Integrating indigenous knowledge and ecological modeling to understand anthrax transmission risk.

Authors

Juan Martin Dabezies, Maria Zubkova, Christian Fohringer, Kevin M Curtin, Delong He, Henriette van Heerden, Meredith L Gore

Published in

PLoS neglected tropical diseases. Volume 20. Issue 11. Pages e0014796. Epub Nov 10, 2026.

Abstract

Anthrax, caused by Bacillus anthracis, remains a persistent zoonotic threat across African savannas, yet its transmission dynamics are poorly understood in regions with limited surveillance systems. Northern Limpopo National Park (Mozambique) combines ecological conditions favorable for spore persistence with Indigenous communities that depend on unfenced grazing and frequent wildlife contact. We integrated ecological suitability modeling with participatory mapping of extensive cattle herding practices to generate fine-scale risk surfaces for anthrax transmission. Ecological modeling indicated broad suitability for spore survival, while participatory mapping revealed localized exposure risk zones. The integrated model refined these patterns by identifying areas where broad ecological suitability intersected with locally mapped livestock use and potential exposure pathways. While the highest suitability class did not consistently coincide with mapped high-exposure features, most participatory risk layers fell within moderately suitable zones, suggesting that fine-scale transmission concern is structured by everyday grazing, water use, and mobility within an environmentally favorable landscape. This integration captures pathogen persistence potential and context-specific exposure dynamics, providing a socially grounded approach to risk prioritization in the absence of robust outbreak records. The findings help inform contextualized and targeted prevention and response options-such as risk communication, vaccination campaigns, and community-based surveillance-and illustrate how combining ecological modeling with Indigenous spatial knowledge can help strengthen zoonotic risk assessments in under-surveilled settings.

PMID:
43008052
Bibliographic data and abstract were imported from PubMed on 11 Nov 2026.

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