ArticleProceedings. Biological sciences2019
Predictive analysis across spatial scales links zoonotic malaria to deforestation.
Article in Proceedings. Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.
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Who cites it
52 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence.The Journal of animal ecology · 2020Pooled it
- Article
- Malaria Prevalence Near African Mangroves: Negative Association With Mangrove Extent, but Positive Association With Mangrove Greenness.Global change biology · 2026Article
- Larval habitat preferences of Anopheles dirus and Anopheles maculatus in North Sumatra, Indonesia.Parasites & vectors · 2026Article
- Submicroscopic Burden of Zoonotic Plasmodium knowlesi Malaria on Mursala Island and Plasmodium falciparum and Plasmodium vivax Transmission in Mainland North Sumatra, Indonesia.The American journal of tropical medicine and hygiene · 2026Article
- Plasmodium knowlesi and global changes: socio-ecological drivers and challenges.Malaria journal · 2025Review
- Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models.BMC medical informatics and decision making · 2025Article
- Household costs associated with zoonotic Plasmodium knowlesi, P. falciparum, P. vivax and P. malariae infections in Sabah, Malaysia.PLoS neglected tropical diseases · 2025Article
- Genomic epidemiology of Plasmodium knowlesi reveals putative genetic drivers of adaptation in Malaysia.PLoS neglected tropical diseases · 2025Article
- Emerging malaria in Indonesia: An overview ofParasite epidemiology and control · 2025Article
- A virus associated with the zoonotic pathogenbioRxiv : the preprint server for biology · 2024Article
- A scoping review on bovine tuberculosis highlights the need for novel data streams and analytical approaches to curb zoonotic diseases.Veterinary research · 2024Article
- Naturally acquired immunity toParasitology · 2024Article
- Updating estimates of Plasmodium knowlesi malaria risk in response to changing land use patterns across Southeast Asia.PLoS neglected tropical diseases · 2024Review
- A virus associated with the zoonotic pathogenVirus evolution · 2024Article
- Article
- Updating estimates ofmedRxiv : the preprint server for health sciences · 2023Article
- No evidence of sustained nonzoonotic Plasmodium knowlesi transmission in Malaysia from modelling malaria case data.Nature communications · 2023Article
- Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance.Remote sensing · 2023Article
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9 authors.
Funding
Abstract
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechanisms are unknown. Here, a novel application of a method for predicting disease occurrence that combines machine learning and statistics is used to identify the key spatial scales that define the relationship between zoonotic malaria cases and environmental change. Using data from satellite imagery, a case-control study, and a cross-sectional survey, predictive models of household-level occurrence of P. knowlesi were fitted with 16 variables summarized at 11 spatial scales simultaneously. The method identified a strong and well-defined peak of predictive influence of the proportion of cleared land within 1 km of households on P. knowlesi occurrence. Aspect (1 and 2 km), slope (0.5 km) and canopy regrowth (0.5 km) were important at small scales. By contrast, fragmentation of deforested areas influenced P. knowlesi occurrence probability most strongly at large scales (4 and 5 km). The identification of these spatial scales narrows the field of plausible mechanisms that connect land use change and P. knowlesi, allowing for the refinement of disease occurrence predictions and the design of spatially-targeted interventions.
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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.