title: Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.
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-to-year 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.
authors: Biomathematics Unit, Department of Zoology, Faculty of Life Science, and.
authors: Jacob Bock
authors: JB
authors: Axelsen
authors: Biomathematics Unit, Department of Zoology, Faculty of Life Science, andPorter School of Environmental Studies, Tel Aviv University, Ramat Aviv 69978, Israel;
authors: Rami
authors: R
authors: Yaari
authors: Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08544;Fogarty International Center, National Institutes of Health, Bethesda, MD 20892-2220; and.
authors: Bryan T
authors: BT
authors: Grenfell
authors: Biomathematics Unit, Department of Zoology, Faculty of Life Science, andSchool of Mathematical and Geospatial Sciences, RMIT University, Melbourne, VIC 3001, Australia lewistone2@gmail.com.
authors: Lewi
authors: L
authors: Stone
mesh_terms: D001499:Bayes Theorem; D005075:Biological Evolution; D002980:Climate; D000939:Epitopes / Q000235:genetics; D005544:Forecasting / Q000379:methods; D006801:Humans; D015994:Incidence; D009980:Influenza A virus / Q000235:genetics* / Q000276:immunology; D007251:Influenza, Human / Q000453:epidemiology*; D007557:Israel / Q000453:epidemiology; D016013:Likelihood Functions; D008954:Models, Biological; D012621:Seasons
chemical_list: D000939:Epitopes
keywords: Bayesian epidemic model; climate; infectious disease; model forecasting; predictive model