Forecasting influenza in Europe using a metapopulation model incorporating cross-border commuting and air travel

Past work has shown that models incorporating human travel can improve the quality of influenza forecasts. Here, we develop and validate a metapopulation model of twelve European countries, in which international translocation of virus is driven by observed commuting and air travel flows, and use th...

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Bibliographic Details
Published in:PLoS computational biology 2020-10, Vol.16 (10), p.e1008233
Main Authors: Kramer, Sarah C, Pei, Sen, Shaman, Jeffrey
Format: Article
Language:English
Subjects:
Accuracy
Air transportation
Air Travel
Aircraft
Commuting
Computational Biology
Computer and Information Sciences
Disease Outbreaks - statistics & numerical data
Distribution
Earth Sciences
Engineering and Technology
Environmental health
Epidemics
Europe
Forecasting
Forecasts and trends
Health aspects
Health sciences
Humans
Humidity
Influenza
Influenza research
Influenza viruses
Influenza, Human - epidemiology
Influenza, Human - transmission
Mathematical models
Medicine and Health Sciences
Metapopulations
Models, Statistical
Pandemics
People and Places
Physical Sciences
Population geography
Public health
Research and Analysis Methods
Seasons
Sentinel health events
Social Sciences
Surveillance systems
Translocation
Travel
Viruses
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Summary:Past work has shown that models incorporating human travel can improve the quality of influenza forecasts. Here, we develop and validate a metapopulation model of twelve European countries, in which international translocation of virus is driven by observed commuting and air travel flows, and use this model to generate influenza forecasts in conjunction with incidence data from the World Health Organization. We find that, although the metapopulation model fits the data well, it offers no improvement over isolated models in forecast quality. We discuss several potential reasons for these results. In particular, we note the need for data that are more comparable from country to country, and offer suggestions as to how surveillance systems might be improved to achieve this goal.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1008233