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Real-time decision-making during emergency disease outbreaks
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Koelle, Katia, Probert, William J. M. , Jewell, Chris P., Werkman, Marleen, Fonnesbeck, Christopher J., Goto, Yoshitaka, Runge, Michael C., Sekiguchi, Satoshi, Shea, Katriona, Keeling, Matthew James, Ferrari, Matthew J. and Tildesley, Michael J. (2018) Real-time decision-making during emergency disease outbreaks. PLoS Computational Biology, 14 (7). e1006202. doi:10.1371/journal.pcbi.1006202 ISSN 1553-7358.
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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1006202
Abstract
In the event of a new infectious disease outbreak, mathematical and simulation models are commonly used to inform policy by evaluating which control strategies will minimize the impact of the epidemic. In the early stages of such outbreaks, substantial parameter uncertainty may limit the ability of models to provide accurate predictions, and policymakers do not have the luxury of waiting for data to alleviate this state of uncertainty. For policymakers, however, it is the selection of the optimal control intervention in the face of uncertainty, rather than accuracy of model predictions, that is the measure of success that counts. We simulate the process of real-time decision-making by fitting an epidemic model to observed, spatially-explicit, infection data at weekly intervals throughout two historical outbreaks of foot-and-mouth disease, UK in 2001 and Miyazaki, Japan in 2010, and compare forward simulations of the impact of switching to an alternative control intervention at the time point in question. These are compared to policy recommendations generated in hindsight using data from the entire outbreak, thereby comparing the best we could have done at the time with the best we could have done in retrospect.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | R Medicine > RA Public aspects of medicine | |||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Epidemics -- Transmission -- Mathematical models, Communicable diseases -- Transmission -- Mathematical models, Decision making -- Mathematical models | |||||||||||||||
Journal or Publication Title: | PLoS Computational Biology | |||||||||||||||
Publisher: | Public Library of Science | |||||||||||||||
ISSN: | 1553-7358 | |||||||||||||||
Official Date: | 24 July 2018 | |||||||||||||||
Dates: |
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Volume: | 14 | |||||||||||||||
Number: | 7 | |||||||||||||||
Article Number: | e1006202 | |||||||||||||||
DOI: | 10.1371/journal.pcbi.1006202 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
RIOXX Funder/Project Grant: |
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