Bidirectional contact tracing could dramatically improve COVID-19 control
dc.contributor.author | Bradshaw, William J. | en_US |
dc.contributor.author | Alley, Ethan C. | en_US |
dc.contributor.author | Huggins, Jonathan H. | en_US |
dc.contributor.author | Lloyd, Alun L. | en_US |
dc.contributor.author | Esvelt, Kevin M. | en_US |
dc.coverage.spatial | England | en_US |
dc.date | 2020-11-24 | |
dc.date.accessioned | 2021-04-07T17:54:19Z | |
dc.date.available | 2021-04-07T17:54:19Z | |
dc.date.issued | 2021-01-11 | |
dc.identifier | https://www.ncbi.nlm.nih.gov/pubmed/33431829 | |
dc.identifier.citation | William 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.issn | 2041-1723 | |
dc.identifier.uri | https://hdl.handle.net/2144/42364 | |
dc.description.abstract | Contact 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.sponsorship | U01CK000587 - ACL HHS; U01 CK000587 - NCEZID CDC HHS | en_US |
dc.format.extent | p. 232 | en_US |
dc.language | eng | |
dc.language.iso | en_US | |
dc.relation.ispartof | Nat 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.uri | http://creativecommons.org/licenses/by/4.0/. | |
dc.subject | COVID-19 | en_US |
dc.subject | Computer simulation | en_US |
dc.subject | Contact tracing | en_US |
dc.subject | Disease outbreaks | en_US |
dc.subject | Humans | en_US |
dc.subject | Mobile applications | en_US |
dc.subject | SARS-CoV-2 | en_US |
dc.subject | Sensitivity and specificity | en_US |
dc.subject | Smartphone | en_US |
dc.title | Bidirectional contact tracing could dramatically improve COVID-19 control | en_US |
dc.type | Article | en_US |
dc.description.version | Published version | en_US |
dc.identifier.doi | 10.1038/s41467-020-20325-7 | |
pubs.elements-source | pubmed | en_US |
pubs.notes | Embargo: No embargo | en_US |
pubs.organisational-group | Boston University | en_US |
pubs.organisational-group | Boston University, College of Arts & Sciences | en_US |
pubs.organisational-group | Boston University, College of Arts & Sciences, Department of Mathematics & Statistics | en_US |
pubs.publication-status | Published online | en_US |
dc.identifier.mycv | 586711 |
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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/.