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Risk scorecard to minimize impact of COVID-19 when reopening

BACKGROUND: We present a novel approach for exiting coronavirus disease 2019 (COVID-19) lockdowns using a ‘risk scorecard’ to prioritize activities to resume whilst allowing safe reopening. METHODS: We modelled cases generated in the community/week, incorporating parameters for social distancing, co...

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Autores principales: Lim, Shin B, Pung, Rachael, Tan, Kellie, Lang, Jocelyn H S, Yong, Dominique Z X, Teh, Shi-Hua, Quah, Elizabeth, Sun, Yinxiaohe, Ma, Stefan, Lee, Vernon J M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420627/
https://www.ncbi.nlm.nih.gov/pubmed/34318330
http://dx.doi.org/10.1093/jtm/taab113
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author Lim, Shin B
Pung, Rachael
Tan, Kellie
Lang, Jocelyn H S
Yong, Dominique Z X
Teh, Shi-Hua
Quah, Elizabeth
Sun, Yinxiaohe
Ma, Stefan
Lee, Vernon J M
author_facet Lim, Shin B
Pung, Rachael
Tan, Kellie
Lang, Jocelyn H S
Yong, Dominique Z X
Teh, Shi-Hua
Quah, Elizabeth
Sun, Yinxiaohe
Ma, Stefan
Lee, Vernon J M
author_sort Lim, Shin B
collection PubMed
description BACKGROUND: We present a novel approach for exiting coronavirus disease 2019 (COVID-19) lockdowns using a ‘risk scorecard’ to prioritize activities to resume whilst allowing safe reopening. METHODS: We modelled cases generated in the community/week, incorporating parameters for social distancing, contact tracing and imported cases. We set thresholds for cases and analysed the effect of varying parameters. An online tool to facilitate country-specific use including the modification of parameters (https://sshsphdemos.shinyapps.io/covid_riskbudget/) enables visualization of effects of parameter changes and trade-offs. Local outbreak investigation data from Singapore illustrate this. RESULTS: Setting a threshold of 0.9 mean number of secondary cases arising from a case to keep R < 1, we showed that opening all activities excluding high-risk ones (e.g. nightclubs) allows cases to remain within threshold; while opening high-risk activities would exceed the threshold and result in escalating cases. An 80% reduction in imported cases per week (141 to 29) reduced steady-state cases by 30% (295 to 205). One-off surges in cases (due to superspreading) had no effect on the steady state if the R remains <1. Increasing the effectiveness of contact tracing (probability of a community case being isolated when infectious) by 33% (0.6 to 0.8) reduced cases by 22% (295 to 231). Cases grew exponentially if the product of the mean number of secondary cases arising from a case and (1—probability of case being isolated) was >1. CONCLUSIONS: Countries can utilize a ‘risk scorecard’ to balance relaxations for travel and domestic activity depending on factors that reduce disease impact, including hospital/ICU capacity, contact tracing, quarantine and vaccination. The tool enabled visualization of the combinations of imported cases and activity levels on the case numbers and the trade-offs required. For vaccination, a reduction factor should be applied both for likelihood of an infected case being present and a close contact getting infected.
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spelling pubmed-84206272021-09-10 Risk scorecard to minimize impact of COVID-19 when reopening Lim, Shin B Pung, Rachael Tan, Kellie Lang, Jocelyn H S Yong, Dominique Z X Teh, Shi-Hua Quah, Elizabeth Sun, Yinxiaohe Ma, Stefan Lee, Vernon J M J Travel Med Original Article BACKGROUND: We present a novel approach for exiting coronavirus disease 2019 (COVID-19) lockdowns using a ‘risk scorecard’ to prioritize activities to resume whilst allowing safe reopening. METHODS: We modelled cases generated in the community/week, incorporating parameters for social distancing, contact tracing and imported cases. We set thresholds for cases and analysed the effect of varying parameters. An online tool to facilitate country-specific use including the modification of parameters (https://sshsphdemos.shinyapps.io/covid_riskbudget/) enables visualization of effects of parameter changes and trade-offs. Local outbreak investigation data from Singapore illustrate this. RESULTS: Setting a threshold of 0.9 mean number of secondary cases arising from a case to keep R < 1, we showed that opening all activities excluding high-risk ones (e.g. nightclubs) allows cases to remain within threshold; while opening high-risk activities would exceed the threshold and result in escalating cases. An 80% reduction in imported cases per week (141 to 29) reduced steady-state cases by 30% (295 to 205). One-off surges in cases (due to superspreading) had no effect on the steady state if the R remains <1. Increasing the effectiveness of contact tracing (probability of a community case being isolated when infectious) by 33% (0.6 to 0.8) reduced cases by 22% (295 to 231). Cases grew exponentially if the product of the mean number of secondary cases arising from a case and (1—probability of case being isolated) was >1. CONCLUSIONS: Countries can utilize a ‘risk scorecard’ to balance relaxations for travel and domestic activity depending on factors that reduce disease impact, including hospital/ICU capacity, contact tracing, quarantine and vaccination. The tool enabled visualization of the combinations of imported cases and activity levels on the case numbers and the trade-offs required. For vaccination, a reduction factor should be applied both for likelihood of an infected case being present and a close contact getting infected. Oxford University Press 2021-07-23 /pmc/articles/PMC8420627/ /pubmed/34318330 http://dx.doi.org/10.1093/jtm/taab113 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of International Society of Travel Medicine. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Lim, Shin B
Pung, Rachael
Tan, Kellie
Lang, Jocelyn H S
Yong, Dominique Z X
Teh, Shi-Hua
Quah, Elizabeth
Sun, Yinxiaohe
Ma, Stefan
Lee, Vernon J M
Risk scorecard to minimize impact of COVID-19 when reopening
title Risk scorecard to minimize impact of COVID-19 when reopening
title_full Risk scorecard to minimize impact of COVID-19 when reopening
title_fullStr Risk scorecard to minimize impact of COVID-19 when reopening
title_full_unstemmed Risk scorecard to minimize impact of COVID-19 when reopening
title_short Risk scorecard to minimize impact of COVID-19 when reopening
title_sort risk scorecard to minimize impact of covid-19 when reopening
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420627/
https://www.ncbi.nlm.nih.gov/pubmed/34318330
http://dx.doi.org/10.1093/jtm/taab113
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