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Synergistic interventions to control COVID-19 : mass testing and isolation mitigates reliance on distancing
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Howerton, Emily, Ferrari, Matthew J., Bjørnstad, Ottar N., Bogich, Tiffany L., Borchering, Rebecca K., Jewell, Chris P., Nichols, James D., Probert, William J. M. , Runge, Michael C., Tildesley, Michael J., Viboud, Cécile and Shea, Katriona (2021) Synergistic interventions to control COVID-19 : mass testing and isolation mitigates reliance on distancing. PLOS Computational Biology, 17 (10). e1009518. doi:10.1371/journal.pcbi.1009518
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WRAP-interventions-control-COVID-19-mass-testing-isolation-mitigates-reliance-distancing-2021.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Public Domain Dedication. Download (1490Kb) | Preview |
Official URL: https://doi.org/10.1371/journal.pcbi.1009518
Abstract
Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.
| 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- ) Faculty of Science, Engineering and Medicine > Science > Mathematics |
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| SWORD Depositor: | Library Publications Router | |||||||||||||||||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | COVID-19 (Disease), COVID-19 (Disease) -- Prevention , COVID-19 (Disease) -- Transmission, Social distancing (Public health), Quarantine , Social distancing (Public health) -- Mathematical models, Quarantine -- Mathematical models | |||||||||||||||||||||||||||||||||
| Journal or Publication Title: | PLOS Computational Biology | |||||||||||||||||||||||||||||||||
| Publisher: | Public Library of Science | |||||||||||||||||||||||||||||||||
| ISSN: | 1553-7358 | |||||||||||||||||||||||||||||||||
| Official Date: | 28 October 2021 | |||||||||||||||||||||||||||||||||
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| Volume: | 17 | |||||||||||||||||||||||||||||||||
| Number: | 10 | |||||||||||||||||||||||||||||||||
| Article Number: | e1009518 | |||||||||||||||||||||||||||||||||
| DOI: | 10.1371/journal.pcbi.1009518 | |||||||||||||||||||||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||||||||||||||||||||
| Publication Status: | Published | |||||||||||||||||||||||||||||||||
| Reuse Statement (publisher, data, author rights): | https://creativecommons.org/publicdomain/zero/1.0/ | |||||||||||||||||||||||||||||||||
| Access rights to Published version: | Open Access | |||||||||||||||||||||||||||||||||
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