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Trading contact tracing efficiency for finding patient zero
As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801158/ https://www.ncbi.nlm.nih.gov/pubmed/36585429 http://dx.doi.org/10.1038/s41598-022-26892-7 |
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author | Waniek, Marcin Holme, Petter Farrahi, Katayoun Emonet, Rémi Cebrian, Manuel Rahwan, Talal |
author_facet | Waniek, Marcin Holme, Petter Farrahi, Katayoun Emonet, Rémi Cebrian, Manuel Rahwan, Talal |
author_sort | Waniek, Marcin |
collection | PubMed |
description | As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals. |
format | Online Article Text |
id | pubmed-9801158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98011582022-12-30 Trading contact tracing efficiency for finding patient zero Waniek, Marcin Holme, Petter Farrahi, Katayoun Emonet, Rémi Cebrian, Manuel Rahwan, Talal Sci Rep Article As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals. Nature Publishing Group UK 2022-12-30 /pmc/articles/PMC9801158/ /pubmed/36585429 http://dx.doi.org/10.1038/s41598-022-26892-7 Text en © The Author(s) 2022, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Waniek, Marcin Holme, Petter Farrahi, Katayoun Emonet, Rémi Cebrian, Manuel Rahwan, Talal Trading contact tracing efficiency for finding patient zero |
title | Trading contact tracing efficiency for finding patient zero |
title_full | Trading contact tracing efficiency for finding patient zero |
title_fullStr | Trading contact tracing efficiency for finding patient zero |
title_full_unstemmed | Trading contact tracing efficiency for finding patient zero |
title_short | Trading contact tracing efficiency for finding patient zero |
title_sort | trading contact tracing efficiency for finding patient zero |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801158/ https://www.ncbi.nlm.nih.gov/pubmed/36585429 http://dx.doi.org/10.1038/s41598-022-26892-7 |
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