ArticleLancet regional health. Americas2025
Human mobility, garimpos and spatiotemporal malaria transmission in the Yanomami Indigenous Territory: a retrospective observational study.
Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Malaria Test Positivity, Temporal Trends, and Associated Factors Among Clinically Suspected Adult Cases in Maruleng Sub-District, Limpopo Province, South Africa, 2018-2023.International journal of environmental research and public health · 2026Article
- Spatiotemporal Evolution and Emergence of Frontier Malaria Mosaics in the Brazilian Amazon.Research square · 2026Article
- Malaria in the 21st Century: Global Disease Burden, Epidemiological Insights, and Strategic Control Approaches.Biology · 2026Review
- Towards Malaria Elimination: A Nationwide Case-Control Study to Assess Risk Factors for Severe Malaria-Related Deaths in Brazil.Tropical medicine & international health : TM & IH · 2025Article
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Authors and funding
2 authors.
Funding
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Abstract
Background: Past research on human mobility and malaria transmission often used coarse spatial scales, limiting effectiveness for targeted control strategies - especially as transmission becomes more localized with lower incidence. This is seen in Brazil's Yanomami Indigenous Territory (YIT), where illegal gold mining ( Methods: MMN quantified diffusion effects and differentiated between autochthonous and imported malaria cases among localities. Integrating malaria and population location data into a regular grid improved the accuracy of malaria risk and transmission assessments. Findings: We observed spatial concentration of malaria cases (86%) and population (91%), and most grids have incorrectly attributed malaria (94%) and population (86%) risks. We improved spatial identification of malaria cases in 12% (70% in Interpretation: Spatial analysis reveals spatiotemporal linkages between residence-based human mobility and malaria, supporting improved epidemiological surveillance. MMN demonstrates how spatiotemporal patterns of malaria transmission aligns with Funding:
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