Dr. Gregory Milne, a postdoctoral researcher at the Natural History Museum who co-led the study, said: "The planetary emergency is changing the conditions in which people, wildlife and pathogens interact. To understand what that means for human health, we need to understand the ecological processes connecting environmental change to disease."

He added that when the team applied the model to Nigeria, "the timing of peaks in infected rodents closely matched the seasonal timing of human Lassa fever outbreaks."

How well did the model work in Nigeria?

The researchers faced an interesting test. Tanzania, where the model was built, has the mouse but no Lassa fever. Nigeria has both. Could a model trained in one country explain outbreaks in another?

Using climate data from five Nigerian states, the team compared model predictions against more than 6,000 confirmed Lassa fever cases recorded by the Nigeria Centre for Disease Control and Prevention between 2018 and 2025.

The results were encouraging but bounded:

• Peaks in infected young rodents tended to occur roughly a month before peaks in human cases.
• In 83% of comparisons, the predicted rodent peak and the observed human peak were within 28 days of each other.
• The model predicted timing, not size — outbreak scale likely depends on other factors such as human behavior, contact with rodents, and disease surveillance.

Kate Jones, director of the UCL People and Nature Lab, said: "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."

How does the virus survive between seasons?

The study also uncovered a mechanism that keeps Lassa virus circulating: transmission from mother to offspring. The model estimated that almost 80% of infected rodent pregnancies passed the virus on this way, allowing it to persist between breeding seasons.

What are the limits — and the wider applications?

The results are preliminary in one important sense: the model forecasts when risk rises, not how many people will fall ill. Outbreak size depends heavily on factors the model does not capture, including human behavior and the strength of local disease surveillance.

Still, the approach goes beyond spotting correlations between climate and human cases. It examines the ecological processes connecting them, which means future climate projections could feed into estimates of how environmental conditions will alter wildlife populations, pathogen transmission, and zoonotic risk.

The framework could also travel beyond Lassa fever. Rodents host more zoonotic pathogens than any other group of mammals and respond rapidly to environmental change, making them a natural test case. Similar models could probe other climate-sensitive host-pathogen systems, especially in regions where human disease data are scarce.

The study forms part of wider research by the Natural History Museum and UCL into how environmental change affects biodiversity and, through it, risks to human health. As Milne put it, understanding how environmental change affects wildlife populations "could help scientists and public health authorities identify periods of heightened risk."