Pieter Trapman
Inferring R0 in emerging epidemics: the effect of common population structure is small
Trapman, Pieter; Ball, Frank; Dhersin, Jean-St�phane; Tran, Viet Chi; Wallinga, Jacco; Britton, Tom
Authors
FRANK BALL frank.ball@nottingham.ac.uk
Professor of Applied Probability
Jean-St�phane Dhersin
Viet Chi Tran
Jacco Wallinga
Tom Britton
Abstract
When controlling an emerging outbreak of an infectious disease, it is essential to know the key epidemiological parameters, such as the basic reproduction number R0 and the control effort required to prevent a large outbreak. These parameters are estimated from the observed incidence of new cases and information about the infectious contact structures of the population in which the disease spreads. However, the relevant infectious contact structures for new, emerging infections are often unknown or hard to obtain. Here, we show that, for many common true underlying heterogeneous contact structures, the simplification to neglect such structures and instead assume that all contacts are made homogeneously in the whole population results in conservative estimates for R0 and the required control effort. This means that robust control policies can be planned during the early stages of an outbreak, using such conservative estimates of the required control effort.
Citation
Trapman, P., Ball, F., Dhersin, J., Tran, V. C., Wallinga, J., & Britton, T. (2016). Inferring R0 in emerging epidemics: the effect of common population structure is small. Interface, 13(121), 1-9. https://doi.org/10.1098/rsif.2016.0288
Journal Article Type | Article |
---|---|
Acceptance Date | Aug 1, 2016 |
Online Publication Date | Aug 1, 2016 |
Publication Date | Aug 31, 2016 |
Deposit Date | Feb 10, 2017 |
Publicly Available Date | Mar 28, 2024 |
Journal | Journal of the Royal Society Interface |
Electronic ISSN | 1742-5689 |
Publisher | The Royal Society |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Issue | 121 |
Article Number | 20160288 |
Pages | 1-9 |
DOI | https://doi.org/10.1098/rsif.2016.0288 |
Keywords | Infectious disease modelling, Emerging epidemics, Population Structure, Real-time spread, R0 |
Public URL | https://nottingham-repository.worktribe.com/output/803877 |
Publisher URL | http://dx.doi.org/10.1098/rsif.2016.0288 |
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
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