Abstract
Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-toyear variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.
| Original language | English |
|---|---|
| Pages (from-to) | 9538-9542 |
| Number of pages | 5 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 111 |
| Issue number | 26 |
| DOIs | |
| State | Published - 1 Jul 2014 |
Funding
| Funders | Funder number |
|---|---|
| Bill and Melinda Gates Foundation | |
| Fogarty International Center | |
| National Institutes of Health | |
| National Institute of Child Health and Human Development | R24HD047879 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Bayesian epidemic model
- Climate
- Infectious disease
- Model forecasting
- Predictive model
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