria Kaabong Moroto/Napak

Target SAM cases sample size 36 36

Achieved SAM cases 27 58

Standard 50% 50%

Threshold value 0.5*27=13.5 0.5*58=29

SAM cases covered 10 24

Coverage classification Unsatisfactory

10<13.5, 10/27=37%

Unsatisfactory

24<29, 24/58=41%

Table 5: Coverage survey classification according to SPHERE standards, based on covered SAM cases + MAM currently recovering in the program

Criteria Kaabong Moroto/Napak

Target SAM cases sample size 36 36

Achieved SAM cases +recovering cases 27+14=41 58+22=80

Standard1 50% 50%

Threshold value 0.5*41=20.5 0.5*80=40.0

SAM cases covered 10 24

Recovering cases covered 14 22

Total covered 24 46

Coverage classification Satisfactory

24 20.5, 24/41=58.5%

Satisfactory 46 40.5,

46/80=57.5%

Alternatively, coverage was classified as moderate in both districts based on three-tier classification (Table 8 and 9 for Moroto/Napak and Kaabong respectively).


Table 6: Three-tier classification of coverage based on covered SAM cases + recovering cases for Moroto/Napak.

A) Moroto/Napak

a. SAM

cases

b. SAM

cases covered

c. Recovering

cases

d. Total in

treatment

(=b + c)

e. Threshold

30% =(a +c)

*0.3

f. Threshold

70% =(a +c)

*0.7

g. Classificatio

n5

Kakingol HC II 3 2 0 2 0.9 2.1 Moderate

Kangole HC II 3 1 2 3 1.5 3.5 Moderate

Lotome HC II 2 0 1 1 0.9 2.1 Moderate

Loputuk HC III 4 3 1 4 1.5 3.5 High

Nadunget HC III 2 2 1 3 0.9 2.1 High

Morulinga HC II 3 1 4 5 2.1 4.9 High

Ngoloritet HC II 2 0 1 1 0.9 2.1 Moderate

Rupa HC II 4 0 0 0 1.2 2.8 Low

Rupa Kidepo HC III 7 3 1 4 2.4 5.6 Moderate

Lopei HC III 10 4 8 12 5.4 12.6 Moderate

Lokopo HC III 8 3 0 3 2.4 5.6 Moderate

Lorengechora HC II 3 3 0 3 0.9 2.1 High

Iriiri HC III /

Amedek HC II 7 2 3 5 3.0 7.0 Moderate

All 58 24 22 46 24.0 56.0 Moderate

Table 7: Three-tier classification of coverage based on covered SAM cases + recovering cases for Kaabong.

B) Kaabong

a.

SAM cases

b.

SAM cases

covered

c.

Recovering cases

d.

Total in treatment

(=b + c)

e.

Threshold 30%

=(a +c) *0.3

f.

Threshold 70%

=(a +c) *0.7

g.

Classification

Lolelia HC III 0 0 1 1 0.3 0.7 High

Lochom HC III 0 0 1 1 0.3 0.7 High

Kopoth HC II 2 0 0 0 0.6 1.4 Low

Kakamar HC II 4 2 3 5 2.1 4.9 High

Lokerui HCII 0 0 0 0 0 0 N/A

Lokolia HC II 1 0 0 0 0.3 0.7 Low

Lomodoch HC II 2 2 1 3 0.9 2.1 High

Kaabong TC HC 1 0 1 1 0.6 1.4 Moderate

Kalapata HC III 2 0 0 0 0.6 1.4 Low

Kathile HC III 8 3 2 5 3.0 7.0 Moderate

Loyoro HC II 3 3 1 4 1.2 2.8 High

Lokanayona HC II 0 0 1 1 0.3 0.7 High

Karenga HC IV 2 0 2 2 1.2 2.8 Moderate

Lokori HC II 0 0 1 1 0.3 0.7 High

Pire HC II 2 0 0 0 0.6 1.4 Low

All 27 10 14 24 12.3 28.7 Moderate

5Coverage classification: If d is less than e, coverage is low; if d is equal or above e and less than f, coverage is moderate; if d is equal or above f, coverage is high


.IV.2. Referral of cases

Identified cases of severe and moderate cases in the coverage survey, not already enrolled in either

therapeutic feeding programs or supplementary feeding programs were referred for treatment to the nearest OTC/SFP or to the location preferred by the caretaker.

.IV.3. Routine Nutrition Program data analysis

.IV.3.1. Rates of admissions in OTCs

In both districts, rates of admissions increased from February to March in 2010, and from February to April

in 2011, this is before the beginning of the rainy season (before households start preparing their land for cultivation and planting) (Figure 4 and 5). Increased admissions also coincided with the end of the lean

season in pastoral areas (January through March), and with the beginning of the lean season in agro-pastoral and agricultural areas (around April when households are running out of food stocks from previous

harvest).

Although May is considered as the peak of the hunger gap in Karamoja, which has been supported by high

prevalence of GAM and SAM reported in nutrition surveillance system. The significant increase in admissions from February to April and tending to decrease in May 2011 indicates that the peak of the

hunger gap may occur a bit earlier than expected, i.e., around March/April (rather than in May).

Figure 4: Admissions trends Kaabong, January 2010 through June 2011


Figure 5: Admissions trends Moroto/Napak districts, January 2010 through June 2011.

Figure 6: Seasonal Calendar July 2010 – June 2011

Very importantly, DHO and ACF trained Village Health Teams (VHTs) in April 2011 which led to active case

finding pro-actively done at community level, and may have contributed to the significant increases in admissions observed in April 2011.

Program objectives had the expected admissions to be 4500 admission from July 2010 to June 2011. Up to the end of June 2011, the program had experienced more than expected admission in the three districts of

operation. Total admissions for this period were 5694 children less than 5 years of age.

.IV.3.2. Indicators performances:

In 2010, in both districts, performance indicators were below SPHERE standards except for the death rates. Rates of defaulters were particularly high from July to October 2010 (Defaulters=39% in Kaabong in

September 2010 and = 45% in Moroto in October 2010, Figure 4).

The poor performances obtained from August through October in 2010 in Kaabong and Moroto coincided

with the end of the lean season/beginning of the crop harvests. Anecdotal evidence suggests that families may have prioritized field activities rather that bringing children at OTCs during this critical period of the

year.


In addition, there was a shortage of Plumpynut® (PPN) that started in July 2010 that also explains the

drop of performances indicators throughout October 2010.

During the end of 2010 in Kaabong, and March/April 2011 in Moroto, health centers staff received trainings

which contributed to improve the overall program performances.

In Moroto in 2011, compared the second half of 2010, rates of cured were promisingly on the rise

(especially since March 2011, Figure 7).

Performance indicators improved significantly in 2011 especially in Kaabong where the rates of defaulters

and of non-respondents decreased and met the SPHERE standards until May 2011 (Figure 8).

Figure 7: Performances trends for Outpatient Therapeutic Care, Moroto/Napak, Jan 2010-June 2011.

Figure 8: Performances trends for Outpatient Therapeutic Care, Kaabong district, Jan 2010-June 2011;


.IV.3.3. Overall performances by each OTC

In order to assess the homogeneity of the situation in terms of indicator performances among HCs, each

HC indicator performances in 2010 were compared with those of the same HC in 2011 (Table 10). In Kaabong, the situation seems clearer than in Moroto. Kaabong showed small improvements whereas,

Moroto overall had improvements but these were insignificant, and should be classified as having similar performances as the previous year.

Table 8: Overall look at indicators’ performances of each health unit of Kaabong and Moroto/Napak districts, where health staff are supported by ACF in IMAM implementation

Kaabong Moroto/Napak

2010 2011 2010 2011

Lochom - + Morulinga -/+ -/+

Lolelia - - Kangole -/+ -

Kapedo -- -- Lotome - -

Kamion# - - + Lopei - +

Kalapata - + Lorengechora - - -

Lokolia - + Amedek + +

Kathile -/+ -/+ Iriiri - -

Kaabong TC + + Nadunget + -/+

Karenga - + Rupa Kidepo + ++

Kopoth - + Loputuk -/+ +

Loyoro + + Lokopo - - +

Lokori + + Moroto TC# -/+ -

Pire -- -- Rupa HC II - -/+

Lobalangit* + ++ Ngoloriet -/+ -

Lomondoch* + ++ Kakingol - - - -

Lokwakaranoe* + ++ Lopepel# + -/+

Kakamar* - + Tapach# - - -

Kalamon* + +

+ 2 OTCs opened in April 2011

NA Lokanayona* + -

+ 4 OTCs opened in

April 2011 NA

*OTCs opened in March 2010

#OTCs not included in the coverage survey, because of insecurity threats in Tapach and Lopelpel HCs in

Moroto and in Kamion in Kaabong, and because of the urban setting for Moroto Town Council HC.

.IV.3.4. Data collected at health units

In order to obtain further indications about the extent of coverage in both districts, the following Nutrition program data were collected (for a small sample of health units for a small sample of children):

i. MUAC at admission,

ii. referral monitoring and main sources of referrals,

iii. home location of beneficiaries, and

iv. number of outreach sessions conducted the month prior coverage survey.

In Moroto, Nadunget, Lopei, Loputuk, and Kakingol HCs were visited, in Kaabong, Lokwakaramoi, Kamion, Lokori, Karenga, Kalimon, and Kapedo HCs were visited and above information collected.


In addition, weight gain and length of stay were analyzed.

.IV.3.5. MUAC at admission

The objective was to assess late admissions, which reflects problems with case finding and recruitment in therapeutic feeding program (low coverage). Moreover, late admissions are often associated with a longer

period of stay, high rate of defaulting, and therefore with poor outcomes.

In Moroto, results showed that 57% of the children enrolled were admitted with a MUAC equal or below

110 mm (26% in Kaabong) while admission criteria is MUAC < 115 mm (Figure 9 and 10).

Figure 9: MUAC at admission in Moroto/Napak districts.

Figure 10: MUAC at admission in Kaabong district.

.IV.3.6. Sources of referrals

In order to assess referral monitoring performances and to obtain information about sources of referral, in

visited HCs, health workers were asked to retrieve what were the main sources of referral for the currently enrolled children: self-referral, or referred by VHTs, or referred after screening at HC (while the

child was brought for other medical reasons); or referred by an hospital, or referred by and SFP.


It‟s worth noting that in some HCs, sources of referral couldn't be clearly established as VHTs lacked of

referral s lips. For instance, in Loputuk HC, VHTs do not issue a referral slip, they instead lead the children identified as severely malnourished to the HC.

In Kaabong, 45% of admitted children were referred by VHTs (48% in Moroto/Napak), and 55% were referred after screening at the health unit (11% in Moroto/Napak). In addition, in Moroto/Napak, 1% of

enrolled children were brought at the OTC by their caretaker, and 40% of enrolled children were referred by Supplementary Feeding Program (SFP) staff.

This clearly indicates that in both districts, the capacity of VHTs needs to be further strengthen community screening and referral system through:

i. an increased awareness of malnutrition,

ii. a better outreach that should lead to timely detection and referral of severely malnourished children.

.IV.3.7. Information related VHTs’ activities

In Moroto/Napak, health workers were asked information related to VHTs and they shared their perception

regarding VHTs‟ involvement and capacities in conducting activities under their responsibility. The information obtained were summarized in Table 11 (Table 12 for Kaabong) and confirmed that VHTs need

to be better supported as it appeared that VHTs may not conduct outreach sessions and barely do cases follow up in the community.

Table 9: Information obtained from Moroto/Napak health worker regarding VHTs

MOROTO/NAPAK Nadunget HC III Kakingol HC II Lopeei HCII Kangole HCIII Loputuk HCII

Number of VHTs involved per HC

48 but 3 are inactive

No information available

76 16 48 but 3 are

inactive

Social mobilization sessions

done by VHTs

Conducted in 24

villages in June

No information

available none none none

VHTs received training on the following topics: Screening using MUAC and

based on edema, management of fever,

malaria and pneumonia

Good/

satisfactory perception

Good/


Good/


Good/


Good/


Accuracy of VHTs during

screening

Few cases referred don‟t

meet admission criteria.

No information

available adequate

No information

available Inadequate

VHTs reporting capacity Some VHTs are

illiterate. No information

available Inadequate


Illiterate (9 out

of 48 VHTs can write and speak

English

Adherence to admission and discharge protocols

Follow IMAM guidelines


good done Follow IMAM guidelines

Availability of functional

equipment

Equipments are available and functional.

Referral slips inadequate.

No information

available available

1 functioning

scale at HC

VHT have MUAC

tapes. No referral

slips. Equipments are

available

Staff IMAM training 10 trained

2 not trained No information

available all all all

Protocols, formats,

implementation aids Available

No information

available inadequate adequate adequate

Plumpy nut shortage 1 week in June No information

available In May In May 1 week in June

VHTs do cases follow up none No information

available inadequate none none


Table 10: Information obtained from Kaabong health worker regarding VHTs

KAABONG Lokori HC II Kapedo HC III Kalimon HC

II Lokwakaramoe

HC II Karenga HC IV

Number of VHTs involved 15 29 48 16 36

Soc ial mobilization sessions done by VHTs

twice in June

Lorengechora-

23/06 Nabinyonae-

16/06 Itanyia-30/06

Not done in June

Done twice in June

Done in June

VHTs receive training Screening (MUAC

and edema)

Screening (MUAC and edema)

Screening and referral

system.

Screening and

referral.

Screening and

referral.

Accuracy of VHTs during

screening adequate

Adequate. Challenged in

referral monitoring

Most cases referred by

VHTs meet the criteria

adequate adequate

VHTs’ reporting capacity. Only 2 out of 15 VHTs don‟t know

how to write

No reporting is

done

Some VHTs

are illiterate Inadequate

No specific

reporting format

VHT do cases follow up Take children to

HC rarely

Take children to

HC

no Do follow up

Adherence to admission and discharge protocols

Follow IMAM guidelines

good Inadequate Follow IMAM guidelines

adequate

Availability of functional

equipment

Equipments are

available and functional.

MUAC tapes available.

Referral slips

inadequate.

MUAC tapes

available

Equipments available and functioning

VHTs have MUAC

tapes, No referral slips

MUAC tapes

available, No referral slips

Staff IMAM training all all all all all

Protocols, formats, implementation aids

Available adequate adequate adequate adequate

Plumpynut® shortage No shortage In April No shortage For the entire month of June

No shortage

.IV.3.8. Distance to travel for beneficiaries, VHTs, and defaulters

In order to address whether the distance that beneficiaries have to travel to reach HCs from their home

location can be a problem in accessing to treatment, or to assess is the defaulters are living far away from an health unit, the time (in hour) one need to travel to reach an OTC was gathered during visits to HCs.

The same information was asked to VHTs as well.

In both districts, a significant proportion of defaulters were found to live within one hours walk from an

OTC (Figures 11 and 12) which is roughly equivalent to a 5-km distance, i.e., within the HC catchment area. This indicates that more support should be brought to VHTs to strengthen their case follow-up

activities.


Figure 11: Distance to travel to reach an OTC in Moroto/Napak districts.

Figure 12: Distance to travel to reach an OTC in Kaabong district.

.IV.3.9. Length of stay and Weight gain:

To further assess OTCs performances, average length of stay and average weight gain were analyzed.

Length of stay:

In Moroto/Napak, out of the 15 health units for which data were available, only 4 showed to have an

average length of stay significantly longer than the recommended 60-day period of treatment (Figure 10). In Kaabong, out of the 11 HCs for which data were available, only 2 showed to have an average length of

stay significantly longer than the recommended 60-day period of treatment (Figure 11).

Weight gain:

In Moroto/Napak, only 3 out of 15 HCs showed to have an average weight gain equal or above the recommended minimum weight gain of 5 g/kg/day (Figure 13).

In Kaabong, only 3 out of 11 HCs had an average gain below the recommended minimum weight gain, which indicates overall acceptable program efficiency of the OTCs in that district (Figure 14).


Figure 13: Average Length of Stay (blue bars) and weight gain (solid red line) per OTC in Moroto/Napak district.

Figure 14: Average Length of Stay (blue bars) and weight gain (solid red line) per OTC in Kaabong district.

.IV.4. Barriers to access treatment

The factors affecting access to treatment were analyzed under five headings: outreach, standard of

service, community, follow-up of defaulters and barriers (physical and human). The information on the above factors was gathered through simple informal and semi structured interviews. These were

developed through discussions with caretakers of beneficiaries, lay people, program staffs, DHO representatives and enumerators so as to build an understanding and explanation of program performance

indicators as well as exploring reasons to explain the coverage findings.


Semi-Structured Interview Response Summary-Moroto and Kaabong Districts

Outreach and referrals: VHT and SFP registered the highest number of referrals. Some referrals were done by screening at health centres. However, children referred by VHTs are not given referral s lips which

makes follow up on the do not attend and defaulters too complicated. Some times VHTs follow up the referred cases by physically escorting the caretakers to the health centres. Sensitization/social

mobilization was done by health staff and VHTs in 24 vi llages attached to Nadunget health centre III. Outreach services by VHTs is negatively affected poor motivation, lack of referral slips, lack of

transportation to reach health centres daily and wrong MAUC tape readings resulting into rejection cases. Outreach is done by VHTs, health workers and Andre Food Consult (AFC).

Standard of service: A total of 80 Health centre staffs had been trained on IMAM and treated SAM cases and support supervision done by ACF monthly. ACF-DHO extends support to the health centres through meetings and supervisory visits. Weekly distribution of therapeutic supplies was done in health centre.

Beneficiaries received correct amounts of both nutritional and medical supplies with exception therapeutic feed stock out reported in a few health centres. VHTs were adequately trained on screening

for malnutrition using MUAC tapes since January 2011; however, a few of them have been actively involved in the IMAM enrolment. Nevertheless, the standard is compromised by increased workload on

staffs that have multiple tasks especially when OPD patients are many. In such circumstances OTC beneficiaries are served last after patients in OPD which results into long waiting hours. Some

communities reject VHT services claiming that VHTs measure their children to be paid. This clearly indicates that communities are not well informed about the role of VHTs. VHT reading inability of MUAC

tapes have resulted into rejection cases of children. Absenteeism of some health staffs due to meetings, workshops, leave days and other personal reasons affect the performance negatively. Selling and misuse of

RUTF by caretakers leads to high levels of non-respondent and long length of stay for children in the program. Breaks in RUTF supply chain has often contributed to delays in the healing process and some

caretakers thinking that the program has been closed thus not taking back their children for treatment.

Physical and human barriers: Difficulties in means of communication and transport between health

workers and VHTs due to long distances and insecurit y that makes it too dangerous to travel. Poor enrolment of children and low turn up of referred cases. Caretakers of moderate children who were once

enrolled in HOTMAM still ask for Plumpydoz® and accuse health workers for segregation. Hard work load on mothers in search for food for their household survival that compromises with taking children to health

centres and sick care takers who are unable to take children to health centres for treatment. Inaccessible routes to the health centres that are blocked by flooding rivers. Program day not rhyming with days that

caretakers are available.

Follow up of the defaulters: This was not being done by VHTs due to lack of feedback and defined

methods of following up defaulters and DNA cases.

Community practices: Caretakers had a good understanding of malnutrition. This was evident with the

local terms used in to mean signs of malnutrition i.e. „akikarit‟ for wasting and „lobute‟ for oedema. More so, they knew the age group most affected, i.e. children below five and t he causes. Other signs noted

included; loss of appetite, fever, diarrhea, cough, loss of weight, oedema and dehydration. The noted causes included; Rainy season aligned with mosquitoes that cause malaria and coldness, poverty, lack of food/hunger, poor chi ld care practice, early child weaning, and negligence from caretakers. The

knowledge was gained through health centre staffs, VHTs and fellow caretakers. Most Caretakers are aware of treatment places and the type of treatment received. This is referred to as “odii” or “emodok”

meaning Plumpynut®.

However, caretakers normally engage in activities such as firewood collection, charcoal burning, stone

breaking, brewing, and generally fail to take their children for treatment in good time. Stigma associated with malnutrition makes some caretakers ashamed to be identified with a malnourished child. In addition,

perception that Plumpynut® does not work causes vomiting and diarrhoea and death especially in Nadunget affect demand for treatment i.e. one caretaker claimed that a friends child died when it was

given Plumpynut®).


Community still reject and abuse VHTs claiming that they are paid through measuring their children.

Caretakers still take it for granted not to continue with treatment in OTC once they are discharged from ITC/SFP which results into relapses.

.IV.4.1. Moroto District

The interview analysis indicated that 34 severely malnourished cases were not covered in the OTP.

Data collected on reasons for coverage failure of the cases above, indicated that the majority of respondents (33; 97.1%) were aware that their children were malnourished. The respondents reported that

their children suffered from diarrhea, fever/malaria, cough/TB, rectum prolapsed, hunger and stunted growth. Among these 90.9% (30) knew where treatment could be obtained and cited the following reasons

for not attending: inadequate child care, lack of referral, long distance and insecurity. These are illustrated in Figure 15 below.

Figure 15: Reasons provided by caretakers of children detected and not covered, Moroto/Napak District, July 2011

0 1 2 3 4 5 6

Dangerous to travel

Lack of child care

Mother/ care taker sick

Too dangerous to travel

Program is too far

Need to be referred and no one to do so

Rejection of other children

Program closed

Program not goos

Program runs on wrong days

Long waiting hours

Ashamed to go to health center

Child is in SFP

Child was in program and defaulted

Child was rejected previously

Others

From the data 13(43.3%) children of the respondents who knew of the treatment programs had their children admitted in the treatment program. Ten of these children‟s condition had improved and been discharged from the program, 2 defaulters and 1 was discharged because the child was not responding.

.IV.4.2. Kaabong District

Simple interview analysis indicated that 18 severely malnourished cases were not covered in the OTP of

which 14 (93.3%) of the respondents were aware that their children were malnourished and had knowledge about the treatment program. Two of the severe uncovered cases did not have coverage failure forms and

2 were not aware that their children were malnourished. The respondents reported that their children suffered from diarrhea, fever/malaria, cough /TB, body rash and thinning/wasting. They cited the

following reasons for not attending as illustrated in figure 1 below.


Figure 16: Reasons provided by caretakers of children detected and not covered in Kaabong District, July 2011.

0 1 2 3 4 5

Child in SFP

Child/sibling was in program and …

Child /sibling was in TC/SC and …

Do not know where to go

lack of child care

Mother/ care taker sick

Need to be reffered and no one to do …

Program is too far

Program staff are rude

From the data 4(28.6%) children of the respondents who knew of the treatment program had their children previously admitted in the treatment program. One of these children‟s condition had improved and been

discharged from the program, 2 defaulters and 1 was discharged because the child was not responding.

.V. CONCLUSION

The results of the 2011 coverage survey identified point coverage has changed little from the 2010 survey, where both Moroto and Kaabong showed an unsatisfactory coverage result. Alternatively in 2011, the

period coverage has been added to look at coverage over a period of treatment which showed that there was satisfactory.

While the program aims for a minimum coverage level there continues to be a number of service delivery and external factors that continue to affect program coverage. These include:

The direct involvement of the VHT in the treatment and follow-up of children enrolled in the program

The late admission of children in the three districts

The perception of severe malnutrition is viewed by health staff, VHTs and the communities

Community understanding of IMAM activities

Distances to access health care and follow-up children for caretakers and VHTs

Improved supply structures to ensure that health services have the nutritional and medical supplies to provide treatment

Family and household responsibilities of mothers in the care of families and household food provision

Security related to moving to health services for treatment

While many of these issues are able to be addressed on the programmatic side of the integration of IMAM in health services, some of the major external factors such as distances and security remain outside the

scope of the program.


.VI. RECOMMENDATIONS

This report provides a number of final recommendations related to the integration of IMAM within health

centres Moroto, Napak and Kaabong on the results.

Continued strengthening of the collaboration between health services and VHT

Stronger awareness and ownership of IMAM at the health centre level

Stronger referral services by VHT and a greater emphasis on active case finding within villages in

all districts

Improved awareness and understanding of services available and malnutrition in order to reduce the unfounded myths associated which childhood malnutrition in Karamoja

Reinforcement of follow-up services from VHTRs in relation to children enrolled in feeding programs

Strengthen health staff and communities on practices associated to infant and young child feeding practices

While security and distances needed to travel to health services need to be serious ly looked into and addressed to ensure a greater uptake of treatment of children and their continuation within nutrition

programs, it remains outside the realms of the program to provide recommendations these issues. Alternative methods of service delivery in relation to the treatment of severe malnutrition may need to be looked into, such as decentralizing services to the village level.


.VII. ANNEXES

.VII.1. ANNEX 1: Methodology

The number of villages to assess was determined on the basis of the following formula 6:

Note: 0.2 represents the percentage of under five children, i.e., 20% of the total population

Target number of SAM cases calculation

The target number of SAM cases (= n) to be found during the survey was designed using the SQUEAC

calculator software (Figure 3) and was equal to 36 in both Kaabong and Moroto/Napak.

Figure 3: SQUEAC Calculator7

Calculation of the median village population:

In each district, for each HC running an OTC supported by ACF, all villages located within the HC‟s

catchment area were listed (HC‟s catchment area has a 5 km radius, although because of the lack of detailed maps in Karamoja, it was difficult to accurately identify villages being indeed within this

perimeter).

6 SQUEAC methodology draft 2nd of June 2011 7SQUEAC calculator is available for download on the Brixton Health website: http://www.brixtonhealth.com/squeaclq.html

This would be the expected

coverage based on what was obtained from 2010 coverage

survey.

Error levels were set at +/-10%

Calculator gave n=36, which means that our target was to find 36 SAM cases during the

survey, in each district.

=


All villages and areas known to be inaccessible (lack of roads) or known to be prone to insecurity threats

were removed from the list.

Village median population was calculated using Excel and median village population was 941 for

Moroto/Napak, and 827 for Kaabong district.

SAM prevalence used:

Using a low SAM estimate helps to ensure that the survey will achieve the target sample size and that all, or nearly all, current and recovering SAM cases in sampled villages will be found4. Therefore, the

prevalence of SAM with exclusion of outliers (SMART flags) was used (Table 4).

Table 4: Severe Acute Malnutrition (wasting) obtained in May 2011, (WHO 2006 S tandards, 95% CI, with

exclusion of outliers).

Indicator Kaabong Moroto/Napak

SAM

W/H < -3 z and/or oedema

1.6%

(0.6% - 4.5%)

1.4%

(0.4% - 4.7%)

The suitable SAM estimate was calculated using a value mid-way between the point estimate and the lower 95% confidence limit4,8 for the latest prevalence of SAM obtained from the round of surveillance

conducted in May 2011:

Estimate prevalence of SAM = SAM - ((SAM – low CI)/2)

Therefore, for Moroto/Napak, prevalence = 1.4 – ((1.4 – 0.4)/2) = 0.9%; and for Kaabong, prevalence = 1.6 – ((1.6 – 0.6)/2) = 1.1%.

Number of villages (nvillage):

The number of villages (nvillage): all the needed parameters for the calculation of the number of villages for

each district obtained above were then used in the formula:

An addition of 15% of nvillage was considered to take in account the proportion of referred children who do

not attend the program, defaulters, and the fact that the village list per HC was not accurately made because of the lack of detailed maps in Karamoja.

For Moroto/Napak: n = 36; median village population = 941; prevalence = 0.9%

nvillage = 21.25 + 15% = 24.4; therefore 25 villages to be randomly selected

For Kaabong: n =36; median village population = 827; prevalence = 1.1%

nvillage = 19.8 + 15% = 22.75; therefore 23 villages to be randomly selected

Village sampling:

Cluster sampling using population proportional sampling (PPS), such as that used for SMART surveys, is not appropriate for coverage survey4 as it gives a greater chance to highly populated villages to be selected.

Instead, a spatial stratification method was used to stratify by HC‟s catchment area with a fixed number of villages systematically randomly selected from a complete list of villages within each HC catchment

area. To do so, a sampling interval was calculated by dividing the number of villages to be assessed (nvillage) over the total number of villages listed.

8 SLEAC methodology draft 2nd of June 2011

=


For Moroto/Napak:

total number of vi llages listed = 150; nv illage = 25; Sampling interval = 150/25 =6

For Kaabong: total number of villages listed = 198; nv illage = 23; Sampling interval = 198/23 =8.6=8

Training

In each district, 12 enumerators were trained for 3 days on anthropometry, local understanding of

malnutrition, active and adaptive case finding, interviewing skills and referral of cases. A pilot test was conducted on the 3r d day of the training.

Training and data collection took two weeks in each district during the month of July 2011.

Data Collection

Active-adaptive case finding

Upon arrival in selected villages, Enumerators informed the local leaders and sought their permission and assistance in locating key guides and VHTs. The VHTs were asked to bring Enumerators to severely

malnourished children and those already admitted in OTCs. The local understanding of malnutrition and pictures (showing severely malnourished children) were used to guide identification of target children.

The teams assessed manyattas exhaustively within the sampled villages.

Anthropometric measurements of the identified children were taken (weight, height, MUAC, presence of

bilateral oedema, calculation of weight/height based on WFH z-score tables, and age estimate based on calendar of events). All information were recorded on the coverage survey form (Annex 1). The coverage

failure questionnaire (simple structured interview) was administered among caretakers whose severely malnourished children were not covered in the OTC program and those children were referred to the

nearest OTC (Annexes 2 and 3). This was used to provide an understanding of the failure to seek treatment at an appropriate OTC/ITC.

The case-definition

The definition of SAM cases was in line with OTC admission criteria:

-Mid Upper Arm Circumference (MUAC) < 115 mm and height >65cm, OR

-W/H9 < -3 SD10, OR

-Presence of bilateral edema (any grade).

Active case finding data interpretation

SAM CASES: The total number of SAM cases (children identified through informant during the coverage survey).

COVERED SAM CASES: The number of SAM cases currently enrolled in an OTC program at the time of the coverage survey.

RECOVERING CASES IN TREATMENT: the total number of children currently enrolled in an OTC at the time of the survey = COVERED SAM CASES + RECOVERING children.

Point coverage (at the time of the survey) is the coverage obtained during the survey period, and takes in account SAM cases only, and was calculated as followed: COVERED SAM CASES / TOTAL SAM CASES x 100

Period Coverage (reflecting the treatment period of time) takes in account TOTAL IN TREATMENT and

reflects coverage throughout a longer period than the survey period of time itself, and was calculated as followed: (COVERED SAM CASES + RECOVERING) / (TOTAL SAM CASES + RECOVERING) x 100

9 Weight for Height

10 Weight for Height Z- scores according to WHO standards


Coverage classification based on 50% SPHERE Standards (rural setting)

Decision rule=d=SAM CASES x (50/100)

Coverage is classified as unsatisfactory when COVERED CASES is less than d; as satisfactory when COVERED

CASES is equal or above d.

Alternatively, coverage classification can be based on three-tier classifications, and there are two

coverage proportions:

p1 : The upper limit of the “low coverage” tier or class; p1=30%;

p2 : The lower limit of the “high coverage” tier or class; p2=70%.

Low coverage class runs below p1; Moderate coverage class runs from p1 to p2; High coverage class runs

above p2.

Informal & Semi-structured interviews

The coverage failure form (Annex 2) was filled out by conducting a semi-structured interview with caretakers of SAM cases not enrolled in any therapeutic feeding program. Informal interview were

conducted with VHTs and OTCs, and with community members (lay people) and caretakers of beneficiaries through focus group discussions (Annex 8) organized most of the time before the round of active/adaptive

case finding in the selected villages. Interview findings were analyzed in XMIND (creation of mind map to understand and analyze factors affecting access to service). Positive and negative factors were analyzed

under five headings: outreach, standard of service, community, follow-up and barriers (physical and human). A mind map was developed providing i)a global understanding on the reasons behind program

coverage classification revealed during the assessment, and ii)recommendations.


.VII.2. ANNEX 2: IMAM Coverage survey form

IMAM Coverage Survey Form

Surveyed village: __________________ Distance from SC/OTC (km): _________ Date surveyed: _________Team: _____

1.Full name of child

2.Sex (M/F)

3.Age (months)

4.Weight (0.1kg)

5.Height (0.1cm)

6.MUAC (mm)

7.Odema (Y/N)

8.Is the child a

severe case (W/H

< -3 z and/or oedema

and/or MUAC <115 mm)

(Y/N)

9. If yes, is the child

currently enrolled in an

OTC? (Y/N)

10.If no, not severe anymore,

but moderate:

1. The child is a recovering

case enrolled in an OTC?

2. The child was in an

OTC, discharged, relapsing

3. Not applicable*

11.Notes: Why have you

led us to a child who is neither a severe nor a

recovering moderate case?

*Not applicable means: or the child is severe (answered yes to question 8), or the child is normal. Severe cases in SFP are not covered. Administer a “coverage failure” form for these cases and record that

the child is in SFP. Administer the “coverage failure” form for all severe cases that are not covered (i.e. not in OTC).

All severe and moderate cases that are not covered should be issued with a referral slip and given instruction to caretaker about when and where to take their child.


.VII.3. ANNEX 3: Coverage survey failure form

Survey Cluster: ____________________ Surveyed village: _________________________________ Date: _________________________ Team Number_______________________________________

Full name of child: _________________________________________________________________

What do you think is wrong with your child? Enter answer_______________________________________________________________________

Do you think this child is malnourished? Yes |__| No |__| If NO then STOP!

Do you know of a program where this child could be treated?

If NO then STOP! Yes |__| No |__|

Why is this child not being treated for malnutrition? Do not read these answers to the respondent. After each answer prompt by asking “Any other reason?”

Tick the appropriate box for each answer given. More than one box may be ticked.

Answers notes

Child is in the supplementary feeding program

Lack of childcare / help with children (not willing to… detail why)

Mother / carer sick

Ashamed to go to the center

The program is closed / not running any more

I need to be referred and there is no-one to do this

Do not know where to go

Program is too far away

That program is for people in another camp / village

It is too dangerous to travel

My husband or family will not let me go

Program staff request money (detail: heard it, experienced it?)

Program staff are rude or difficult

Program runs on the wrong days

Waiting times are too long

Child (or sibling) was rejected previous ly

Child (or sibling) was in TFC / SC and discharged

Child (or sibling) was in program and defaulted (reason?)

Other children were rejected

Program is not good (detail)

Other (detail)

Was your child previously admitted to the program? Yes |__| No |__| If yes, why is he/she not in the program anymore?

□ Defaulted (when…..why….) □ Condition improved and discharged by the program (when?)

□ Discharged because the child was not recovering (when?) □ Other

Thank the career and refer case to the nearest OTP (give referral slip)


.VII.4. ANNEX 4: Referral Slip

Date: _____________________

Child name: ________________ Care taker Name: ____________________ Address: Sex: Age:

Weight: ________ Height: ________WHZ__________MUAC_________ Oedema: Y/ N

Nutrition status: SAM MAM referred to: __________________________

During nutrition surveillance program quarterly data collection, the team screened and identified this

child to be malnourished.

Thank you for attending to this child.

Name of enumerator: _________________________sign____________ Sub county____________________________

Village________________________________


.VII.5. ANNEX 5: OTC sites in Kaabong and Moroto/Napak districts

Lopelipel HC

Tapac HC

Kakingol HC

Napak

Moroto

Kaabong


.VII.6. ANNEX 6: Local understanding of malnutrition

Kaabong

Wasting/extreme thinness/marasmus ikarit (severe)/ ebothiarit (at risk)

Oedema (swelling of legs) natelewa

Puffy face lowul

Big belly lokapet

Before weaning the child mother gets pregnant which

results in poor health & nutritional status of child tutukan

Vulnerability (people with problems with eg food insecurity)

akuliako

Children who are not eating emam ekibure ka akimuj

Orphan ikoki

Poor birth spacing/children in overcrowded household akituny

Children weaned early due to pregnancy of mother akitabo ikoku

Households without food ekal ngolo ka eropirop

Children who are currently sick with fever or diarrhea amwanith ka akuwan (fever)/akiurut (diarrhea)

Children who are often sick with fever or diarrhea ngidwe ngulu ediakaka amwanith kori akiurut

HIV/AIDS lodiim

Literally broken home indicating familial & social problems

Divorce ekal ngolo atiakathi ekile ka aberu

Child headed household ekal koki

Household suffering with alcoholism ekal ngolo kameran

Child living with step-parents ikoku ngini kijokuno

Orphans living with grandparents ngikokiok ngulu iboyete ka tata kec kori ka papaa kec Very weak child emam ngigup/agogong

Helpless child apalago

TFP (OTC/ITC) kitanae

Moroto

Visible ribs Erogo A child with Pale hair Ikoku ngini ejalim/ enyagaka ngitim Baggy pants Erinyito ngikaosios Extreme thinning/ wasting Ikarit/ asenyit Edema/ puffy face Lobute Old man‟s face Emojongiarit ereet Very sick child Ikoku ngini iumiara Children who are currently sick with fever or diarrhea Ngidwe ngulu emwanikinit kori iurusete Children who are oftenly sick with fever or diarrhea Ngidwe ngulu emwanunuiete ka kiuresete Children who are not eating/ no appetite Ngidwe ngulu emam ekibure ka akimuj Poor birth spacing/ children in overcrowded household Ngidwe ngulu itunyunitae Helpless child Ikoku ngini palag Orphan Ikoki HIV/AIDS Lodiim Defaulters Ngulu ethalanarete TFP(OTC/ITC) Eyai ikoku nenika odi/ imodok Divorce Atyaka Child headed household Ekal ngolo koki Household suffering with alcoholism Ekal ngolo eriamunit ngica kotere emeret Child living with step parents/ uncle/ aunt Ikoku ngini iboyete ka ngiyeneta Orphans living with grand parents Ngikokiok ngulu iboyeta ka papaa kec kori tata

kec Household without food Ekal ndolo emam akimuj


.VII.7. ANNEX 7: Active case finding data in Kaabong district

Subcount

y Parish OTC name Village

Distanc

e betwee

n

village and

OTC (km)

# of

chilbren met

SAM

cases

SAM cases

covered

SAM cases

not covere

d

Recovering

cases in OTC

MAM

cases in SFP

MAM cases

not enrolle

d

Norma

l cases

Lolelia Lolelia Centre

Lolelia HC III Piyoitu 1.5 2

0 0 0 1 0 1 0

Sidok

Kathimeri Lochom HC III Kalolet 3 3 0 0 0 1 2 0 0

Longaro Kopoth HC II Lourwong 5 4 2 0 2 0 1 1 0

Kakamar Kakamar HC

II Kitelore

4.5 10 4 2 1+1relapsing 3 2 1 0

Kaabong

Rural

Lokerui Lokerui HCII Lomoruitae 2.5 2 0 0 0 0 0 1 1

Lokolia Lokolia HC II Komithka 3 4 1 0 1 0 1 1 1

Kaimese Lomodoch HC

II Kaiwele

3 5 2 2 0 1 0 1 1

Kaabong

TC

Komuria Kaabong TC

HC

Komuria West 3 3 1 0 1 1 1 0 0

Biafra Karongo 3 3 0 0 0 0 1 1 1

Kalapata Kalapata Kalapata HC

III

Kalonyangait

2 1 5 2 0 2 0 2 1 0

Kathile

Kamachrikol

Kathile HC III

Urut Kapel 6 5 1 0 1 0 1 3 0

Lorengrchora 4 5 5 2 3 0 0 0 0

Kathile

Usake 5 9 2 1 1 1 1 4 1

Moru Angirisiria 2 2 0 0 0 1 0 1 0

Loyoro

Toroi

Central

Loyoro HC II

Nyangakop 4

2 1 1 0 1 0 0 0

Toroi West Mading 0.5 2 1 1 0 0 1 0 0

Lorengechor

a Lorengechora

3.5 4 1 1 0 0 0 0 3

Lokanayona Lokanayona

HC II Ligot

2 4 0 0 0 1 3 0 0

Karenga

Loyoro Napole

Karenga HC IV

Loyoro south 2 4 0 0 0 1 2 1 0

Nakitoit South 6 3 1 0 1 0 1 1 0

Karenga Nalemoru 2 3 1 0

1 relapsin

g 1 0 1 0

Lokori Lokori HC II Nangolemoru 1 5 0 0 0 1 1 3 0

Pire Pire HC II Nakeluo 5 3 2 0 2 0 0 1 0


.VII.8. ANNEX 8: Active case finding data in Moroto district

Subcounty

Parish OTC name Village

Distance

between village

and OTC (km)

# of

chilbren

met

SAM cases

SAM

cases cove

red

SAM

cases not

covered

Recove

ring cases in

OTC

MAM cases in

SFP

MAM

cases not

enroll

ed

Normal case

Kathikelkile

Lia Kakingol HC

II Nakiloro

8 3 3 2

1relapsing

0 0 0 0

Lotome Lokoret

Kangole HC

III Lopeny

3 6 3 1 2 2 0 1 0

Kalokengel Lotome HC

III

Looro 3 6 0 0 0 1 5 0 0

Nadunget

Nariamarega

e Lolet

5 4 2 0 2 0 1 0 1

Loputuk

Loputuk HC

III

Lokwakwa 0.5 2 2 2 0 0 0 0 0

Nasinyonoit 5 3 2 1 1 1 0 0 0

Nadunget HC III

Looi 3 7 0 0 0 0 5 2 0

Nadunget Loletyak 4 5 2 2 0 1 2 0 0

Matany

Morulinga Morulinga

HC II

Kokweta 1 3 2 1 1 1 0 0 0

Lokupoi 2.5 6 1 0 1 3 0 0 2

Ngoloriet Narengemor

u Ngoloriet

HC II Ajokomolteny

3 11 2 0 1+1relap

sing 1 1 4 3

Rupa Rupa

Rupa HC II Lomario 1.5 7 4 0 4 0 0 3 0

Rupa Kidepo

HC III

Lokorete 2 5 3 3 0 1 1 0 0

Lobuneit Lokitelapis 8 7 4 0 4 0 0 3 0

Lopei

Lopei

Lopei HC III

Loteede 3 5 3 0 3 2 0 0 0

Lokudumo Naoyakorete 12 2 1 0 0 0 0 1 0

Lomusia 5 6 2 1 1 3 0 1 0

Nakwamoru

Lokapangate

ng 14 2 1 0 1 0 0 1 0

Loparipar 7 8 3 3 0 2 2 1 0

Naregae 16 3 0 0 0 1 0 1 1

Lokopo

Akalale

Lokopo HC

III

Adipala 5 1 1 0

1relapsing 0 0 0 0

Lorikitae Lolita 5 4 3 0 3 0 1 0 0

Lorikitae 5 14 4 3 1 0 10 0 0

Iriiri

Lorengechora

Lorengechora HC III

Lobok 4

3 3 3 0 0 0 0 0

Iriiri

Iriiri HC III /

Amedek HC II

Lokachikit 7

12 7 2 5 3 0 2 0


.VII.9. ANNEX 9: Semi structured interview guide

Lay people from the community

1. Understanding of child hood illnesses. Common illnesses and their symptoms/signs in the community among children in that location.

Ranking of illnesses.

Timing of illnesses in the year and possible reasons.

Most serious illnesses and reasons. Knowledge of treatment places or areas.

2. Understanding of malnutrition

If malnutrition has not been mentioned from above, bring pictures

Ask what the condition they see is.

Ask if they have ever seen such cases in their community and what was done about it. Knowledge of places or programs that treat such conditions.

3. Awareness of treatment services

Any opinion about existing treatment programs (place, what they give, what they call the treatment and who can take the treatment).

Awareness of children receiving the treatment.

4. Program coverage

Information about children who have the problem but are not going for the treatment and why.

5. Perception of the service/IMAM and defaulting

What people say about the service

How children are identifies for the service (criteria of admission/identification). About defaulting and possible reasons.

6. Recommendations if any.

Program staff

1. Involvement in the IMAM and challenges

Duration of service in IMAM Challenges

Recommendations 2. Most prevalent childhood diseases and causes of malnutrition. 3. Referral system and follow up of cases. 4. About mothers who come with healthy children. 5. Defaulters and reasons for defaulting and follow up of defaulters.

No. of children who default for more than 2 weeks Defaulting pattern

What they do about defaulting 6. Any other recommendations.

Caretakers of beneficiaries

1. General understanding of malnutrition 2. Outreach/treatment programs and duration in the program. 3. Information from staff about the treatment. 4. Knowledge of other children with similar conditions 5. Distance of clinic from village 6. Quality of service 7. Absence/defaulting and reasons for defaulting 8. Perception of IMAM and recommendations


.VII.10. ANNEX 10: A guide for conducting interviews in the community

Select the team: 8-12 people who will discuss their experiences, feelings, and preferences about a topic. A homogenous (similar socio economic and cultural background) team and who does not know each

other is desirable.

Facilitator and recorder. Natives are preferred.

Decide on timing and location: The duration should last 1-2 hours in a location that is comfortable and

allows privacy. Open places are not suitable since intruders can interfere with discussions.

Prepare discussion guide: A list of topics and issues to be discussed. Few topics are recommended to allow

for flexibility to discuss unanticipated but relevant issues. The guide provides the facilitator the framework to explore, probe and ask questions. Review existing questions.

Conduct the interview:

- Establish rapport: Facilitator to establish purpose and format of discussions, make everyone to

be at ease, explain that the discussion is informal, everyone is expected to participate and divergent views are welcome.

- Phrase questions carefully: Yes/no and why questions are not recommended. A good question could be like tell us what makes mothers not to seek treatment of their children in good time?

Open ended questions are recommended. Facilitator can narrow down broad discussions.

- Use probing techniques: Probe for full and clear answers by repeating the question, pause for

the answer, avoid showing that you know a lot, repeat the reply, ask when, what, where, which and how questions, use neutral comments.

- Control the discussion and aim at balancing participation: address questions to individuals who are reluctant to talk; give nonverbal cues; intervene politely, summarize the points and refocus

the discussion, thank the group and recognize their consent to continue.

- Minimize group pressure to control acceptance of answers without discussion through probing

for alternative views.

Record the discussion: The recorder should take up this task. Tape recording and written notes in language

of participants are suitable. Notes should be extensive and even reflect messages conveyed through non verbal cue. After the interview the team should summarize the information bearing its

impressions and implications. Report in both local language and English.

Analyze the results: Assemble the notes, summaries and other relevant data to analyze trends and

patterns. The following methods can be used:

- Read summaries all at one time to note trends or patterns s trongly held or frequently aired opinions.

- Read each transcript and highlight sections that correspond to interview guide questions and mark comments that could be used in the report.

- Analyze each question separately: Write a summary statement that describes the discussion for each question.

- The analyst should consider:

- words used and their weighted meaning

- Consider circumstances in which comments were made-context of previous discussion, tone and intensity

- Status of internal agreement/pressure. Were shifts in opinion caused by internal pressure.

- Precision of responses-give more weight to those based on personal experience than vague

impressions

- Big picture: Pin point major ideas and reflect on main findings.

- Purpose of the report: Objectives of the study and information needed to make decisions. Oral reports give main findings, descriptive reports summarize the discussion and analytical reports

provide trends, patterns or findings and include selected comment.

Documents

Nutrition Programme Coverage Assessment Report · nutrition) children was implemented in surrounding villages of health centres to better understand the extent of the coverage of