Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers

Jacob Bock Axelsen, Rami Yaari, Bryan T. Grenfell, Lewi Stone*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

76 Scopus citations

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 languageEnglish
Pages (from-to)9538-9542
Number of pages5
JournalProceedings of the National Academy of Sciences of the United States of America
Volume111
Issue number26
DOIs
StatePublished - 1 Jul 2014

Funding

FundersFunder number
Bill and Melinda Gates Foundation
Fogarty International Center
National Institutes of Health
National Institute of Child Health and Human DevelopmentR24HD047879

    Keywords

    • Bayesian epidemic model
    • Climate
    • Infectious disease
    • Model forecasting
    • Predictive model

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