Evidence map›Paper›PMID 40442675›Full record

ArticleBMC public health2025

Spatiotemporal patterns and climate-induced macroeconomic burden of malaria in sub-Saharan Africa.

Tianen Yao, Xinyu Yang, Huaixiao Ye, Yida Wang, Xiaoyi Yu, Yuxin Huang, Ming Xu

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Tianen YaoDepartment of Global Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191, China.
Xinyu YangDepartment of Global Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191, China.
Huaixiao YeCollege of Urban and Environmental Sciences, Peking University, Beijing, 100191, China.
Yida WangHarris School of Public Policy, The University of Chicago, Chicago, IL, 60637, USA.
Xiaoyi YuDepartment of Global Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191, China.
Yuxin HuangDepartment of Global Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191, China.
Ming XuDepartment of Global Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191, China. xum2022@pku.edu.cn.

Funding

Gates Foundation INV-049673
6 · The paper itself

Abstract

backgroundThe global malaria burden is characterized by economic, geographical, and climatic disparities, especially in sub-Saharan Africa (SSA). Moreover, meteorological factors have become increasingly important to understand the malaria burden in SSA in the context of climate change.

methodsValue of Statistical Life Year (VSL) and machine learning are proposed to jointly assess the weather-induced economic burden of malaria in SSA from 2000 to 2022. Geographic information systems (GIS) are employed to examine the spatial autocorrelation of malaria burden and address the issues of spatiotemporal heterogeneity. Finally, the uncertainty in the relationship between weather patterns and malaria burden was tested for robustness using Bayesian statistics.

resultsMalaria mortality in SSA has decreased by 30 per 100,000 incidences annually from 2000 to 2022. The macroeconomic burden of malaria accounts for 1.58% of the total GDP in SSA, equating to USD 497.06 billion (95% CI, [418.38, 553.56]), with weather conditions contributing 60% of the economic burden. The climate-related macroeconomic burden of malaria mortality varies dramatically across regions, with East Africa bearing the highest cost at USD 195.90 billion, followed by Central Africa (57.36 billion), West Africa (30.43 billion), and Southern Africa (1.81 billion). Besides, there is notable autocorrelation and spatial heterogeneity in malaria patterns. East Africa has a high malaria burden and is climate vulnerable. For every 1 °C increase in temperature in SSA, the number of malaria incidences will rise by 16.30 [95% Credible Interval (CrI), (13.88, 18.61)] per 1,000 incidences, while malaria-related deaths per 100,000 incidences will increase by 5.79 [95% CrI, (4.90, 6.74)].

conclusionsRising temperatures have increased the burden of malaria, especially in East and Central Africa. Climate change also indirectly increases the economic burden associated with malaria, which could put enormous pressure on government health budgets. Therefore, local governments in East Africa should adopt measures to cope with climate warming and allocate resources rationally to achieve the goal of malaria elimination by 2030.

Indexed as

Climate ChangeCost of IllnessMalariaAfrica South of the SaharaBayes TheoremGeographic Information SystemsHumansIncidenceMachine LearningSpatio-Temporal AnalysisWeatherClimate changeEconomic burdenGISMalaria mortality

Identifiers

PMID40442675
PMCPMC12121131

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.