
New Climate Model May Help Predict Influenza Outbreaks Worldwide
Key Takeaways
- A unified, nonlinear humidity–temperature transmission curve reconciles winter-peaked temperate epidemics with year-round or bimodal tropical influenza patterns across North and South America.
- Influenza risk increases at both low specific humidity and at high specific humidity with warm temperatures, while colder temperatures consistently elevate transmission probability.
Because influenza outbreaks follow a humidity‑temperature curve, climate change may shift flu epidemics and reshape risk from tropics to temperate regions.
For decades, scientists have struggled to explain why influenza behaves so differently depending on where in the world it strikes. In temperate climates, flu arrives each winter and produces sharp, short-lived epidemics. In tropical regions, transmission tends to occur year-round, sometimes flaring twice annually instead of once.1,2
A new study published in PNAS Nexus offers a unifying explanation, including a single, nonlinear relationship between specific humidity and temperature that appears to govern flu transmission everywhere, regardless of latitude.1,2
Modeling Outbreaks Across the Americas
Researchers from Brown University, Princeton University, McGill University, and the University of California, Berkeley, built a mechanistic susceptible-infected-recovered-susceptible model using influenza surveillance data from 81 locations across North and South America, spanning tropical, subtropical, and temperate climates. Rather than treating tropical and temperate outbreaks as separate phenomena, the team tested whether one climate-driven transmission curve could explain both.1
The result was a U-shaped relationship between specific humidity and transmission risk, with low humidity (as seen in temperate winters) and, at the opposite end, high humidity paired with warm temperatures (as seen in some tropical climates), both of which were associated with elevated transmission. Temperature further modulated this effect, with colder conditions consistently boosting transmission risk.1,2
According to the study's senior author, this combined climate signal was able to recreate the wintertime peaks characteristic of United States and Canadian flu seasons as well as the more dispersed, sometimes bimodal outbreaks observed in countries like Nicaragua, Costa Rica, and Brazil.1,2
Implications for a Changing Climate
The investigators also used the model to project how flu activity might shift under future climate scenarios drawn from Coupled Model Intercomparison Project Phase 6 data. Their simulations suggest that by the century's end, many temperate regions could see modest declines in peak outbreak size as humidity rises, while several tropical regions could experience increased outbreak intensity. This divergence carries real consequences for health systems already managing substantial seasonal flu burden; CDC estimates that flu has caused between 9.4 million and 51 million illnesses and up to 710,000 hospitalizations annually in the US since 2010.1-3
What This Means for Pharmacists
Although the model is primarily a forecasting and public health planning tool, it carries practical relevance for community and health-system pharmacists. More precise, climate-informed seasonal forecasting could eventually help refine the timing of vaccination campaigns, particularly in subtropical and tropical US territories or international markets where flu activity doesn't follow the familiar fall-winter pattern. Pharmacists who work in or supply patients in less temperate climates may want to remain attentive to evolving guidance on optimal vaccination windows as this research matures.4
Looking Ahead
The study authors note that their model does not account for evolving factors such as vaccine uptake, viral strain evolution, or population mobility, all of which influence year-to-year flu severity independent of climate. Regardless, the study represents one of the first attempts to mechanistically link a single climate-transmission framework to flu dynamics across an entire hemisphere, and the authors suggest similar approaches could eventually be applied to other seasonal respiratory viruses.1,2










































































































