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dc.contributor.authorBradshaw, William J.en_US
dc.contributor.authorAlley, Ethan C.en_US
dc.contributor.authorHuggins, Jonathan H.en_US
dc.contributor.authorLloyd, Alun L.en_US
dc.contributor.authorEsvelt, Kevin M.en_US
dc.coverage.spatialEnglanden_US
dc.date2020-11-24
dc.date.accessioned2021-04-07T17:54:19Z
dc.date.available2021-04-07T17:54:19Z
dc.date.issued2021-01-11
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/33431829
dc.identifier.citationWilliam J Bradshaw, Ethan C Alley, Jonathan H Huggins, Alun L Lloyd, Kevin M Esvelt. 2021. "Bidirectional contact tracing could dramatically improve COVID-19 control.." Nat Commun, Volume 12, Issue 1, pp. 232 - ?. https://doi.org/10.1038/s41467-020-20325-7
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/2144/42364
dc.description.abstractContact tracing is critical to controlling COVID-19, but most protocols only "forward-trace" to notify people who were recently exposed. Using a stochastic branching-process model, we find that "bidirectional" tracing to identify infector individuals and their other infectees robustly improves outbreak control. In our model, bidirectional tracing more than doubles the reduction in effective reproduction number (Reff) achieved by forward-tracing alone, while dramatically increasing resilience to low case ascertainment and test sensitivity. The greatest gains are realised by expanding the manual tracing window from 2 to 6 days pre-symptom-onset or, alternatively, by implementing high-uptake smartphone-based exposure notification; however, to achieve the performance of the former approach, the latter requires nearly all smartphones to detect exposure events. With or without exposure notification, our results suggest that implementing bidirectional tracing could dramatically improve COVID-19 control.en_US
dc.description.sponsorshipU01CK000587 - ACL HHS; U01 CK000587 - NCEZID CDC HHSen_US
dc.format.extentp. 232en_US
dc.languageeng
dc.language.isoen_US
dc.relation.ispartofNat Commun
dc.rights© The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/.
dc.subjectCOVID-19en_US
dc.subjectComputer simulationen_US
dc.subjectContact tracingen_US
dc.subjectDisease outbreaksen_US
dc.subjectHumansen_US
dc.subjectMobile applicationsen_US
dc.subjectSARS-CoV-2en_US
dc.subjectSensitivity and specificityen_US
dc.subjectSmartphoneen_US
dc.titleBidirectional contact tracing could dramatically improve COVID-19 controlen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1038/s41467-020-20325-7
pubs.elements-sourcepubmeden_US
pubs.notesEmbargo: No embargoen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Mathematics & Statisticsen_US
pubs.publication-statusPublished onlineen_US
dc.identifier.mycv586711


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© The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.