ArticlePLOS global public health2025
Modelling the impact of climatic and environmental variables on malaria incidence in Tanzania: Implications for achieving the WHO's 2030 Targets.
Article in PLOS global public health, 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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1 citing paper in PubMed.
- Recent advances in machine learning and Bayesian modeling for tropical disease prediction, diagnosis, and risk analysis: a scoping review.BMC infectious diseases · 2026Article
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7 authors.
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Abstract
Malaria remains a significant public health challenge, particularly among vulnerable populations in high-burden countries like Tanzania. Despite progress in reducing malaria incidence, climatic and environmental condition variability has led to uneven reductions, hindering the achievement of the WHO 2030 targets. We assessed the impact of climatic and environmental variables on malaria incidence to better understand spatial and temporal trends and their implications for the WHO targets. We utilized geo-covariate data from the Demographic and Health surveys (DHS) program, applying a Moran's I test for spatial autocorrelation, a geostatistical Bayesian-based model to predict malaria incidence at an unsampled locations, and calculated the percentage change in predicted incidence over a ten-year interval. The results showed that malaria incidence decreased with greater variance across Tanzania. Mean malaria incidence decreased from 0.347 (95% CI: 0.336, 0.357) in 2000 to 0.118 (95% CI: 0.114, 0.122) in 2020, relative to the increasing insecticide-treated bednets (ITNs) coverage (0.037; 95% CI: 0.036, 0.039 in 2000 to 0.496; 95% CI: 0.476, 0.517 in 2020). Malaria incidence was higher in the Lake, western, eastern and southern zones compared to others, with spatial clustering observed (Moran's I of 0.93 in 2000, 0.87 in 2010, and 0.74 in 2020). Higher temperatures increased malaria incidence (Odds ratio (OR): 1.06; 95% credible interval (CI):1.04,1.08 and 1.13;95% CI:1.10,1.16) in 2000 and 2010, respectively). Enhanced vegetation index increased the likelihood of malaria incidence (ORs ranging from 5.28; 95% CI: 4.96,5.61) in 2000 to 6.22; 95% CI: 5.91,6.55) in 2020 and higher aridity was associated with higher malaria incidence (ORs: 1.11; 95% CI: 1.10,1.13) in 2010 and 1.07; 95% CI: 1.06,1.07) in 2020). To achieve the WHO 2030 malaria reduction targets, fine-scale and region-specific interventions are essential to mitigate the impact of climate and environmental factors on malaria incidence.
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