The distribution of the time taken for an epidemic to spread between two communities

Yan, Ada W.C., Black, Andrew J., McCaw, James M., Rebuli, Nicolas, Ross, Joshua V., Swan, Annalisa J., and Hickson, Roslyn I. (2018) The distribution of the time taken for an epidemic to spread between two communities. Mathematical Biosciences, 303. pp. 139-147.

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Abstract

Assessing the risk of disease spread between communities is important in our highly connected modern world. However, the impact of disease- and population-specific factors on the time taken for an epidemic to spread between communities, as well as the impact of stochastic disease dynamics on this spreading time, are not well understood. In this study, we model the spread of an acute infection between two communities ('patches') using a susceptible-infectious-removed (SIR) metapopulation model. We develop approximations to efficiently evaluate the probability of a major outbreak in a second patch given disease introduction in a source patch, and the distribution of the time taken for this to occur. We use these approximations to assess how interventions, which either control disease spread within a patch or decrease the travel rate between patches, change the spreading probability and median spreading time.We find that decreasing the basic reproduction number in the source patch is the most effective way of both decreasing the spreading probability, and delaying epidemic spread to the second patch should this occur. Moreover, we show that the qualitative effects of interventions are the same regardless of the approximations used to evaluate the spreading time distribution, but for some regions in parameter space, quantitative findings depend upon the approximations used. Importantly, if we neglect the possibility that an intervention prevents a large outbreak in the source patch altogether, then intervention effectiveness is not estimated accurately.

Item ID: 64031
Item Type: Article (Research - C1)
ISSN: 1879-3134
Copyright Information: © 2018 Elsevier Inc. All rights reserved.
Funders: ACS Foundation Scholarship, Australian Government Research Training Program Scholarship, Australian Research Council (ARC), Australian Research Council (ARC), National Health and Medical Research Centre of Australia Centre for Research Excellence Policy Relevant Infectious Disease Simulation and Mathematical Modelling (NHMRC)
Projects and Grants: DE160100690, FT130100254, NHMRC 1078068
Date Deposited: 18 Aug 2020 00:28
FoR Codes: 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490102 Biological mathematics @ 33%
49 MATHEMATICAL SCIENCES > 4905 Statistics > 490510 Stochastic analysis and modelling @ 34%
42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 33%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 50%
92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920404 Disease Distribution and Transmission (incl. Surveillance and Response) @ 50%
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