Modeling the impact of surveillance activities combined with physical distancing interventions on COVID-19 epidemics at a local level

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• dc.contributor.author Chen, Guan-Jhou
• dc.contributor.author Palmer, John R. B.
• dc.contributor.author Bartumeus, Frederic
• dc.contributor.author Alba-Casals, Ana
• dc.date.accessioned 2023-07-18T06:35:55Z
• dc.date.available 2023-07-18T06:35:55Z
• dc.date.issued 2022
• dc.description.abstract Physical distancing and contact tracing are two key components in controlling the COVID-19 epidemics. Understanding their interaction at local level is important for policymakers. We propose a flexible modeling framework to assess the effect of combining contact tracing with different physical distancing strategies. Using scenario tree analyses, we compute the probability of COVID-19 detection using passive surveillance, with and without contact tracing, in metropolitan Barcelona. The estimates of detection probability and the frequency of daily social contacts are fitted into an age-structured susceptible-exposed-infectious-recovered compartmental model to simulate the epidemics considering different physical distancing scenarios over a period of 26 weeks. With the original Wuhan strain, the probability of detecting an infected individual without implementing physical distancing would have been 0.465, 0.515, 0.617, and 0.665 in designated age groups (0–14, 15–49, 50–64, and >65), respectively. As the physical distancing measures were reinforced and the disease circulation decreased, the interaction between the two interventions resulted in a reduction of the detection probabilities; however, despite this reduction, active contact tracing and isolation remained an effective supplement to physical distancing. If we relied solely on passive surveillance for diagnosing COVID-19, the model required a minimal 50% (95% credible interval, 39–69%) reduction of daily social contacts to keep the infected population under 5%, as compared to the 36% (95% credible interval, 22–56%) reduction with contact tracing systems. The simulation with the B.1.1.7 and B.1.167.2 strains shows similar results. Our simulations showed that a functioning contact tracing program would reduce the need for physical distancing and mitigate the COVID-19 epidemics.
• dc.description.sponsorship F.B. and J.R.B.P. acknowledge funding from the European Commission, under Grants 874735 (VEO), 853271 (H-MIP), and 2020/2094 (NextGenerationEU, through CSIC's Global Health Platform, PTI Salud Global).
• dc.format.mimetype application/pdf
• dc.identifier.citation Chen GJ, Palmer JRB, Bartumeus F, Alba-Casals A. Modeling the impact of surveillance activities combined with physical distancing interventions on COVID-19 epidemics at a local level. Infect Dis Model. 2022;7(4):811-22. DOI: 10.1016/j.idm.2022.11.001
• dc.identifier.doi http://dx.doi.org/10.1016/j.idm.2022.11.001
• dc.identifier.issn 2468-2152
• dc.identifier.uri http://hdl.handle.net/10230/57606
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Infectious Disease Modelling. 2022;7(4):811-22.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874735
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/853271
• dc.rights © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.keyword SARS-CoV-2
• dc.subject.keyword Physical distancing
• dc.subject.keyword Social mixing pattern
• dc.subject.keyword Contact tracing
• dc.subject.keyword Scenario tree analysis
• dc.title Modeling the impact of surveillance activities combined with physical distancing interventions on COVID-19 epidemics at a local level
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion