Evidence map›Paper›PMID 41088283›Full record

ArticleMalaria journal2025

Institutional quality, aid flows, and malaria burden: a geospatial analysis of sub-Saharan Africa.

Caroline Namubiru

Abstract read
In one paragraph

Article in Malaria journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

1 author.

Caroline NamubiruDepartment of Economics, Faculty of Economics and Social Sciences, University of Tübingen, Tübingen, Germany. carolinen97@gmail.com.

Funding

Central African Infectious Disease and Epidemics Research Alliance (CAIDERA) under the German Academic Exchange Service (DAAD) Project ID 57592740
6 · The paper itself

Abstract

backgroundMalaria remains a major public health challenge in sub-Saharan Africa, accounting for approximately 95 percent of global malaria deaths despite extensive interventions. Significant disparities persist in disease burden across countries, with some achieving remarkable progress while others experiencing persistently high transmission rates, suggesting factors beyond resource availability influence disease control effectiveness. This study examines the relationship between institutional quality, development aid flows, and malaria burden across 38 sub-Saharan African countries during 2010-2022.

methodsThe analysis employed malaria cases and deaths per 1,000 population as malaria burden measures. Key explanatory variables included development assistance for health per capita, government effectiveness indices and health worker density as institutional quality indicators, alongside control variables for intervention coverage, climatic factors, and socioeconomic conditions. Data was sourced from the World Health Organization, United Nations Development Program, Institute for Health Metrics and Evaluation, Malaria Atlas project, Demographic and Health surveys, and World Bank databases. Spatial econometric models, including Spatial Durbin Models, Spatial Lag of X, and Spatial Durbin Error Models, were used to account for spatial autocorrelation and cross-border transmission effects, while fixed-effects models with Driscoll-Kraay standard errors provided baseline estimates.

resultsThe study found overall malaria burden reduction across sub-Saharan Africa. Malaria cases and deaths demonstrated significant spatial autocorrelation annually, indicated by Moran's I statistics. Findings revealed that increased health worker density, enhanced institutional effectiveness, and higher aid levels are positively associated with the burden. These effects persisted with lagged values of health workers and government effectiveness. The geospatial analysis reveals that the malaria burden is driven more by local conditions with limited spillover effects from neighbouring countries.

conclusionFindings highlight that while malaria burden has generally declined across sub-Saharan Africa, it is spatially clustered. There is need for localized health systems strengthening alongside targeted regional coordination.

Indexed as

Cost of IllnessMalariaAfrica South of the SaharaHumansSpatial AnalysisMalariaSpatial effectsSpatial panel data models

Identifiers

PMID41088283
PMCPMC12519830

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