Development and validation of influenza forecasting for 64 temperate and tropical countries

PLoS Computational Biology
Sarah C Kramer, Jeffrey Shaman

Abstract

Accurate forecasts of influenza incidence can be used to inform medical and public health decision-making and response efforts. However, forecasting systems are uncommon in most countries, with a few notable exceptions. Here we use publicly available data from the World Health Organization to generate retrospective forecasts of influenza peak timing and peak intensity for 64 countries, including 18 tropical and subtropical countries. We find that accurate and well-calibrated forecasts can be generated for countries in temperate regions, with peak timing and intensity accuracy exceeding 50% at four and two weeks prior to the predicted epidemic peak, respectively. Forecasts are significantly less accurate in the tropics and subtropics for both peak timing and intensity. This work indicates that, in temperate regions around the world, forecasts can be generated with sufficient lead time to prepare for upcoming outbreak peak incidence.

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Citations

May 24, 2020·Influenza and Other Respiratory Viruses·Aaron L WeinmanSteven Y C Tong
Feb 26, 2020·Influenza and Other Respiratory Viruses·Matthew BiggerstaffJoseph T Wu
Oct 30, 2020·Environmental Science and Pollution Research International·Abu Reza Md Towfiqul IslamSaleemul Huq
Mar 25, 2021·International Journal of Biometeorology·Pablo Fdez-ArróyabeAna Santurtún Zarrabeitia
Sep 27, 2020·American Journal of Human Biology : the Official Journal of the Human Biology Council·James Holland JonesZack Almquist
Jun 10, 2021·PLoS Computational Biology·Haokun YuanWan Yang
Mar 25, 2019·Journal of Biomedical Informatics·Shanen ChenXiaojian Liu
Dec 25, 2021·PeerJ·Matthieu Domenech de CellèsLulla Opatowski
Jan 13, 2022·Proceedings. Biological Sciences·Matthieu Domenech de CellèsSarah C Kramer

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Software Mentioned

Global Land Data Assimilation System ( GLDAS )
FluID
FluNet

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