Climate-driven host ecology as a framework for zoonotic disease risk: Understanding transferability across arenavirus systems

Mechanistic frameworks linking climate to zoonotic disease risk through host ecology remain rare, limiting transferable insights across systems. We develop a Bayesian framework combining an integral projection model of rodent demography with a compartmental disease model. Applied to capture-mark-recapture data from the Natal multimammate mouse ( Mastomys natalensis ; N = 20,249 captures, 1994–2023) and serological data on the Lassa virus-related Morogoro arenavirus ( N = 7,850 tests, 2010–2017), the framework jointly estimates climatic, demographic, and transmission parameters. Rainfall was a dominant driver of rodent recruitment, with seasonal rainfall explaining 52.1% (95% CrI 2.1 to 79.0%) of modeled recruitment variation. In a field-first, we estimate that 79.1% (95% CrI 69.3 to 88.9%) of infected pregnancies result in vertical transmission, identifying this as the primary mechanism maintaining viral persistence between breeding seasons. We assess framework transferability to capture the seasonal dynamics of Lassa fever outbreaks in Nigeria ( N = 6,469 laboratory-confirmed cases, 2018–2025), substituting model climate inputs without refitting any parameters. Predicted peaks in rodent subadult infections preceded observed outbreaks by 0.92 mo (95% CrI −2.76 to 0.92), with 83% of predicted and observed peaks falling within ±28 d [Pr(Δ ≤ 28d) = 0.83], substantially outperforming seasonal rainfall or rodent demography [Pr(Δ ≤ 28d) ≤ 0.11]. Infected adult peaks lagged observed outbreaks by 0.92 mo [Pr(Δ ≤ 28d) = 0.56], suggesting subadults might primarily be responsible for zoonotic hazard. Outbreak magnitude was not reproduced, likely reflecting human behavioral and surveillance factors beyond the model’s scope. These results illustrate how mechanistic frameworks grounded in reservoir host ecology can yield transferable insights into zoonotic risk, with potential application across other climate-sensitive host–pathogen systems.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2026-09-25
DOI
https://doi.org/10.1073/pnas.2625913123
Primary Topic
Viral Infections and Outbreaks Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Climate-driven host ecology as a framework for zoonotic disease risk: Understanding transferability across arenavirus systems

Gregory Milne, Christl Ann Donnelly, Herwig Leirs, Lauren A. Attfield et al.
Proceedings of the National Academy of Sciences
Viral Infections and Outbreaks Research
article

Climate-driven host ecology as a framework for zoonotic disease risk: Understanding transferability across arenavirus systems

Gregory Milne, Christl Ann Donnelly, Herwig Leirs, Lauren A. Attfield, David W. Redding, Kate E. Jones, Lucinda Kirkpatrick, Joachim Mariën
article en

Abstract

Mechanistic frameworks linking climate to zoonotic disease risk through host ecology remain rare, limiting transferable insights across systems. We develop a Bayesian framework combining an integral projection model of rodent demography with a compartmental disease model. Applied to capture-mark-recapture data from the Natal multimammate mouse ( Mastomys natalensis ; N = 20,249 captures, 1994–2023) and serological data on the Lassa virus-related Morogoro arenavirus ( N = 7,850 tests, 2010–2017), the framework jointly estimates climatic, demographic, and transmission parameters. Rainfall was a dominant driver of rodent recruitment, with seasonal rainfall explaining 52.1% (95% CrI 2.1 to 79.0%) of modeled recruitment variation. In a field-first, we estimate that 79.1% (95% CrI 69.3 to 88.9%) of infected pregnancies result in vertical transmission, identifying this as the primary mechanism maintaining viral persistence between breeding seasons. We assess framework transferability to capture the seasonal dynamics of Lassa fever outbreaks in Nigeria ( N = 6,469 laboratory-confirmed cases, 2018–2025), substituting model climate inputs without refitting any parameters. Predicted peaks in rodent subadult infections preceded observed outbreaks by 0.92 mo (95% CrI −2.76 to 0.92), with 83% of predicted and observed peaks falling within ±28 d [Pr(Δ ≤ 28d) = 0.83], substantially outperforming seasonal rainfall or rodent demography [Pr(Δ ≤ 28d) ≤ 0.11]. Infected adult peaks lagged observed outbreaks by 0.92 mo [Pr(Δ ≤ 28d) = 0.56], suggesting subadults might primarily be responsible for zoonotic hazard. Outbreak magnitude was not reproduced, likely reflecting human behavioral and surveillance factors beyond the model’s scope. These results illustrate how mechanistic frameworks grounded in reservoir host ecology can yield transferable insights into zoonotic risk, with potential application across other climate-sensitive host–pathogen systems.

Proceedings of the National Academy of SciencesVol. 123(39)
University of Antwerp (BE), Bangor University (GB), Leverhulme Trust (GB), University of Oxford (GB), Ecology and Ecosystem Health (FR), University College London (GB), Imperial College London (GB), Instituut voor Tropische Geneeskunde (BE)
Climate action
Openalex Percentile: Top 12%
Viral Infections and Outbreaks Research
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