ENDLINE SURVEY FINAL REPORT International Rescue … · Moba, Nyemba, and Nyunzu. In November 2016,...

ENDLINE SURVEY FINAL REPORT International Rescue Committee, Democratic Republic of Congo

Prepared by ICF and the International Rescue Committee for WHO Rapid Access Expansion (RAcE) Program

MARCH 31, 2017

AUTHORS: Ramine Bahrambegi, Debra Prosnitz, Alison Wittcoff, Bronwyn Nichol, Ruwan Ratnayake

RAcEDRCEndlineSurveyReport ii

ACKNOWLEDGEMENTS

ICF and the International Rescue Committee would like to thank the Democratic Republic of Congo (DRC) Ministry of Public Health for its contributions to this work. We would also like to thank the Relais Communitaires (DRC’s community health workers), who work hard to provide services to caregivers and children in communities, and to the caregivers who give so much to ensure and improve the health of their children. This work was made possible by the World Health Organization through funding by the Canadian Government.

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TABLE OF CONTENTS

ABBREVIATIONS ............................................................................................................................................................. iv

EXECUTIVE SUMMARY .................................................................................................................................................. v

1 BACKGROUND .......................................................................................................................................................... 1 1.1 RAcE Program Goals and Objectives .............................................................................................................. 1 1.2 International Rescue Committee Project Background ................................................................................ 1 1.3 IRC Endline Survey Objectives .......................................................................................................................... 2

2 SURVEY METHODS ................................................................................................................................................... 3 2.1 Survey Implementation and Partnership ......................................................................................................... 3 2.2 Survey Design ........................................................................................................................................................ 3 2.3 Survey Questionnaire .......................................................................................................................................... 4 2.4 Selection and Training of Survey Staff .............................................................................................................. 5 2.5 Data Collection ..................................................................................................................................................... 5 2.6 Data Entry and Management .............................................................................................................................. 6 2.7 Data Analysis ......................................................................................................................................................... 6 2.8 Survey Indicators .................................................................................................................................................. 7 2.9 Survey Limitations ................................................................................................................................................ 7

3 FINDINGS ..................................................................................................................................................................... 8 3.1 Characteristics of Sick Children and Caregivers .......................................................................................... 8 3.2 Decision-Making .................................................................................................................................................... 9 3.3 Caregiver Knowledge and Perceptions of ReCos ...................................................................................... 10 3.4 Care-Seeking ........................................................................................................................................................ 11 3.5 Assessment ........................................................................................................................................................... 12 3.6 Treatment Coverage ......................................................................................................................................... 14 3.7 First Dose of Treatment and Counseling from ReCo ............................................................................... 15 3.8 Referral Adherence ............................................................................................................................................ 16 3.9 Sick Child Follow-Up ......................................................................................................................................... 17 3.10 Illness Management and Diagnostics by Sex ................................................................................................. 17

4 DISCUSSION .............................................................................................................................................................. 19

Annex A. Summary of Sampling Methodology ......................................................................................................... 21

Annex B. Baseline and Endline Samples ...................................................................................................................... 22

Annex C. Survey Questionnaire .................................................................................................................................. 25

Annex D. People Involved in Endline Survey Implementation .............................................................................. 26

Annex E. Survey Training Schedules ........................................................................................................................... 27

Annex F. Survey Fieldwork Schedule .......................................................................................................................... 30

Annex G. Routine Monitoring Treatment Data Trends ........................................................................................ 36

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ABBREVIATIONS

ACT artemisinin-based combination therapy

CCM community case management

DHS Demographic and Health Survey

DRC Democratic Republic of Congo

HMIS health management information system

iCCM integrated community case management

IRC International Rescue Committee

MoPH Ministry of Public Health

ORS oral rehydration solution

PPS probability proportional to size

RAcE Rapid Access Expansion

RDT rapid diagnostic test

ReCo Relais Communitaire (community health worker in DRC)

WHO World Health Organization

RAcEDRCEndlineSurveyReport v

EXECUTIVE SUMMARY

Since September 2013, the International Rescue Committee (IRC) has been implementing the Rapid Access Expansion (RAcE) program in 11 health zones of Tanganyika province of the Democratic Republic of Congo (DRC): Ankoro, Kabalo, Kalemie, Kansimba, Kiambi, Kongolo, Manono, Mbulula, Moba, Nyemba, and Nyunzu. In November 2016, IRC conducted the endline household survey, with technical assistance from ICF. We report endline data on sick child care-seeking, assessment, and treatment coverage as well as caregivers’ knowledge of childhood illnesses and their perceptions of services provided by Relais Communitaires (ReCos, or community health workers).

The baseline survey was conducted during project start-up when ReCos had not yet been fully recruited, trained, or deployed to provide integrated community case management (iCCM) services. Baseline results for most indicators, and specifically for those about knowledge and perceptions of ReCos and any services provided by ReCos, were close to zero. Security concerns throughout project implementation in certain zones necessitated evacuation of IRC staff and resulted in displacement of ReCos during periods of project implementation and during the endline survey. This resulted in an inability to sample a fully random and representative area of the RAcE project. Inability to sample sites affected by security issues likely biased the sample toward project areas receiving better or more consistent health services.

Results for caregiver knowledge and perceptions of ReCos are not reflective of areas excluded from the sample, particularly those areas where both ReCos and the communities they serve were displaced amidst insecurity due to inter-tribal violence. Of those caregivers surveyed, knowledge of ReCo presence in their communities was close to universal at 95 percent. Care-seeking from an appropriate provider was 89 percent at endline. As expected, as services were extended into communities through iCCM-trained ReCos, care-seeking shifted from health centers (from 50 percent at baseline to 6 percent at endline) to ReCos (from 1 percent at baseline to 84 percent at endline).

Results for case management by ReCos at endline show that caregivers are accessing care for their sick children from ReCos in their communities. Appropriate treatment by any provider was 57 percent at endline (p<0.001). Of those cases of illness among children aged 2–59 months who received appropriate treatment from any provider, 59 percent received appropriate treatment from a ReCo. Having slightly more than 50 percent of cases receive appropriate treatment from any provider suggests a strong need to improve both access to and quality of services. According to caregivers surveyed at endline, less than half (47 percent) of cases treated by a ReCo received the first dose of treatment in the presence of the ReCo. This may be explained by large stockouts during the month in which the endline survey was conducted and other disruptions in the commodity supply chain over the course of the project.

The endline survey results are not fully representative of the RAcE DRC project area, and results are skewed toward areas that likely had better and more continuous access to health services. Endline results are likely overestimates of achievement, measured from a sample of communities likely receiving better or more consistent health services than those excluded from the sample.

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Table 1. Key indicators at baseline and endline

Indicator Baseline Endline % point

change p-value

% (CI %) % (CI %)

Caregiver knowledge

1

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who are aware of the presence of the CCM-trained ReCo in their community

10.2 (5.1 - 19.4)

94.7 (88.0 - 97.7)

84.50 0.0000

2

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who know the role of the CCM-trained ReCo in their community

43.4 (29.8 - 58.0)

77.5 (67.0 - 85.4)

34.10 0.0006

3

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who know two or more signs of childhood illness that require immediate assessment by an appropriately trained provider

85.4 (79.7 - 89.7)

41.0 (33.0 - 49.4)

-44.42 0.0000

Caregiver perceptions of iCCM services

4

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who view CCM-trained ReCos as trusted health care providers

11.3 (5.2 - 22.8)

98.0 (94.5 - 99.0)

86.70 0.0000

5

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who believe CCM-trained ReCos provide quality services

9.4 (4.7 - 18.1)

96.0 (92.1 - 98.1)

86.60 0.0000

6

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who found the CCM-trained ReCo at first visit

85.7 (41.5 - 98.1)

95.2 (91.8 - 97.2)

9.50 0.2460

7

Percentage of caregivers of children age 2-59 months who have been sick in the two weeks preceding the survey who cite the CCM-trained ReCo as a convenient source of treatment

13.2 (6.1 - 26.3)

99.6 (98.5 - 99.9)

86.40 0.0000

Sick child care-seeking

8

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey for whom advice or treatment was sought from an appropriate provider

Overall 65.8

(56.4 - 74.1) 89.0

(83.9 - 92.7) 23.20 0.0001

Fever 55.2

(45.5 - 64.5) 83.5

(78.0 - 87.8) 28.28 0.0000

Diarrhea 51.8

(41.9 - 61.5) 79.4

(71.0 - 85.8) 26.63 0.0006

Cough with difficult or fast breathing 52.9

(42.8 - 62.7) 79.9

(72.3 - 85.8) 27.01 0.0002

9

Percentage of children age 2-59 months who were sick in two weeks preceding the survey taken to a CCM-trained ReCo as first source of care

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Overall 0.1

(0.0 - 0.8) 67.1

(60.4 - 73.2) 67.12 0.0000

Fever 0.0 69.5

(62.2 - 75.9) 69.47 0.0000

Diarrhea 0.6

(0.2 - 2.6) 63.7

(54.1 - 72.3) 63.06 0.0000

Cough with difficult or fast breathing 1.0

(0.2 - 4.5) 67.7

(61.4 - 73.5) 66.75 0.0000

Sick child assessment

10 Percentage of children age 2-59 months with fever in the two weeks preceding the survey who had finger or heel stick

22.0 (16.7 - 28.4)

75.8 (68.4 - 82.0)

53.88 0.0000

11

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had had finger or heel stick in the two weeks preceding the survey

88.9 (76.2 - 95.2)

89.9 (83.5 - 93.0)

1.04 0.8330

12

Percentage of children age 2-59 months with cough and difficult or rapid breathing in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing

28.3 (21.3 - 36.4)

59.1 (48.2 - 69.2)

30.83 0.0003

Sick child assessment by ReCo

13

Percentage of children age 2-59 months with fever in the two weeks preceding the survey who had a finger or heel stick by a ReCo among all fever cases managed by a ReCo

0.0 90.5

(86.7 - 93.3) 90.51 n/a

14

Percentage of children age 2-59 months for whom their caregiver received the results of the malaria diagnostic test of the children who had a finger or heel stick by a ReCo in the two weeks preceding the survey among all fever cases managed by a ReCo

0.0 82.3

(77.6 - 86.1) 82.28 n/a

15

Percentage of children age 2-59 months with cough and difficult or rapid breathing in the two weeks preceding the survey who had their respiratory rate counted to assess fast breathing by a ReCo among all cough and difficult or rapid breathing cases managed by a ReCo

0.0 73.6

(62.8 - 82.1) 73.55 0.0201

Sick child treatment

16

Percentage of children age 2-59 months who have been sick in two weeks preceding the survey who received appropriate treatment

Overall 10.1

(7.7 - 13.2) 57.1

(49.2 - 64.7) 41.40 0.0000

Malaria* (ACT within 24 hours) 16.7

(7.7 - 32.4) 67.5

(58.0 - 75.7) 50.78 0.0000

Diarrhea (ORS and zinc) 1.6

(0.6 - 4.4) 52.9

(42.7 - 62.9) 51.33 0.0000

Cough with difficult or fast breathing (amoxicillin)

17.9 (13.1 - 23.8)

53.0 (42.8 - 63.0)

35.19 0.0000

17

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey who received appropriate treatment from a CCM-trained ReCo

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Overall 0.1

(0.0 - 0.8) 59.0

(50.8 - 66.8) 58.9 0.0000

Malaria* (ACT within 24 hours) 0.0

(0.0 - 0.0) 80.4

(71.2 - 87.2) 80.4 0.0000


(0.0 - 0.0) 49.5

(40.1 - 59.0) 49.53 0.0000


0.3 (0.0 - 2.6)

51.4 (41.2 - 61.5)

51.10 0.0000

18

Percentage of children age 2-59 months who have been sick in the two weeks preceding the survey who received the first dose of treatment in the presence of a ReCo among those who received prescription medicines for a CCM condition in the two weeks preceding the survey

Overall 0.3

(0.0 - 2.1) 47.3

(39.4 - 55.3) 47.02 0.0000

Malaria* (ACT) 0.0

(0.0 - 0.0) 74.1

(64.2 - 82.1) 74.14 0.0000


(0.0 - 0.0) 48.5

(38.5 - 58.6) 48.47 0.0000


100.0 85.9

(78.6 - 91.0) -14.11 0.7022

19

Percentage of sick children age 2-59 months for whom their caregivers received counseling on how to provide the treatment(s) among those who received prescription medicines for a CCM condition in the two weeks preceding the survey

Overall 3.7

(0.5 - 23.9) 97.3

(94.8 - 98.6) -93.60 0.0000

Malaria* (ACT) 0.0

(0.0 - 0.0) 95.1

(90.7 - 97.4) 95.06 0.0000

Diarrhea (ORS and zinc) 0.0 98.8

(95.1 - 99.7) 98.80 n/a


100.0 98.2

(94.4 - 99.4) -1.8405 0.8796

Sick child referral and follow-up

20

Percentage of sick children age 2-59 who were referred in the two weeks preceding the survey whose caregiver adhered to referral advice

66.7 (13.3 - 96.3)

63.4 (51.3 - 74.0)

-3.2800 0.9105

21

Percentage of sick children age 2-59 months receiving treatment from a ReCo in the two weeks preceding the survey who received a follow-up visit from a ReCo

83.3 (37.5 - 97.7)

66.2 (57.6 - 73.7)

-17.2100 0.3576

CCM=community case management, ACT= artemisinin-based combination therapy, ORS=oral rehydration solution

* Cases of fever that had a blood test and determined positive for malaria.

RAcEDRCEndlineSurveyReport 1

1 BACKGROUND

1.1 RAcE Program Goals and Objectives

In 2013, the World Health Organization (WHO) launched the Rapid Access Expansion (RAcE) program in five sub-Saharan African countries—Democratic Republic of Congo (DRC), Malawi, Mozambique, Niger, and Nigeria. The goal of the program was to increase coverage of diagnostic, treatment, and referral services for malaria, pneumonia, and diarrhea to decrease overall mortality and the number of severe cases among children aged 2–59 months. The program would accomplish this goal through the following objectives:

Catalyze the scale-up of integrated community case management (iCCM) as an integral part of government-provided health services in sub-Saharan Africa.

Stimulate policy review and regulatory update in each country on disease case management.

Accelerate adaptation of supply management and surveillance systems to include services at the community level.

This effort came at a time when there was great momentum for iCCM at the country level and a high degree of interest among the global health community to understand how to best measure success and how to build country ownership and capacity to sustain iCCM interventions.

1.2 International Rescue Committee Project Background

The International Rescue Committee (IRC), in collaboration with the Congolese Ministry of Public Health (MoPH), is implementing the RAcE project in all 11 health zones of Tanganyika province (Ankoro, Kabalo, Kalemie, Kansimba, Kiambi, Kongolo, Manono, Mbulula, Moba, Nyemba, and Nyunzu) in DRC. IRC is leveraging its strong relationship with the MoPH, extensive experience working across the health sector, and previous iCCM implementation experience to expand coverage and add to the evidence base of iCCM in DRC through the RAcE project. RAcE DRC, which started in September 2013, aims to increase the coverage and quality of iCCM in order to reduce mortality in children aged 2–59 months in the targeted province. Over the course of four years, the project is aiming to reach a target population of about 1 million, including approximately 150,000 children under 5 years of age.

The project is implementing a three-pronged strategy that supports the development of a strong, responsive, community case management (CCM) network within the existing health system that can sustainably provide services. The first prong of the strategy focuses on expanding access to treatment for children in iCCM-eligible areas by establishing or revitalizing community care sites for treatment of malaria, diarrhea, and pneumonia; and by providing drugs and supplies. ICCM-eligible areas are defined by the MoPH as villages at least five kilometers from a health facility or villages that have a significant geographic barrier between them and the health facility.

The second prong aims to improve the quality of care provided by Relais Communitaires (ReCos, or community health workers) through training, including on-the-job training and supervision, and by strengthening the drug management system. In the DRC, ReCos provide iCCM in their communities to increase access to treatment for malaria, diarrhea, and pneumonia to children under five years of age.


The third prong of the strategy involves conducting operational research to further improve iCCM services and determine whether a simplified package of tools and adapted training materials can result in improved quality of care, reduced workload, and reduced implementation costs.

The DRC is among the countries with the highest rates of child mortality in the world, estimated at 118 deaths per 1,000 live births1. According to the 2014 DRC Demographic Health Survey (DHS), in Katanga Province, from which Tanganyika was decentralized in 2015, 15 percent of children under 5 years of age with malaria received timely treatment with artemisinin-based combination therapy (ACT), 39 percent of children under 5 years of age with diarrhea received treatment with oral rehydration solution (ORS) and 1 percent received treatment with zinc, and approximately 56 percent of children with suspected pneumonia received treatment with antibiotics.

Over the past three years, IRC has worked with the MoPH to respond to numerous emergencies and outbreaks throughout the country. In partnership with other donors and nongovernmental organizations, IRC supports health zones in Tanganyika that are often affected by insecurity due to tribal conflicts. Contingency systems were put in place to ensure that sufficient supplies of medications were available in health zones across the province so that ReCos could effectively function (provide iCCM services) throughout periods of insecurity, influxes of displaced populations, and other volatile situations. However, there were security concerns throughout project implementation in certain zones, which necessitated evacuation of IRC staff and resulted in displacement of ReCos, particularly during the endline survey. This resulted in an inability to sample a fully representative area of the RAcE project. Inability to sample sites affected by security issues likely biased the sample toward project areas receiving better or more consistent health services.

The baseline survey for RAcE DRC was implemented from September 22, 2013 to October 6, 2013 by IRC with technical support from ICF. The survey objectives were to: (1) assess the care-seeking behavior and knowledge of primary caregivers of children aged 2–59 months in the project area for malaria, diarrhea, and pneumonia; and (2) establish a baseline for the assessment of changes in treatment coverage for malaria, diarrhea, and pneumonia among children aged 2–59 months in the RAcE project area.

1.3 IRC Endline Survey Objectives

The objective of the RAcE endline household survey is to assess care-seeking behavior for sick children, iCCM coverage, and caregiver knowledge, attitudes, and practices related to malaria, diarrhea, and pneumonia in RAcE DRC project areas. However, because the endline survey sample is not representative of the entire project area, endline results are not directly comparable with the baseline survey results. We present endline data on care-seeking, assessment, and treatment coverage as well as caregivers’ knowledge of childhood illnesses and perceptions of ReCo services.

1 http://www.who.int/maternal_child_adolescent/epidemiology/profiles/neonatal_child/cod.pdf


2 SURVEY METHODS

2.1 Survey Implementation and Partnership

IRC conducted the RAcE endline survey with technical assistance from ICF. From June to November 2016, IRC worked with ICF to finalize the questionnaire. IRC conducted the training of enumerators, supervisors, and data entry operators; and provided oversight to the entire implementation process with remote support from ICF.

The survey protocol received ethical approval from ICF’s Institutional Review Board. IRC received a letter of approval from the DRC MoPH to proceed with the endline survey as a continuation of the baseline and part of a project evaluation. The MoPH and the Tanganyika Provincial Health Division were aware of the endline survey but elected not to participate so as not to bias the results by acting as self-evaluators.

2.2 Survey Design

This was a cross-sectional cluster-based household survey, targeting primary caregivers of children aged 2–59 months who had been sick with diarrhea, fever, or cough with difficult or fast breathing during the two weeks prior to survey administration. All primary caregivers of children aged 2–59 months who were reported to have experienced diarrhea, fever, or cough with difficult or fast breathing in the two weeks prior to interview were considered eligible for inclusion in the survey. ICF developed standardized sampling guidance for all RAcE projects, which was adapted for IRC.

In order to detect a 20 percent difference at 90 percent power with a two-tailed test and 95 percent confidence using cluster sampling, 263 cases were needed for each disease. ICF rounded up to 300 cases to ensure a consistent number of interviews per cluster and a slight increase in the precision of the coverage estimates.

The household survey used a 30x30 multi-stage cluster sampling methodology. At baseline, the target population comprised the entire RAcE project area, which consisted of iCCM-eligible areas more than five km from a health facility. At baseline, 30 clusters were selected from this sampling frame using probability proportional to size (PPS). Within each cluster, 10 interviews were conducted for each of the three illness modules—diarrhea, fever, and cough with difficult or fast breathing—for a total of 30 interviews per cluster, or 300 interviews per each illness across the project area.

The endline survey was designed to sample the same clusters that were visited for the baseline survey. However, the majority of clusters required replacement at various points in the survey implementation process, described as follows:

First, the baseline sampling frame contained nine clusters that were ultimately not targeted for RAcE project implementation due to decisions made after implementation of the baseline survey. Eleven2 clusters were removed from the sample and replaced during survey planning

2 Nine clusters were planned to be project areas at the time of baseline and ultimately were not included in the RAcE intervention area. Two clusters sampled at baseline were no longer in existence at endline: one was dissolved following the death of the chief, and the other was dissolved after being plagued by “witchcraft.”


stages with the closest nearby cluster in the project area with a similar population size. “Nearby” was defined as being within the catchment area of the same Aire de Sante (health center) of the cluster being replaced.

Second, insecurity and population displacements flared before survey implementation in Nyunzu health zone. The five clusters in Nyunzu health zone were consequently replaced. Because the entire health zone was determined a no-go zone, the “nearby” replacement methodology could not be used. Using the updated endline sampling frame,3 IRC used PPS to randomly select the five replacement clusters.

Third, while survey fieldwork was underway, further population displacement occurred, leading to large areas being deserted as people fled closer to nearby towns. Population displacement rendered five clusters–four in Kalemie health zone and one in Nyemba health zone–void of community members to survey. IRC selected five replacement clusters purposively, considering a number of issues in an effort to ensure that the replacement clusters were as similar as possible to the originally sampled clusters. These factors included proximity to the cluster that needed to be replaced, population size, distance to the health center, and distance to other major towns.

In summary, the 30 endline survey clusters included only 9 of the baseline clusters. The other 21 clusters were selected through a variety of replacement methods before and during survey fieldwork by ICF and IRC. Annex A provides a detailed summary of the sampling methodology. Annex B provides the baseline and endline samples.

The multiple replacement sampling methodologies used and the necessary exclusion of large parts of the RAcE project area render the endline survey neither random nor fully representative of the RAcE project. Inability to sample sites affected by security issues likely biased the sample toward project areas receiving better or more consistent health services. The endline survey results are likely biased in the positive direction, showing more positive results (e.g., higher coverage) than if the sample had been truly representative. Comparison of baseline and endline results does not represent true changes over time in the project area, nor does it accurately demonstrate project performance.

2.3 Survey Questionnaire

ICF developed a standard questionnaire for all RAcE grantees to use for their baseline surveys, which consisted of seven modules: caregiver and household background information; caregivers’ knowledge of iCCM activities in their community; caregivers’ knowledge of childhood illness danger signs; household decision-making; and a module for each iCCM focus illness: fever, diarrhea, and fast breathing. In addition to collecting information about caregiver knowledge, care-seeking, and treatment coverage, the questionnaire collected standard DHS data, specific to DRC, on household ownership of selected assets, materials used for housing construction, and types of water access and sanitation facilities, which ICF will analyze and use for the final evaluation.

3 Inaccessible clusters were removed from the updated endline sampling frame, leaving only clusters in Kalemie, Kansimba, Kongolo, Mbulula, Moba, and Nyemba health zones.


IRC and ICF worked together to tailor the questionnaire to reflect the DRC context. Two modules were added to the endline questionnaire: Module 2, DHS household assets, as noted above, and Module 4, household decision-making. Questions designed to capture information about caregivers’ malaria knowledge were added to Module 6, and care-seeking questions for the three illnesses (i.e., diarrhea, malaria, and pneumonia) were added to Modules 7–9. A question about whether the ReCo used counting beads to assess children for pneumonia was also added to Module 9. Modules and questions added at endline do not change the overall comparability of baseline and endline surveys. Data from the additional questions will be point estimates for endline only.

The questionnaire was professionally translated from English to French, and the French translation was reviewed by the IRC team. The French translation was then translated to Swahili, and back-translated to French by IRC. The Swahili questionnaires were used in the field and were piloted by the RAcE DRC health management information system (HMIS) manager and an IRC supervisor before training began. Translation issues found were addressed during supervisor training and were fixed before final printing of the questionnaire. The final questionnaire was 29 pages long.

Annex C contains the survey questionnaire.

2.4 Selection and Training of Survey Staff

IRC recruited and trained 12 interviewers and 6 supervisors for the endline survey. The endline supervisors were existing IRC RAcE supervisors, who supervised the survey in health zones outside their regular zones of coverage. The supervisors were trained from October 26 to 28, 2016, including an afternoon in a nearby village where they practiced village mapping, numbering, and household selection. They also attended the full interviewer training.

Twenty interviewers were invited for the training, and 12 were selected as finalists based on selection criteria that included a combination of attendance, end-of-day quizzes, and performance during field practice. Interviewer training was held from November 4 to 8, 2016 at IRC offices in Kalemie, using standardized training materials developed by ICF and tailored for the DRC survey by IRC. The training included one day of field practice in a village near Kalemie that was not part of the survey sample. Interviewers were trained by IRC staff, including the health monitoring and evaluation coordinator, the RAcE DRC HMIS manager, and RAcE survey supervisors.

Six temporary data entry staff were hired by IRC, using an existing pool of staff used for short-term data entry work. The RAcE DRC HMIS manager trained staff on the data entry program in CSPro after data collection was competed.

Annex D provides the list of people involved in the endline survey implementation. Annex E provides the survey training schedules.

2.5 Data Collection

Data collection was conducted by six data collection teams consisting of one supervisor and two interviewers, and it was implemented over a period of 15 days from November 11 to 26, 2016. After an eligible household was identified in each cluster, interviewers obtained verbal informed consent from the eligible caregiver before conducting the interview. Interviews were conducted with caregivers of children aged 2–59 months who were sick in the last two weeks with diarrhea, cough with difficult or


fast breathing, or fever. Enumerators used age calendars to help determine children’s ages. If the caregiver was not present in the household at the time of the initial visit, the team made up to three revisits to complete an interview. In most cases, interviews in a cluster were completed within a day, but in some cases, it took three days because community members were often working in the field. In 12 clusters, survey teams did not find adequate numbers of cases of illness, likely due to the small population size4 and also possibly due to low incidence rates of disease; diarrhea and cough with difficult or fast breathing were the most difficult to find. For these 12 clusters, the team continued to the nearest village and continued data collection until it conducted the required number of interviews. Travel time from cluster to cluster also varied; some were done in the same day and others within a few days. In addition, heavy rains caused muddy conditions for travel, which delayed the ability of the survey teams to visit villages and conduct the survey.

Following ICF’s quality control guidance, supervisors reviewed all questionnaires before leaving a cluster. Each supervisor also completed 10 quality control checklists (observation of interviews) in each cluster (5 per enumerator). Feedback was provided to enumerators before leaving each cluster.

Annex F contains the fieldwork schedule.

2.6 Data Entry and Management

Data entry took place over a two and a half week period from December 5 to 20, 2016. Data entry operators double-entered the survey data into a database using a CS Pro tool developed by ICF. After two data entry operators entered the data separately for a cluster, the data entry supervisor ran a quality check built into the CS Pro tool to compare the first and second entries for the cluster. If the check found any discrepancies, the data entry operators used the paper questionnaires to verify the correct values and then resolved the discrepancies using the CS Pro tool. The supervisor ran the quality check again, and if it resulted in no discrepancies, the data for the cluster were considered clean.

Names of participants were only collected for purposes of listing and were not used during any stage of data analysis. Data entered could not be traced back to the individuals. Access to data was restricted to authorized personnel only. After data for all clusters were entered and validated, IRC stripped the final dataset of any identifying information and shared it with ICF for analysis.

2.7 Data Analysis

ICF analyzed the survey data using Stata v14 and Microsoft Excel. The ICF analyst imported the endline household CS Pro data files into Stata and merged them into one file. The baseline data file was appended to the endline data file, and the merged file was checked, cleaned, and coded for the analysis.

The ICF analyst calculated point estimate and 95 percent confidence intervals accounting for cluster effects. To test for statistically significant changes between indicators at baseline and endline a Pearson’s chi-squared test was used for binary and categorical variables and regression for continuous variables.

4 Four clusters had a population of 50–100 people; 4 clusters had populations of 101–200 people; 2 clusters had populations of 200–500 people; 1 cluster had a population of approximately 700 people; and 1 cluster had a population of approximately 1,800 people.


Indicators with p-values less than 0.05 show a statistically significant change between baseline and endline.

Endline data are displayed disaggregated by child’s sex and illness. For the comparison of indicators between baseline and endline, we only disaggregated data by sex if we found the differences between males and females to be statistically significant.

2.8 Survey Indicators

The survey collected 18 key indicators related to caregiver knowledge of ReCos and child illnesses; caregiver perceptions of ReCos; and sick child care-seeking, assessment, treatment, referral adherence, and follow-up. The survey also collected information on household and caregiver characteristics and household decision-making.

2.9 Survey Limitations

In total, 21 of the endline survey clusters were selected through a variety of replacement methods prior to and during survey fieldwork by ICF and IRC. Security concerns throughout project implementation in certain zones necessitated evacuation of IRC staff and resulted in displacement of ReCos, especially during the period of time when the endline survey was implemented. Some project area clusters consequently did not have a chance to be included in the endline survey. Therefore, the endline survey sample and results are not representative of the full RAcE project area. Excluded sites are likely to have experienced disruption in health services or fewer or poorer quality services for the same reasons they were excluded from sample selection. It follows that that the areas included in the survey were likely receiving better or more consistent health services, biasing the sample for more positive results.

In addition, there are known potential biases and limitations with the indicators that assess caregiver recall of malaria diagnostic testing and coverage of appropriate treatment for children with fever and with cough with difficult or fast breathing. The potential biases and limitations of these indicators are further detailed in the findings section.


3 FINDINGS

This report presents endline survey findings. At baseline, the project area was defined as areas in which ReCos were planned to be deployed during the project period. No iCCM services were being provided at the time of the baseline survey. The project intervention areas were refined after implementation of the baseline survey, and some clusters sampled at baseline were ultimately not part of the project area. Thus, the endline survey results presented in this report are not fully representative of the RAcE DRC project area. The endline findings and results are also skewed toward areas that likely had better and more continuous access to health services.

3.1 Characteristics of Sick Children and Caregivers

Table 2. Characteristics of sick children included in survey

Characteristic Baseline % (CI%)

Endline % (CI%)

Sex of sick children included in survey

Male, % 49.1

(44.5-53.8) 53.4

(49.6-57.2)

Female, % 50.9

(46.2-55.5) 46.6

(42.8-50.4) Age (months) of sick children included in survey

<12, % 21.8

(18.4-25.7) 22.5

(19.2-26.2)

12-23, % 20.9

(17.2-25.1) 25.8

(22.7-29.2)

24-35, % 23.4

(19.6-27.7) 22.9

(19.7-26.4)

36-47, % 20.5

(17.3-24.1) 17.8

(14.5-21.6)

48-59, % 13.5

(10.9-16.4) 11.1

(8.3-14.6) Two-week history of illness of children included in surveyHad fever, % 61.2 66.7 Had diarrhea, % 58.8 55.2 Had cough with fast breathing, % 55.4 53.1 Average number of illnesses, n 1.8 1.8 Cases of illness included in survey Fever, n 328 393 Diarrhea, n 315 325 Cough with fast breathing, n 297 313 Total number of sick child cases included in survey

940 1,031


Table 3. Characteristics of caregivers

Characteristic Baseline% (CI%)

Endline% (CI%)

Age (Years) 15-24 33.2

(29.3 - 37.3) 35.7

(30.9 - 40.8) 25-34 44.1

(40.1 - 48.2) 37.7

(33.7 - 41.9) 35-44 18.0

(15.0 - 21.4) 21.3

(17.4 - 25.9) 45-60 4.7

(2.9 - 7.7) 5.3

(3.4 - 8.2) Education None 65.8

(58.6 - 72.3) 51.2

(43.6 - 58.7) Primary 17.7

(13.8 - 22.4) 21.3

(17.5 - 25.7) Secondary 10.4

(7.3 - 14.8) 13.7

(10.3 - 18.0) Higher 6.1

(3.6 - 10.3) 13.8

(9.9 - 19.0) Marital status* Currently married

n/a 94.7

(92.0 - 96.5) Not married but living with a partner

n/a 1.0

(0.4 - 2.5) Not in union

n/a 4.3

(2.6 - 6.9) Partner living with caregiver (among those in union)*

Yes n/a

99.1 (97.8 - 99.6)

Total number of caregivers 508 586 n/a=not available * 534 caregivers in a union at endline

3.2 Decision-Making

Decision-making about both income and general care-seeking was made predominantly by the caregiver’s spouse or partner. Overall decision-making was not captured in the baseline survey. At endline, as shown in Table 4, approximately two-thirds of all caregivers reported that decisions regarding household income and decisions regarding care-seeking were made by their husband or partner. Only approximately 8 percent of caregivers made these decisions jointly with their partner. However, as shown in Table 5, among caregivers who sought care for their child aged 2–59 months who had been sick in the two weeks before the survey, joint decision-making to seek that care was high (69 percent).


Table 4. Usual decision-maker in household about income and care-seeking

Decision-maker Income decisions Care-seeking decisions

Baseline Endline Baseline Endline% (CI%) % (CI%) % (CI%) % (CI%)

Caregiver n/a 16.0

(12.1 - 21.0) n/a

14.8 (11.8 - 18.4)

Caregiver’s husband or partner

n/a 74.3

(69.2 - 78.9) n/a

76.5 (71.6 - 80.8)

Caregiver and partner jointly

n/a 8.2

(5.6 - 11.8) n/a

7.5 (5.0 - 11.0)

Other n/a 1.4

(0.6 - 3.2) n/a 1.3 (0.6-2.8)

Total number of caregivers

n/a 561 n/a 561

n/a=not available

Table 5. Joint decision-making to seek care for child by illness

Decided to seek care jointly with partner

Baseline % (CI%)

Endline % (CI%)

Baseline N

Endline N

p-value

Overall 90.8

(83.6 - 95.0) 68.6

(60.8 - 75.5) 761 939 0.0004

Fever 90.0

(81.8 - 94.8) 71.6

(63.6 - 78.5) 271 363 0.0040

Diarrhea 91.6

(85.0 - 95.4) 66.6

(57.1 - 74.9) 250 290 0.0001

Cough with difficult or fast breathing

90.8 (82.3 - 95.5)

66.8 (58.0 - 74.5)

240 286 0.0008

3.3 Caregiver Knowledge and Perceptions of ReCos

Surprisingly, the percentage of caregivers who know at least two signs of child illness decreased significantly over the course of the project. Fever was the sign of illness most recognized by caregivers (40 percent at baseline, 43 percent at endline). The percentage of caregivers who know that a ReCo works in their community was nearly universal at endline (95 percent). Most caregivers (76 percent) were able to list at least two curative services provided by the ReCo. Of the many activities that ReCos implement in communities, caregivers most noted ReCo activities as treatment for malaria (70 percent), treatment for pneumonia (50 percent), and provision of ORS for diarrhea (57 percent). The high percentages of caregiver knowledge and perception in relation to ReCos at endline are not reflective of areas excluded from the sample, particularly those areas where both ReCos and the communities they serve were displaced.

Table 6. Caregiver knowledge of childhood illnesses

Caregiver knowledge Baseline Endline

p-value % (CI %) % (CI %)

Knows 2+ child illness signs 85.4

(79.7 - 89.7) 41.0

(33.0 - 49.4) 0.0000

Knows cause of malaria n/a 42.0

(32.7 - 51.9)

Knows fever is a sign of malaria n/a 62.5

(56.4 - 68.1)

Knows malaria treatment n/a 53.5

(4.5 - 62.4)

Total number of caregivers 513 586

n/a=not available


Table 7. Caregiver knowledge of ReCo

Caregiver knowledge Baseline Endline


Knows CCM-trained ReCo works in community 10.4

(5.0 - 20.2) 94.7

(89.2 - 97.5) 0.0000

Total number of caregivers 511 586

Knows location of ReCo* 13.2

(6.1 - 26.3) 99.5

(98.3 - 99.8) 0.0000

Knows 2+ ReCo curative services* 43.4

(29.9 - 58.0) 77.5

(67.0 - 85.4) 0.0006

Total number of caregivers 53 555 * Only asked of caregivers who stated that there was a CCM-trained ReCo in their community

Table 8. Caregiver perceptions of CCM-trained ReCo

Caregiver perceptions Baseline Endline


View CCM-trained ReCos as trusted health care providers*

11.3 (5.2 - 22.8)

97.7 (94.5 - 99.0)

0.0000

Believe CCM-trained ReCos provide quality services* 9.4

(4.5 - 18.1) 96.0

(92.1 - 98.1) 0.0000

Found the CCM-trained ReCo at first visit (for all instances of care-seeking included in survey)**

85.7 (41.5 - 98.1)

95.2 (91.8 - 97.2)

0.2460

Cite the CCM-trained ReCo as a convenient source of treatment*

13.2 (6.1 - 26.3)

99.6 (98.5 - 99.9)

0.0000

Total number of caregivers 55 555 *Among caregivers who are aware of the iCCM-trained ReCo in their community ** Denominator 7 at baseline; 848 at endline; only those who sought care from a ReCo for their child for at least one case of illness

3.4 Care-Seeking

The percentage of children age 2-59 months who have been sick in the two weeks preceding the survey for whom advice or treatment was sought from an appropriate provider was 89 percent at endline. ReCos were not providing iCCM services at the time of the baseline survey. As expected with the deployment of ReCos to communities, the source of care-seeking shifted over the course of the project. Of those who sought care at endline, only 6 percent sought care from a health center, and 84 percent sought care from ReCos.

A similar shift took place in the first source of care. For the cases of illness among children aged 2-59 months who were sick in the two weeks preceding the survey, 74 percent were taken to a ReCo as a first source of overall care, and 2 percent went to a health center as the first source of care. Pharmacies (11 percent) and traditional practitioners (3 percent) were the other most frequent sources of care-seeking for cases of illness among children aged 2-59 months in the two weeks preceding the survey.

Among those who did not seek care at all at endline (N=92 cases of illness), 32 percent did not seek care for other (unspecified) reasons, and 16 percent did not seek care because the condition passed. Most of those who sought care but did not seek care from a ReCo did not cite a reason.


Table 9. Source of care by illness

Illness

Sought care from appropriate provider* p-

value

ReCo was first source of care p-

value Baseline

N Endline

N Baseline Endline Baseline Endline% (CI %) % (CI %) % (CI %) % (CI %)

Overall 65.8

(56.4 - 74.1) 89.0

(83.9 - 92.7)0.0001

0.1 (0.0 - 0.8)

67.1 (60.4 - 73.2)

0.0000 940 1031

Fever 55.2

(45.5 - 64.5) 83.5

(78.0 - 87.8) 0.00000.0

69.5 (62.2 - 75.9)

0.0000 328 393

Diarrhea 51.8

(41.9 - 61.5) 79.4

(71.0 - 85.8)0.0006

0.6 (0.2 - 2.6)

63.7 (54.1 - 72.3)

0.0000 315 325


52.9 (42.8 - 62.7)

79.9 (72.3 - 85.8)

0.00021.0

(0.2 - 4.5) 67.7

(61.4 - 73.5)0.0000 297 313

* Appropriate providers include hospital, health center, health post, dispensary, ReCo, or health clinic.

Table 10. Care-seeking from ReCo

Illness

ReCo was first source of care among those who sought any care p-

value Baseline N Endline N

Baseline Endline% (CI %) % (CI %)

Overall 0.1

(0.0 - 1.0) 73.7

(67.2 - 79.3) 0.0000 761 939

Fever 0.0 75.2

(67.9 - 81.3) 0.0114 271 363

Diarrhea 0.8

(0.2 - 3.3) 71.4

(61.5 - 79.6) 0.0000 250 290


1.3 (0.3 - 5.6)

74.1 (68.3 - 79.2)

0.0002 240 286

Table 11. Cases of illness for which no care was sought

Illness Did not seek care

p-value

Sought care but not from ReCo

p-value Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

Overall 19.0

(12.0 - 28.8) 8.9

(6.2 - 12.7) 0.0028

99.2 (97.3 - 99.8)

16.1 (11.7 - 21.8)

0.0000

Fever 17.4

(10.7 - 27.0) 7.6

(4.8 - 11.9) 0.0025

100.0 (0.0 - 0.0)

14.3 (10.2 - 19.8)

0.0000

Diarrhea 20.6

(12.9 - 31.3) 10.8

(6.5 - 17.3) 0.0319

100.0 (0.0 - 0.0)

14.3 (10.2 - 19.8)

0.0000


19.2 (11.6 - 30.1)

8.6 (5.5 - 13.3)

0.0186 98.8

(94.4 - 99.7) 17.8

(12.9 - 24.1) 0.0000

Total number of sick child cases

940 1,031 761 939

3.5 Assessment

Caregiver recall of malaria diagnostic testing is poor, which could affect the malaria diagnosis and appropriate treatment indicators calculated. According to the Indicator Guide: Monitoring and Evaluating Integrated Community Case Management, “Studies have found poor sensitivity and specificity of maternal recall for malaria diagnostic tests (finger/heel stick). Consequently, the current recommendation is that household surveys track treatment coverage of fever and, where possible,


supplement with data from service delivery assessment to better understand the proportion of suspected malaria cases that receive appropriate diagnosis and treatment.”5

At baseline, virtually no cases of illness were assessed by ReCos in communities, because iCCM had not yet been rolled out in the project areas. At endline, for cases of fever among children aged 2–59 months in the two weeks preceding the survey, 76 percent had their blood drawn and tested for malaria by any provider using a rapid diagnostic test (RDT) or microscopy. Of the cases of fever among children aged 2–59 months with fever in the two weeks prior to the survey managed by a ReCo, 91 percent had an RDT administered. Of those, 82 percent of caregivers reported receiving the result, 78 percent of which were reported to have been positive for malaria.

Table 12. Malaria assessment among children with fever

Fever assessment Cases managed by ReCo

p-value All cases

p-value Baseline Endline Baseline Endline % (CI %) % (CI %) % (CI %) % (CI %)

Child had blood drawn* 0.0 90.5

(86.7 - 93.3) n/a

22.0 (16.7 - 28.4)

75.8 (68.4 - 82.0)

0.0000

Caregiver received result of blood test

0.0 82.3

(77.6 - 86.1) n/a

88.9 (76.2 - 95.2)

89.9 (83.5 - 94.0)

0.8330

Blood test positive for malaria

0.0 78.2

(73.2 - 82.4) n/a

75.0 (62.4 - 84.4)

85.6 (78.2 - 90.8)

0.0966

Received ACT after positive blood test, among those who had a positive blood test

0.0 90.7

(86.3 - 93.8) n/a

7.3 (4.6 - 11.4)

57.8 (47.7 - 67.3)

0.0000

Total number of fever cases

0 316 328 393

* Assumed to be an RDT by ReCo and either RDT or microscopy by health facility provider

ReCos use both a timer (or watch) and counting beads to measure respiratory rate. The percentage of cases of cough with difficult or fast breathing among children aged 2–59 months that had their respiratory rate counted using a watch or timer by any provider was 59 percent at endline. Among cases managed by a ReCo at endline, 73 percent had their respiratory rate counted with a watch or timer, and 66 percent had their respiratory rate counted with counting beads. These results suggest that not all ReCos are using both timers and counting beads for respiratory rate assessment.6

The percentage of cases of cough with difficult or fast breathing that had their respiratory rate assessed is low. The low proportion of cases assessed is particularly notable when considering that these results represent communities that likely had better and more consistent access to health services than the project area population as a whole.

5 Maternal and Child Health Integrated Program. (2013). Indicator Guide: Monitoring and Evaluating Integrated Community Case Management. 6 These are results of un-validated survey questions. Caregivers recall regarding details of illness assessment may not be strong, and their responses may be biased by the flow or survey questions. Caregivers were first asked if their child’s breathing was assessed using a watch or timer, and if yes, by whom. If caregivers sought care from a ReCo, they were also asked whether the ReCo used counting beads to count the respiratory rate.


Table 13. Respiratory rate assessment

Respiratory rate assessment

Cases managed by ReCop-value

All cases p-value Baseline Endline Baseline Endline

% (CI %) % (CI %) % (CI %) % (CI %) Respiratory rate assessed with watch/timer

0.0 (0.0 - 0.0)

72.8 (61.8 - 81.6)

0.0225 28.3

(21.3 - 36.4) 59.1

(48.2 - 69.2) 0.0003

Respiratory rate assessed with counting beads

0.0 (0.0 - 0.0)

66.0 (54.5 - 75.8)

0.0472

Total number of cough with difficult or fast breathing cases

3 242 297 313

3.6 Treatment Coverage

Overall, appropriate treatment coverage was quite low at endline, with only 57 percent of cases receiving appropriate treatment from any provider. At endline, of those cases of illness among children aged 2–59 months who received appropriate treatment from any provider in the two weeks preceding the survey, 59 percent received appropriate treatment from a ReCo. At endline, a total of 719 cases of illness sought care from a ReCo and received appropriate treatment. The percentage of cases treated appropriately by illness are provided in Tables 14–16.

Treatment of cough with difficult or fast breathing must be interpreted carefully. Pneumonia treatment, for which this indicator is a proxy, is globally recognized to have validity issues7 because diagnosis of presumptive pneumonia is often inaccurate in comparison with clinical diagnosis of pneumonia at health facilities. Therefore, the number of cases of cough with difficult or fast breathing is likely an overestimate of actual clinical pneumonia cases, and the percentage of these treated with amoxicillin can, and should, reasonably not be 100 percent.

Table 14. Treatment coverage

Illness (treatment) Received appropriate treatment

p-value Baseline N Endline N Baseline Endline% (CI %) % (CI %)

Overall* 10.1

(7.6 - 13.2) 57.1

(49.2 - 64.7) 0.0000 666 893

Confirmed malaria (ACT)** 44.4

(31.4 - 58.4) 89.0

(81.4 - 93.8) 0.0000 54 255

Confirmed malaria (ACT within 24 hours)**

16.7 (7.7 - 32.4)

67.5 (58.0 - 75.7)

0.0000 54 255


(0.6 - 4.4) 52.9

(42.7 - 62.9) 0.0000 315 325


17.9 (13.1 -23.8)

53.0 (42.8 – 63.0)

0.0000 297 313

* Includes confirmed treatments for malaria (ACT within 24 hours), diarrhea (ORS and zinc), and cough with difficult or fast breathing (amoxicillin)

** Among fever cases with a positive RDT result

7 Campbell H, el Arifeen S, Hazir T, O'Kelly J, Bryce J, Rudan I, et al. (2013). Measuring coverage in MNCH: Challenges in monitoring the proportion of young children with pneumonia who receive antibiotic treatment. PLoS Med 10(5): e1001421. doi:10.1371/journal.pmed.1001421


Table 15. Appropriate treatment by ReCo

Illness (treatment)

Received appropriate treatment from ReCo


Overall* 0.2

(0.0 - 1.2) 59.0

(50.8 - 66.8) 0.0000 666 893


(0.0 - 0.0) 87.5

(79.0 - 92.8) 0.0000 54 255


0.0 (0.0 - 0.0)

80.4 (71.2 - 87.2)

0.0000 54 255


(0.0 - 0.0) 49.5

(40.1 - 59.0) 0.0000 315 325


0.3 (0.0 - 2.6)

51.4 (41.2-61.5)

0.0000 297 313



Table 16. Sought care from a ReCo and received appropriate treatment by ReCo

Illness (treatment)

Received appropriate treatment from ReCo among those who

sought care from ReCo p-value Baseline N Endline N Baseline Endline% (CI %) % (CI %)

Overall* 16.7

(4.1 - 48.7) 72.3

(64.8 - 78.7) 0.0004 6 719


0.0 68.6

(59.6 - 76.4) n/a 0 242


(57.0 - 74.9) 0.0206 3 242


33.3 (10.3 - 68.5)

67.7 (54.6 - 78.4)

0.0799 3 235

n/a=not available



3.7 First Dose of Treatment and Counseling from ReCo

According to caregivers surveyed at endline, less than half (47 percent) of cases treated by a ReCo received the first dose of the treatment in the presence of the ReCo. This ranged from 86 percent of cases of cough with difficult or fast breathing receiving the first dose of amoxicillin in the presence of the ReCo, to 49 percent of cases of diarrhea receiving the first dose of both ORS and zinc in the presence of the ReCo. These results may be explained by major stockout issues experienced in the month before and during which the endline survey was conducted. In October 2016, only 11 percent of the ReCos had all iCCM commodities in stock. In November 2016, only 44 percent of the ReCos had all iCCM commodities in stock.

Counseling by ReCos on how to provide treatment was high overall (97 percent) at endline and for each illness treatment. Counseling on provision of ACT for malaria was the lowest at 95 percent, and counseling on provision of zinc for diarrhea was the highest at 99 percent.


Table 17. First dose of treatment from ReCo

Illness (treatment) First dose received in presence of ReCo


Overall* 0.3

(0.0 - 2.1) 47.3

(39.4 - 55.3) 0.0000 761 939


(0.0 - 0.0) 74.1

(64.2 - 82.1) 0.0000 49 263

Diarrhea (ORS) 0.0

(0.0 - 0.0) 70.8

(64.2 - 76.6) n/a 0 209

Diarrhea (zinc) 0.0

(0.0 - 0.0) 79.0

(67.2 - 87.4) n/a 0 181


(0.0 - 0.0) 48.5

(38.5 - 58.6) n/a 0 229


100.0 85.9

(78.6 - 91.0) 0.7022 2 163

n/a=not available

* Includes confirmed treatments for malaria (ACT), diarrhea (ORS and zinc), and cough with difficult or fast breathing (amoxicillin)


Table 18. Counseling on treatment administration by ReCo

Illness (treatment)

Counseled on treatment administration


Overall* 3.7

(0.5 - 23.9) 97.3

(94.8 - 98.6) 0.0000 52 587

Confirmed malaria (ACT)** 0.0 95.1

(90.7 - 97.4) 0.0000 49 263

Diarrhea (ORS) 0.0 98.1

(95.0 - 99.3) n/a 0 209

Diarrhea (zinc) 0.0 98.9

(95.6 - 99.7) n/a 0 181


(95.1 - 99.7) n/a 0 161


100.0 98.2

(94.4 - 99.4) 0.8796 2 163

n/a=not available

* Includes confirmed treatments for malaria (ACT), diarrhea (ORS and zinc), and cough with difficult or fast breathing (amoxicillin)


3.8 Referral Adherence

At endline, ReCo referred 13 percent of cases of illness they managed. Caregiver’s reported adherence to a referral provided by a ReCo was 63 percent. Referral adherence by illness is shown in Table 19. Of those who reported that they did not comply with the referral provided, the majority (44 percent) did not comply because they did not have money, 24 percent did not comply because the facility was too far, and 12 percent did not comply due to lack of transport.


Table 19. Adherence to ReCo referral

Condition Baseline Endline

p-value Baseline N Endline N % (CI %) % (CI %)

Overall 66.7

(13.3 - 96.3) 63.4

(51.3 - 74.0) 0.0000 3 115

Fever 0.0 63.6

(45.3 - 78.7) n/a 0 33

Diarrhea 100.0 75.0

(56.7 - 87.3) 0.4240 2 32


0.0 (0.0 - 0.0)

55.3 (32.0 - 76.6)

0.3343 1 47

n/a=not available

3.9 Sick Child Follow-Up

According to the iCCM protocol used in RAcE DRC, ReCos are trained to counsel mothers to bring their child back to the ReCo for follow-up within three days. At endline, caregivers returned to the ReCo for follow-up for 66 percent of cases of all illnesses. Of those that followed up, nearly all followed up within the advised 3-day period: 60 percent followed up within 1 day, 23 percent followed up within 2 days, and 13 percent followed up within 3 days.

Table 20. Caregiver follow-up with ReCo

Condition Baseline Endline

p-value Baseline N Endline N % (CI %) % (CI %)

Overall 83.3

(37.5 - 97.7) 66.1

(57.6 - 73.7) 0.3576 6 794

Fever 0.0 66.6

(61.1 - 71.6) n/a 0 311

Diarrhea 100.0 67.8

(56.8 - 77.1) 0.2969 3 242


66.7 (9.6 - 97.4)

63.8 (54.0 - 72.7)

0.9303 3 235

n/a=not available

3.10 Illness Management and Diagnostics by Sex

There were no notable differences in appropriate assessment or treatment of iCCM illnesses between boys and girls.

Table 21. Fever management and treatment administered

Sex Confirmed malaria treatment Number of children

with positive RDT Any anti-malarial ACT ACT within 24 hours

Overall 92.2

(85.3 - 96.0) 89.0

(81.4 - 93.8) 67.5

(58.0 - 75.7) 255

Male 89.6

(79.5 - 95.1) 86.7

(75.8 - 93.1) 67.4

(55.4 - 77.5) 135

Female 95.0

(87.9 - 98.0) 91.7

(83.5 - 96.0) 67.5

(55.5 - 77.6) 120

Table 22. Fever diagnostics

Sex Had blood taken from finger or heel

Among those who had blood taken Number of children with fever Were given results Test result positive

Overall 75.8 (68.4 - 82.0)

89.9 (83.5 - 94.0)

85.6 (78.2 - 90.8)

393

Male 74.8 (66.1 - 81.9)

90.0 (80.4 - 95.2)

84.4 (74.5 - 90.9)

214

Female 77.1 (67.6 - 84.4)

89.9 (83.6 - 93.9)

87.0 (79.9 - 91.8)

179


Table 23. Diarrhea management by provider and treatment administered

Sex Sought any advice or treatment

Sought treatment from an appropriate

provider*

Sought treatment

from a ReCo

Sought treatment

from a ReCo as first choice

Treatment

Treated with ORS AND Zinc

Number of

children with

diarrhea

ORS Home-made fluid

Zinc

Overall 89.2

(82.7 - 93.5) 79.4

(71.0 - 85.8) 74.5

(65.4 - 81.8) 63.7

(54.1 - 75.8) 71.7

(63.1 - 79.0) 0

58.8 (48.6 - 68.3)

53.6 (43.5 - 63.5)

325

Male 89.4

(81.4 - 94.3) 79.4

(69.3 - 86.9) 73.9

(62.9 - 82.5) 61.3

(49.1 - 72.3) 71.1

(61.1 - 79.4) 0

57.2 (45.4 - 68.3)

51.1 (38.9 - 63.2)

181

Female 89.0

(79.4 - 94.4) 80.6

(69.1 - 88.5) 75.2

(65.2 - 83.1) 66.7

(56.1 - 75.8) 72.4

(61.1 - 81.5) 0

60.7 (47.0 - 72.9)

56.9 (44.1 - 68.8)

144

* Refers to those who sought care from a hospital, health center, health post, dispensary, ReCo, or health clinic

Table 24. Cough with difficult or fast breathing management by provider and treatment

Sex Sought any advice or treatment

Sought treatment from an appropriate

provider*

Sought treatment from

a ReCo

Sought treatment from a ReCo as first

choice

Assessed for rapid breathing

Treatment Number of children

with cough with difficult

or fast breathing

Any antibiotic Amoxicillin

Overall 91.4

(86.7 - 94.5) 79.9

(72.3 - 85.8) 75.1

(68.1 - 80.9) 67.7

(61.4 - 73.5) 59.1

(48.2 - 69.2) 56.6

(46.6 - 66.0) 53.0

(42.8 - 63.0) 313

Male 90.8

(83.5 - 95.1) 80.4

(71.6 - 87.0) 76.7

(68.6 - 83.2) 66.9

(58.4 - 74.4) 60.7

(49.1 - 71.3) 54.0

(44.1 - 63.6) 52.2

(42.1 - 62.1) 157

Female 92.0

(85.1 - 95.9) 79.3

(67.9 - 87.4) 73.3

(63.3 - 81.4) 68.6

(59.0 - 76.8) 57.3

(44.8 - 69.0) 59.3

(47.2 - 70.5) 54.0

(41.7 - 65.8) 156

* Refers to those who sought care from a hospital, health center, health post, dispensary, ReCo, or health clinic


4 DISCUSSION

With the roll-out of iCCM services in Tanganyika starting in 2013 through the RAcE project, the presence of ReCos in communities has increased, as has overall care-seeking and treatment for children aged 2–59 months. The baseline survey was conducted during project start-up when ReCos had not yet been deployed to provide iCCM services in the project area. As such, baseline results for indicators relating to caregiver knowledge of ReCos and any case management provided by ReCos are essentially zero. The necessary exclusion of many project areas from the endline sample, and non-random selection of some replacement clusters, renders the endline survey sample unrepresentative of the full RAcE DRC project area. The endline sample and endline results reflect communities that likely had better and more continuous access to care. Baseline and endline results are thus not directly comparable.

Endline results for caregiver knowledge and perceptions of ReCos are not reflective of areas excluded from the sample, particularly those areas where both ReCos and the communities they serve were displaced amidst insecurity due to inter-tribal violence. Of those caregivers surveyed, knowledge of the presence of ReCos in their communities was close to universal at 95 percent. Of those caregivers, 70 percent were aware that ReCos provide treatment for malaria, 50 percent were aware that ReCos provide treatment for pneumonia, and 57 percent aware that ReCos provide ORS for diarrhea.

Care-seeking from an appropriate provider was high at endline, with 89 percent of cases of illness in the two weeks preceding the survey among children aged 2–59 months being taken to an appropriate provider. This high percentage of care-seeking for child illness at endline may be due to the presence of ReCos in the communities and the consequent (presumed) increase in access to care for those communities. It follows that a shift took place in the source of care-seeking, and first source of care in particular. As expected, when services were extended into communities through iCCM-trained ReCos, care-seeking shifted from health centers to ReCos as the location where most sought care. At endline, among cases of illness in children aged 2–59 months who sought care from an appropriate provider in the two weeks preceding the survey, only 6 percent sought care from a health center, and 84 percent sought care from a ReCo. A similar shift took place in the first source of care.

Results for case management by ReCos at endline show that caregivers are accessing care for their sick children from ReCos in their communities. However, the results are likely overestimates of project achievements. Of the cases of fever among children aged 2–59 months with fever in the two weeks preceding the survey managed by a ReCo, 91 percent had an RDT administered. Among cases of cough with difficult or fast breathing managed by a ReCo, 73 percent had their respiratory rate counted with a watch or timer, and 66 percent had their respiratory rate counted with counting beads.

Overall, appropriate treatment coverage was quite low at endline, with only 57 percent of cases receiving appropriate treatment from any provider. Of those cases of illness among children aged 2-59 months who received appropriate treatment from any provider at endline, 59 percent received appropriate treatment from a ReCo. At endline, a total of 719 cases of illness sought care from a ReCo, 72 percent of which received appropriate treatment. According to caregivers surveyed at endline, less than half (47 percent) of cases treated by a ReCo received the first dose of the treatment in the presence of the ReCo. This may be explained by widespread stockouts during the months before and during endline survey implementation. In October 2016, only 11 percent of ReCos had all iCCM drugs


in stock.8 In November 2016, only 44 percent had all iCCM drugs in stock.9 Having slightly more than 50 percent of cases receive appropriate treatment (from any provider) suggests a strong need to improve the quality of services and access to services, and to strengthen the supply chain to minimize stockouts for ReCos.

Although few referrals were made by ReCos, adherence was reported to be relatively high (63 percent). Reasons for non-adherence to the referral (lack of money, lack of transport, and facility being too far away) highlight broader issues with access to health care for populations in DRC. In addition to the reasons cited by survey respondents, the obligation to pay for care at facilities and lack of medications available at health facilities are likely additional or compounding reasons for low rates of both care-seeking at facilities and referral adherence.

Although the baseline and endline survey results are not directly comparable, they are in line with trends in routine monitoring data collected by IRC over the course of the project. Routine monitoring data show that treatment of cough with fast or difficult breathing with amoxicillin by ReCos increased from 158 cases in September 2014 to 6,896 cases in November 2016, with a big dip from May to October 2016, coinciding with international amoxicillin procurement issues and local stockout issues. IRC’s routine monitoring data also show increasing trends for diarrhea and malaria treatment. Annex G provides graphs of these trends.

Although the endline survey results are skewed toward areas that likely had better and more continuous access to health services, and not fully representative of the RAcE DRC project area, they show a high percentage of caregiver knowledge and care-seeking and suggest needed improvements in appropriate treatment. Greater improvements in access to quality health care are needed to meet the health needs of children in Tanganyika province. There is a need for the MoPH and its partners to continue supporting ReCos to provide iCCM services. This may include strengthening the supply chain; improving quantification of drugs; and motivating head nurses (l’infirmier titulaire) to attend monthly meetings, get restocked by the central health bureau, and restock and coach ReCos during supervision visits.

8 ReCos had the following percentages of each drug in stock in October 2016: ORS: 84 percent; zinc: 81 percent; amoxicillin: 22 percent; ACT1: 85 percent; ACT2: 90 percent; ACT suppository: 95 percent; and RDT: 95 percent. 9 ReCos had the following percentages of each drug in stock in November 2016: ORS: 88 percent; zinc: 86 percent; amoxicillin: 69 percent; ACT1: 89 percent; ACT2: 90 percent; ACT suppository: 92 percent; and RDT: 92 percent.


ANNEX A. SUMMARY OF SAMPLING METHODOLOGY

A total of 21 clusters from the anticipated sample of 30 clusters were replaced at various points in survey preparation and implementation. Table A1 summarizes the replacement methodologies used.

Table A1. Clusters that were replaced for the endline survey

Health zone # of

replaced clusters

Reasons for replacement

Timing Method

Multiple 9 Ended up not being part of RAcE coverage area

Pre-endline implementation

Re-selected by ICF from the sampling frame using the criteria that the replacements be nearby clusters with similar population size to the original (baseline) cluster Multiple 2 Villages no

longer existed at endline


Nyunzu 5 Insecurity pre-endline


By IRC, pre implementation PPS using remaining sampling frame (from baseline)

Kalemie 4 Insecurity During endline implementation

By IRC, during implementation Based on security concerns, proximity to the cluster that needed to be replaced, the population, and distance from the health center

Nyemba 1 Insecurity During endline implementation

Within each cluster, the survey team used a random number table to randomly select the first household for interview. Following the first randomly selected household in each cluster, the survey team proceeded to the household with its front door nearest to the front door of the current household until the team conducted 10 interviews with caregivers who had a child with illness during the past 2 weeks. A household was defined as a group or people who eat from the same cooking pot or whose meals are prepared together.

At each household, the enumerator first determined if an eligible child lived there. An eligible child was aged 2–59 months and had been sick with diarrhea, fever, or cough with difficult or fast breathing, or any combination of the three illnesses in the 2 weeks preceding the survey. Survey teams used age calendars to more easily determine eligibility of children. If the caregiver was not present in the households at the time of the initial visit, the team made up to three revisits to complete an interview.

If there was an eligible child in the household, the interviewer administered the questionnaire, including all applicable illness modules, to the caregiver of the eligible child. If more than one child was eligible, and they were sick with different illnesses, their caregiver was asked about each instance of illness. If there was more than one eligible child in the household for an illness, the interviewer randomly selected one of the eligible children and interviewed his or her caregiver.

In 12 clusters, survey teams were unable to identify an adequate number of cases of each disease and thus proceeded to the neighboring village to complete the interviews.


ANNEX B. BASELINE AND ENDLINE SAMPLES

Baseline Survey Sample

Zone de Sante Aire de Sante Village Population

deservie par le site

Distance village - CS

(km)

Population aged 2–59

months

KALEMIE NYEMBA NGANGO 230 8 37

KALEMIE FATUMA KATONTOKA 526 15 84

KALEMIE TEMBWE KAHUBI 581 18 93

KALEMIE MULANGE KAMALENGE 689 5 110

KANSHIMBA MAZONDE MPAMA 371 15 59

KANSHIMBA KANSAMBALA KITINDA 195 35 31

KANSHIMBA KIBIZIWA KILANDO 109 10 17

KANSHIMBA KABELE KIFUPA 49 23 8

KONGOLO KILAE MWEPU 1700 8 272

KONGOLO KILEMBI LWANGA 1045 19 167

KONGOLO MUKOKO KALAWA MWANAKITENGE 329 11 53

MBULULA KAHENGA MUTANTWA 237 6 38

MBULULA BUYOVU LUNGILA 79 6 13

MBULULA KABUNDI BATULE 139 11 22

MBULULA KATEBA KATIKALAKALA 158 9 25

MBULULA MAKUTANO COMPONI 133 5 21

MBULULA KUNDU MWALIKUNI 66 6 11

MBULULA BIGOBO BUNGU 409 10 65

MOBA PEPA LUVUNGI 1931 17 309

NYEMBA L/KATENGA KASANGALA 200 11 32

NYEMBA MULOLWA BYOKABA 130 18 21

NYEMBA TABAC KAMAKALA 142 9 23

NYEMBA RUGUMBA UZI 1,065 11 170

NYEMBA TUDWA DJIMBWE NYUNZU MULONGO KAHENDWA 99 6 16

NYUNZU NGOY KAUNDANGOY 79 9 13

NYUNZU MUKUNDI LEVI 504 16 81

NYUNZU KABEYA MAY KATI 217 6 35

NYUNZU ZONGWE MPINDA 202 6 32

NYUNZU MASAMBA KEBUYUE 33 8 5

NYUNZU NGOMBE KYULU 142 8 23


Endline Survey Sample

Zone de Sante

Aire de Sante Village Population

deservie par le site

Distance village - CS (km)

Population aged 2–59

months Commentaire

KANSHIMBA KABELE KIFUPA 49 23 8

Relais actif (une dame) et le SSC est accessible par véhicule.

KANSHIMBA KANSAMBALA KITINDA 195 35 31

Relais actif et le SSC n'est accessible que par moto,le véhicule ne pourra s'arrêter juste au niveau du CS.

KANSHIMBA MAZONDE MPAMA 371 15 59 Relais actif et est accessible par véhicule

KANSHIMBA KANSAMBALA KABEYA 541 10 87

Relais actif et est accessible par véhicule

KANSHIMBA KIBIZIWA KYANGEZNZE 87 18

Replaced Kansonso (Nyunzu)

KANSHIMBA KIBIZIWA LWAN YE 168 35

Replaced Musongi (Nyunzu)

KONGOLO KILAE MWAHU 1,700 8 272

SSC fonctionnel( 2 SSC: Mwehu 1&2)

KONGOLO KILEMBI LWANGA 1,045 19 167 SSC fonctionnel

KONGOLO MUKOKO KALAW MWANAKITENGE

329 11 53 SSC fonctionnel

KONGOLO SOLA KAHAMBWE KILUMBU 142 8

Replaced Kyulu (Nyunzu)

MBULULA BIGOBO BUNGU 409 10 65 SSC fonctionnel

MBULULA KAHENGA MUTANTWA 237 6 38 SSC fonctionnel

MBULULA BUYOVU MACHEKELE 80 10 MBULULA KABUNDI KAHOMPO 2 179 7.5 MBULULA KATEBA KIBAMBA 1 69 14

MBULULA KUNDU KALUNGULUNGU 452 12

MBULULA MAKUTANO LWANGALI 481 5

MBULULA KASAWA KAVUMA 223 5

Replaced Kati (Nyunzu)

MBULULA KAYENGE MILUNDWA 520 15 Replaced Levi (Nyunzu)

MBULULA KABUNDI MULENDA 55 10

Replaced Kibwe (Nyunzu)


NYEMBA L/KATENGA KASANGALA 200 11 32 SSC fonctionnel

NYEMBA L/KATENGA SHIBUKUMBA 214 6 NYEMBA MULOLWA MUTABI 86 17 NYEMBA KISONGO KABUGA 490 12 78 NYEMBA TABAC BASOMBO 142 13

NYEMBA MAHILA BULONGO

1,818 8 291

Replaced Bulongo (Fatuma/Kalemie)

NYEMBA MULEKA RUGOGO 1

758 13 121

Replaced Kamalenge (Nyemba/Kalemie)

NYUNZU SULUMBA MUFKWA

837 134 8

Replaced Mulumbi (Nyemna/Kalemie)

NYUNZU SULUMBA MPENDE

731 117 7

Replaced Mumbwili (Nyemba/Kalemie)

NYEMBA TABAC KALENGE

719 115 13

Replaced Katutuma (Tundwa/Nyemba)


ANNEX C. SURVEY QUESTIONNAIRE

See attached


ANNEX D. PEOPLE INVOLVED IN ENDLINE SURVEY IMPLEMENTATION

Name Organization Role

1. Pascal Ngoy IRC DRC Health Director

2. Alison Wittcoff IRC Health Technical Advisor

3. Bibiche Malilo IRC RAcE Coordinator (acting/interim)

4. Bronwyn Nichol IRC Health Research, M&E Coordinator

5. Maxime Bushiri IRC HMIS Manager

6. Josephine Kasongo IRC Pharmacist/Admin

7. Claude Dumbu IRC Supervisor

8. Rebecca Kalenga IRC Supervisor

9. Gilbert Mucthwima IRC Supervisor

10. Innocent Ngongo IRC Supervisor

11. Alpha Tambwe IRC Supervisor

12. Andre Yabota IRC Supervisor

13. Bertha Yumba Yomeni IRC Interviewer

14. Charlotte Ashina IRC Interviewer

15. Elisabeth Matende Samba IRC Interviewer

16. Esther Oracle Muerwa IRC Interviewer

17. Felix Mulindi IRC Interviewer

18. Francine Bembeleza Lusanga IRC Interviewer

19. Marie Shimba Alewo IRC Interviewer

20. Michael Lufimbo Kanamu IRC Interviewer

21. Pelerin Mwilambwe IRC Interviewer

22. Plamedie Kalume IRC Interviewer

23. Samuel Ngoy Kasanga IRC Interviewer

24. Serge Sabiti Kabinga IRC Interviewer

25. Unnamed IRC Data Entry







ANNEX E. SURVEY TRAINING SCHEDULES

Training Schedule for Supervisors

Jour Temps Activité Description

Mercredi, 26/10

8:30 Introduction Aperçu de l'enquête:

Fournir une description de l'objet de l'enquête et de la formation.

Réviser le programme de formation, notant que la formation comprend

Décrire l'échantillon

Décrire le questionnaire, et les modules à inclure

Le personnel de l’enquête:

Rôles du personnel de l'Enquête RAcE

Supervision des entrevues

13:00 déjeuner

14:00 Procédures de travail sur le terrain

Assurer la confidentialité

Consentement éclairé

16:30 Q&R Temps pour Q&R

Jeudi, 27/10 8:30 Sélection des ménages

Sélection des répondants

Qualité des données

13:00 Déjeuner

14:00 Vérification des questionnaires remplis.

17:00 Q&R Q&R

Vendredi, 28/10

8:30 Le questionnaire Parcourir le questionnaire, question par question.

13:00 Déjeuner

14:00

Fiche du superviseur

Erreurs courantes

17:00 Q&R Q&R


Training Schedule for Enumerators

Jour Temps Activité Description

Vendredi, 4/11

8:30 Introduction Aperçu de l'enquête:

Fournir une description du projet RAcE et discuter de l'objet de l'enquête et de la formation.

Réviser le programme de formation, notant que la formation comprend

Décrire l'échantillon

Décrire le questionnaire, et les modules à inclure

13:00 déjeuner

14:00 Le personnel de l’enquête:

Rôles du personnel de l'Enquête RAcE

Supervision des entrevues

16:30 Q&R Temps pour Q&R

Samedi, 5/11

8:30 • Procédures de travail sur le terrain

o Assurer la confidentialité

• Consentement éclairé

o Que faire lorsque les répondants potentiels refusent de participer

o Comment répondre aux questions des répondants, devraient-ils au préalable consentir avant de participer

o Obtenir un consentement verbal et l'enregistrer sur le formulaire

13:00 Déjeuner

14:00 • Sélection des ménages

• Sélection des répondants

• Qualité des données

o Vérification des questionnaires remplis.

17:00 Q&R Q&R

Dimanche, 6/11

8:30 Remplir le questionnaire

Parcourir le questionnaire, question par question. \

Pour chaque question:

• parvenir à un consensus sur la façon de la poser dans la langue locale

• Examiner les options de réponse, y compris les réponses acceptables dans la langue locale


• S'accorder sur les révisions nécessaires, s'il y a un consensus au sein de toute l'équipe

13:00 Déjeuner

14:00 Remplir le questionnaire

Suite

17:00 Q&R Q&R

Lundi, 7/11 8:30 Pratique Essaye sur terrain du questionnaire

13:00 Déjeuner

14:00 Compte rendu de l’essaye au terrain

17:00 Q&R Q&R

Mardi, 7/11 8:30

Revue des erreurs courantes

13:00 Déjeuner

14:00

Discussion des logistiques

16:00 Q&R Q&R


ANNEX F. SURVEY FIELDWORK SCHEDULE

Supervisor: Innocent Enqueteurs: Michael et Elisabeth

Day Groupe 1 - Matin Apres-midi Lieu de logement Commentaire

10-Nov Preparation 11-Nov Voyage pour Lambo Katenga en Vehicule 145 km Dormir a Lambo Katenga

12-Nov Travaille a Kasangala - Retour a L/Katenga

11 Km 11 Km Dormir a Lambo Katenga pour atteindre plusieurs menages on travaille apres midi

13-Nov Travaille a Shibukumba - Depart pour Mahila

6 Km Dormir a Mahila IDEM

14-Nov Voyage de Mahila a Mulolwa 190 Km Dormir a Mulolwa on passe nuit a Mulolwa

15-Nov Travaille a Mutabi 5 Km Dormir a Mulolwa travaille apres midi

16-Nov Voyage de Mulolwa a Tabac 130 Km Dormir a Tabac Congo passer nuit a Tabac

17-Nov Travaille a Basombo/Kayombo 4 Km Dormir a Tabac Congo travaille apres midi

18-Nov Voyage de Tabac a Kisongo et travaille a Kabuga

47 Km 12 Km Dormir a Kisongo on travaille d'abord Kabuga et on passe nuit a Kisongo

19-Nov 62 Km retour a Kalemie

20-Nov

21-Nov Retour a Kalemie

22-Nov Entretien vehicule

23-Nov 24-Nov Depart Tabac-Travail a Kalenga 25 Km 12 Km Dormir a Tundwa

25-Nov Continue a Travailler a Kalenga - Retour a Kalemie

12 Km 25 Km retour a Kalemie


Supervisor: Gilbert Enqueteurs: Esther et Serge


9-Nov preparation

10-Nov Voyage sur Moba centre 408 km Dormir à Moba centre

11-Nov BCZS - TERRITOIRE -Voyage + Travail à Kitinda -retour sur Maseba 42 Km 22 Km Dormir à Maseba

12-Nov Voyage + Travail sur Mpama - retour a Moba Centre 35 Km 15 km Dormir à Moba centre usage de la moto

13-Nov Voyage pour l'AS. Fatuma(PS de Machine) 318 Km -- Dormir au PS MACHINE Accessible par vehicule

14-Nov Voyage a Bulongo-Travail a Bulongo Moto - Retour Mulange 6 Km 70 Km Dormir a Mulange

15-Nov Travail a Kamalenge - Retour Kalemie - Depart Tundwa 5 Km 55 km Dormir a Tundwa

16-Nov Travail a Katutuma - Voyage vers Nyemba 12 Km du CS Dormir a Tundwa

17-Nov Retour a Kalemie 55 Km

18-Nov

19-Nov

20-Nov

21-Nov Quitte Moba pour Kabwela 208 Km Dormir a Kabwela

22-Nov Quitte Kabwela pour Kalemie - Voyage pour Mahila 200 Km 120 Km Dormir a Mahila

23-Nov Travaille a Bulongo 8 Km 8 Km Dormir a Mahila

24-Nov Quitte Mahila pour Muleka - Travaille a Rugogo 1 60 Km 13 Km Dormir a Muleka

25-Nov Continue a Travailler a Rugogo 1 - Retour a Kalemie 13 Km 60 Km Retour a Kalemie


Supervisor: Rebecca Enqueteurs: Charlotte et Samuel


9-Nov préparation

10-Nov Voyage sur Moba centre 408 km Dormir à Moba

11-Nov BCZS - TERRITOIRE - voyage sur Mutotomoya/Kabele 202 Km Dormir à Mutotomoya/Kabele

Présenter les civilités aux autorités

12-Nov Voyage + Travail à Kifupa - aller sur Mwanza 23 Km 61 Km Dormir à Mwanza

13-Nov Voyage sur Moba centre 130 Km Dormir à Moba

14-Nov Voyage sur Kibiziwa 145 km Dormir à Mulungushi

Peut arriver à Mulungushi par voiture,mais besoin de prendre les moto à Moba centre

15-Nov Voyage et Travail à Lwanye - aller sur Kyankenze 27 Km 13 Km Dormir à kyankenze

Usage de la moto du CS au SSC

16-Nov Travail à Kyankenze + retour à Mulungushi 21 Km Dormir à Mulungushi Usage de la moto

17-Nov Voyage sur Moba centre 145 km Dormir à Moba centre

18-Nov Voyage + Travail Kabeya - retour à Shebele 70 Km 10 km Dormir à Shebele

Peut arriver à Shebele par voiture,mais besoin de prendre les moto à Moba centre

19-Nov Voyage sur Kalemie 408 Km


Supervisor: Andre Enqueteurs: Francine et Marie


9-Nov preparation

10-Nov Voyage pour Nyunzu 194 km -- Dormir a Nyunzu

11-Nov Continuer le voyage jusqu'a Kongolo 176 km -- Dormir a Kongolo Centre

12-Nov BCZS - TERRITOIRE -Voyage jusqu'a Lwanga 90 km -- Dormir a Lwanga

La voiture va arriver jusqu'a Kabeshi et de la l'equipe pourra faire 6 km a pieds comme la fois passe

13-Nov Travail a Lwanga - Voyage pour Kongolo Centre -- 90 Km Dormir a Kongolo Centre

14-Nov Voyage pour Kilae /Mwehu 78 km -- Dormir a Kilae/Mwehu

15-Nov Travail a Mwehu et retour a Kongolo Centre -- 78 km Dormir a Kongolo Centre Le vehicule arrive

16-Nov Voyage jusqu'a Sola et travail a Kahambwe Kilumbu 30 km Dormir a Sola

17-Nov

Voyage jusqu'a Kalawa - travail Kalawa Mwanakitenge et retour a Kongolo (Sola-Kalawa 16 km) 16 Km 30 Km Dormir a Kongolo Centre

18-Nov Voyage Pour Nyunzu 176 km Dormir a Nyunzu

19-Nov Voyage pour Kalemie 194 km Kalemie


Supervisor: Alpha Enqueteurs: Pelerin et Bertha


9-Nov Preparation

10-Nov Voyage pour Nyunzu 194km en vehicule -- Dormir a Nyunzu

11-Nov Voyage pour Mbulula 122 Km -- Dormir a Mbulula centre

12-Nov Formalite & civilite ECZS - Depart Kasawa - Travail a Kavuma 70 Km 5 Km Dormir a Kabanzi

A pieds ou moto de Kibanzi a Kuvuma(5 km)

13-Nov Depart de Kavuma pour Makutano - Travaille a Lwangali 35 Km 6 Km Domir a Makutano

14-Nov Depart de Makutano pour Kayenge - Travail a Milundwa 25 Km 15 Km Dormir a Milundwa

15-Nov Suite travail a Milundwa et depart pour Kundu -Travaille a Kalungulungu 36 Km 12 Km Dormir a Kalungulungu

16-Nov Suite de travail a kalungulungu - depart pour Bigobo - Travaille a Bungu 40 Km 10 Km Domir a Mahundu(PS)

17-Nov Suite de travail a bungu et retour a Mbulula 35 Km Dormir a Mbulula centre

Vehicule reste au PS Mahundu et pieds de 6 km jusqu'a Bungu

18-Nov Voyage pour Nyemba 122 Km -- Dormir a Nyemba Centre

19-Nov Travail a Mumbwili 12 km de Nyemba Dormir a Nyemba Centre

20-Nov Retour a Kalemie 194 Km en vehicule

21-Nov Dormir a Nyunzu Centre

22-Nov Quitter Nyunzu pour Sulumba - Travail a Mufukwa 64 Km 8 Km Dormir a Sulumba

23-Nov Travail a Mufukwa - depart pour Nyunzu 8 Km 64 Km Dormir a Nyunzu Centre

24-Nov Retour a Kalemie 194 Km Retour a Kalemie


Supervisor: Claude Enqueteurs: Felix et Plamedie


10-Nov Preparation

11-Nov Voyage pour Nyunzu 194km en vehicule -- Dormir a Nyunzu

12-Nov Voyage pour Mbulula 122 Km -- Dormir a Mbulula centre

13-Nov Formalite & civilite ECZS - Depart Kateba - Travail a Kibamba 1 122 Km 14 Km Dormir a Kibamba

Juste un cocher au CS pour feu vert sur terrain

14-Nov Travaille a Kibamba - depart a Buyovu 30m Dormir a Buyovu

15-Nov Travaille a Mashegele - depart pour Mupenda 35km Dormir a Mulenda

16-Nov travaille a Mulenda - depart a Kabundi - Travaille a Kahompo 2 15km Dormir a Kabundi CS

17-Nov Depart a Kahenga - Travaille a Mutantwa 20 Km Dormir a Kahenga CS

18-Nov Retour a Mbulula 100 Km Dormir a Mbulula centre

19-Nov Voyage pour Nyemba 122 Km -- Dormir a Nyemba Centre

20-Nov Travail a Mulumbi 12 km de Nyemba Dormir a Nyemba Centre

21-Nov Dormir a Nyunzu Centre

22-Nov Quitter Nyunzu pour Sulumba - Travail a Mpende 64 Km 7 Km Dormir a Sulumba

23-Nov Travail a Mpende - depart pour Nyunzu 7 Km 64 Km Dormir a Nyunzu Centre

24-Nov Retour a Kalemie 194 Km Retour a Kalemie


ANNEX G. ROUTINE MONITORING TREATMENT DATA TRENDS

Figures G1–G3 show trends in routine monitoring data for pneumonia, diarrhea, and malaria treatment captured by IRC over the course of the project, up to November 2016.

Figure G1. Trends in pneumonia treatment

There is a large variance in pneumonia treatment over the course of the project. The big dips were mainly stockouts because even at the international level there were problems with procuring amoxicillin. In general, when medications were available treatments were constantly increasing over the life of the project as IRC continued expanding the network of ReCos.

Figure G2. Trends in diarrhea treatment

Dips in diarrhea treatment correspond to periods of stockouts.

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Figure G3. Trends in malaria treatment

Some dips in malaria treatment correspond to period of stockouts, and others are related to seasonality; there is more malaria during the rainy season.

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ENDLINE SURVEY FINAL REPORT International Rescue … · Moba, Nyemba, and Nyunzu. In November 2016,...

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