Climate-driven rodent infection dynamics align with Lassa fever seasonality in humans
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Lassa fever (LF), caused by Lassa mammarenavirus (LASV), imposes a major public health burden in West Africa. The Natal multimammate mouse ( Mastomys natalensis , MN) is the principal reservoir, yet the extent to which host dynamics shape human outbreaks remains unclear. Leveraging long-term MN capture-mark-recapture data from Tanzania ( N =20,249 captures, 1994–2023) and daily climate records, we quantify the demographic and climatic drivers of MN population dynamics. Using serological data on the LASV-related Morogoro arenavirus ( N =7,850 tests, 2010–2017), we parameterize a Bayesian population model to estimate that 79.1% (95% CrI 69.3–88.9%) of infected pregnancies result in vertical transmission. Rainfall was the strongest predictor of rodent recruitment and subsequent spikes in arenavirus exposure through both vertical and horizontal transmission. When recalibrated to the Nigerian climate, our model predicted the approximate timing of LF outbreaks from 2018–2025 ( N =6469 laboratory-confirmed cases), with predicted peaks occurring on average 0.92 months (95% CrI 0– 2.8) after observed outbreaks. These findings link climate-driven rodent demography to human LF dynamics while suggesting some generalizability between rodent-arenavirus systems. Our results provide a framework for understanding the drivers of rodent host population dynamics that, in turn, shape the temporal and spatial patterns of human zoonotic disease risk.
Significance Statement
Lassa fever (LF), caused by Lassa mammarenavirus, remains a major public health threat in West Africa. Since human infections arise as spillovers from the Natal multimammate mouse ( Mastomys natalensis , MN), understanding rodent demography may clarify patterns of human risk. Using long-term data on MN populations, arenavirus exposure, and climate from Tanzania, we show that rainfall strongly predicts rodent recruitment and arenavirus exposure, with an estimated 79% of infected pregnancies resulting in vertical transmission. When recalibrated to the Nigerian climate, predicted peaks in infected rodents closely aligned with annual LF outbreaks. These results highlight how demographic and climatic factors drive rodent populations and may, in turn, shape the timing of zoonotic disease risk.
