Exploiting routinely collected severe case data to monitor and predict influenza outbreaks.

Corbella, Alice; Zhang, Xu-Sheng; Birrell, Paul; Boddington, Nicki; Pebody, Richard G; Presanis, Anne; De Angelis, Daniela

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Authors

Corbella, Alice

Zhang, Xu-Sheng

Birrell, Paul

Boddington, Nicki

Pebody, Richard G

Presanis, Anne

De Angelis, Daniela

Publication Date

2018-06-26

Journal Title

BMC public health

ISSN

1471-2458

Volume

Issue

Pages

790

Language

eng

Type

Article

Physical Medium

Electronic

Metadata

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Citation

Corbella, A., Zhang, X., Birrell, P., Boddington, N., Pebody, R. G., Presanis, A., & De Angelis, D. (2018). Exploiting routinely collected severe case data to monitor and predict influenza outbreaks.. BMC public health, 18 (1), 790. https://doi.org/10.1186/s12889-018-5671-7

Keywords

Humans, Hospitalization, Severity of Illness Index, Population Surveillance, Models, Statistical, Bayes Theorem, Retrospective Studies, Seasons, Disease Outbreaks, Forecasting, Schools, Holidays, England, Influenza, Human

Identifiers

External DOI: https://doi.org/10.1186/s12889-018-5671-7

This record's URL: https://www.repository.cam.ac.uk/handle/1810/284124

Rights

Attribution 4.0 International

Licence URL: https://creativecommons.org/licenses/by/4.0/

Except where otherwise noted, this item's licence is described as Attribution 4.0 International