TY - JOUR
T1 - Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers
AU - Axelsen, Jacob Bock
AU - Yaari, Rami
AU - Grenfell, Bryan T.
AU - Stone, Lewi
PY - 2014/7/1
Y1 - 2014/7/1
N2 - 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.
AB - 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.
KW - Bayesian epidemic model
KW - Climate
KW - Infectious disease
KW - Model forecasting
KW - Predictive model
UR - http://www.scopus.com/inward/record.url?scp=84903727051&partnerID=8YFLogxK
U2 - 10.1073/pnas.1321656111
DO - 10.1073/pnas.1321656111
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AN - SCOPUS:84903727051
SN - 0027-8424
VL - 111
SP - 9538
EP - 9542
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 26
ER -