Tanzanian mouse and rainfall records predict the timing of Nigeria's Lassa fever peaks

The best thing about this study is how it was tested. As the team describes it, the model rests on almost 30 years of University of Antwerp records: more than 20,000 Tanzanian rodent captures, paired with climate and pathogen exposure data ^[2][5]. The Nigerian cases came in only as a test ^[8]. That removes the cheapest way for a disease model to look good, which is to tune it on the same outbreaks it is later scored against. The work is published in the Proceedings of the National Academy of Sciences ^[1].

In the model, rain matters because of breeding. According to the team, wetter conditions likely raise the food supply and stimulate breeding ^[5]. The 2015-2016 El Nino was the clearest case. Unusually heavy rain in East Africa coincided with a predicted rise in young rodents, followed by an increase in infected animals ^[12]. The rise in young rodents there was the model's output, not a field count ^[12].

"When we applied the model to Nigeria, the timing of peaks in infected rodents closely matched the seasonal timing of human Lassa fever outbreaks," said Gregory Milne, a Natural History Museum postdoctoral researcher who co-led the study ^[6]. Infected young rodents tended to peak around a month before human cases ^[9]. Seen from the other side, the 83% match rate means 17% of comparisons missed by more than 28 days ^[1]. That tolerance is nearly as wide as the lead itself. For a disease with a regular season, the obvious control is a calendar forecast that names the same peak month every year. The thing this doesn't tell you is how the model scores against that baseline, or how many comparisons sit behind the 83% across five states and eight years of records ^[2].

Outbreak size is out of reach. The team reports that the model could often predict the timing of outbreaks but not their size, and says size likely depends on human behavior, contact with rodents and disease surveillance ^[13]. People catch Lassa through contact with infected rodents, or with food and household items contaminated by their urine or feces, and severe cases can be fatal ^[4]. "Climate alone cannot predict the size of an outbreak, but understanding the ecological processes connecting environmental conditions, wildlife populations and pathogens could help identify periods when the risk of spillover is higher," said Kate Jones, director of the UCL People and Nature Lab ^[14].

In my view the evidence supports a seasonal timing tool with a lead of about a month from rodent peak to human peak ^[9]. Its record so far is retrospective. The model was scored against Nigerian cases already recorded between 2018 and 2025 ^[8].