Please use this identifier to cite or link to this item: https://doi.org/10.1093/jtm/taab113
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dc.titleRisk scorecard to minimize impact of COVID-19 when reopening
dc.contributor.authorLim, Shin B.
dc.contributor.authorPung, Rachael
dc.contributor.authorTan, Kellie
dc.contributor.authorLang, Jocelyn H. S.
dc.contributor.authorYong, Dominique Z. X.
dc.contributor.authorTeh, Shi-Hua
dc.contributor.authorQuah, Elizabeth
dc.contributor.authorSun, Yinxiaohe
dc.contributor.authorMa, Stefan
dc.contributor.authorLee, Vernon J. M.
dc.date.accessioned2022-10-13T01:17:53Z
dc.date.available2022-10-13T01:17:53Z
dc.date.issued2021-07-23
dc.identifier.citationLim, 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. (2021-07-23). Risk scorecard to minimize impact of COVID-19 when reopening. Journal of travel medicine 28 (7). ScholarBank@NUS Repository. https://doi.org/10.1093/jtm/taab113
dc.identifier.issn1708-8305
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/232900
dc.description.abstractBACKGROUND: 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. © International Society of Travel Medicine 2021. Published by Oxford University Press.
dc.publisherNLM (Medline)
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2021
dc.subjectcontact tracing
dc.subjectimported cases
dc.subjectinfectious diseases
dc.subjectquarantine
dc.subjectSARS-CoV-2
dc.subjectsocial distancing
dc.subjecttraveller testing
dc.typeArticle
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.doi10.1093/jtm/taab113
dc.description.sourcetitleJournal of travel medicine
dc.description.volume28
dc.description.issue7
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