Independent Evaluation of the Rapid Scale-Up Program to Reduce Under-Five Mortality in Burkina Faso

Munos, Melinda; Guiella, Georges; Roberton, Timothy; Maïga, Abdoulaye; Tiendrebeogo, Adama; Tam, Yvonne; Bryce, Jennifer; Baya, Banza

doi:10.4269/ajtmh.15-0585

Cited by 40 publications

(53 citation statements)

References 12 publications

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“…Consistent with existing studies, the evaluation method for this study is difference‐in‐differences (DD). Based on mixed‐effects negative binomial modeling , the preferred specification is given by:

\begin{matrix} Y_{ijt} = β_{0} + β_{1} {INT}_{ij} + β_{2} {POST}_{t} + β_{3} {INT}_{ij} * {POST}_{t} + X_{ijt}^{'} γ_{1} + {LGA}_{j}^{'} γ_{2} \\ + α_{1} {TREND}_{t} + {MTH}_{t}^{'} α_{2} + α_{3} {PEAK}_{t} + u_{ij} + ε_{ijt} \end{matrix}

…”

Section: Methodsmentioning

confidence: 88%

“…The assumption does not hold in dynamic settings. Empirical evidence has indicated that, if implemented properly for a sufficiently long period, antimalarial interventions can interrupt malaria transmission, reducing the incidence rate and, consequently, the number of malaria‐related facility visits over time . The introduction of free RDTs, in particular, has been associated with a lower rate of clinical services utilization, with non‐malaria cases being more effectively screened out .…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…The literature suggests that there are time‐varying determinants of antimalarial services utilization that are difficult to account for. Examples include quality of care provided at health facilities, as well as the level of protective immunity and exposure to malaria vectors among different populations in different areas, all of which may change after the introduction of a large‐scale intervention program and may impact the program effects.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Second, a relatively weak research design has been used. Difference‐in‐differences estimates in existing studies are likely to be biased, given the baseline non‐comparability of intervention vis‐à‐vis control groups . Finally, statistical analyses performed in earlier studies have been too simplistic.…”

Section: Introductionmentioning

confidence: 99%

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Effectiveness of antimalarial interventions in Nigeria: Evidence from facility‐level longitudinal data

Witvorapong

Yakubu²

2019

Health Services Research

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Objective To evaluate the effectiveness of a program of antimalarial interventions implemented in 2010‐2013 in Niger State, Nigeria. Data Sources Utilization reports from 99 intervention and 51 non‐intervention health facilities from the Niger State Malaria Elimination Program, supplemented by data on facility‐level characteristics from the Niger State Primary Health Care Development Agency and Local Government Malaria Control units. Study Design Estimated with mixed‐effects negative binomial modeling, a difference‐in‐differences method was used to quantify the impact of the program on the number of febrile illness cases and confirmed malaria cases. Potential confounding factors, non‐stationarity, seasonality, and autocorrelation were explicitly accounted for. Data Extraction Methods Data were retrieved from hard copies of utilization reports and manually inputted to create a panel of 5550 facility‐month observations. Principal Findings The program was implemented in two phases. The first phase (August 2010‐June 2012) involved the provision of free artemisinin‐based combination therapies, long‐lasting insecticidal nets, and intermittent preventive treatments. In the second phase (July 2012‐March 2013), the program introduced an additional intervention: free parasite‐based rapid diagnostic tests. Compared to the pre‐intervention period, the average number of monthly febrile illness and malaria cases increased by 20.876 (P < 0.01) and 22.835 (P < 0.01) in the first phase, and by 19.007 (P < 0.05) and 19.681 (P < 0.05) in the second phase, respectively. The results are consistent across different evaluation methods. Conclusions This study suggests that user‐fee removal leads to increased utilization of antimalarial services. It motivates future studies to cautiously select their investigative methods.

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\begin{matrix} Y_{ijt} = β_{0} + β_{1} {INT}_{ij} + β_{2} {POST}_{t} + β_{3} {INT}_{ij} * {POST}_{t} + X_{ijt}^{'} γ_{1} + {LGA}_{j}^{'} γ_{2} \\ + α_{1} {TREND}_{t} + {MTH}_{t}^{'} α_{2} + α_{3} {PEAK}_{t} + u_{ij} + ε_{ijt} \end{matrix}

…”

Section: Methodsmentioning

confidence: 88%

Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effectiveness of antimalarial interventions in Nigeria: Evidence from facility‐level longitudinal data

Witvorapong

Yakubu²

2019

Health Services Research

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“…iCCM has been shown in smaller experiments to improve child health and reduce child mortality [5]. However, recent evaluations of nationally scaled-up versions have been mixed [6, 7]. …”

Section: Introductionmentioning

confidence: 99%

Hierarchical Statistical Models to Represent and Visualize Survey Evidence for Program Evaluation: iCCM in Malawi

et al. 2016

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Policy and Program evaluation for maternal, newborn and child health is becoming increasingly complex due to changing contexts. Monitoring and evaluation efforts in this area can take advantage of large nationally representative household surveys such as DHS or MICS that are increasing in size and frequency, however, this analysis presents challenges on several fronts. We propose an approach with hierarchical models for cross-sectional survey data to describe evidence relating to program evaluation, and apply this approach to the recent scale up of iCCM in Malawi. We describe careseeking for children sick with diarrhea, pneumonia, or malaria with empirical Bayes estimates for each district of Malawi at two time points, both for careseeking from any source, and for careseeking only from health surveillance assistants (HSA). We do not find evidence that children in areas with more HSA trained in iCCM are more likely to seek care for pneumonia, diarrhea, or malaria, despite evidence that many indeed are seeking care from HSA. Children in areas with more HSA trained in iCCM are more likely to seek care from a HSA, with 100 additional trained health workers in a district corresponding to a 2% average increase in careseeking from HSA. The hierarchical models presented here provide a flexible set of methods that describe the primary evidence for evaluating iCCM in Malawi and which could be extended to formal causal analyses, and to analysis for other similar evaluations with national survey data.

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Integrated community case management of childhood illness in low- and middle-income countries

Oliphant

Manda

Daniels

et al. 2021

Cochrane Database of Systematic Reviews

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Independent Evaluation of the Rapid Scale-Up Program to Reduce Under-Five Mortality in Burkina Faso

Cited by 40 publications

References 12 publications

Effectiveness of antimalarial interventions in Nigeria: Evidence from facility‐level longitudinal data

Effectiveness of antimalarial interventions in Nigeria: Evidence from facility‐level longitudinal data

Hierarchical Statistical Models to Represent and Visualize Survey Evidence for Program Evaluation: iCCM in Malawi

Integrated community case management of childhood illness in low- and middle-income countries

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