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How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19
To combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effective...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093197/ https://www.ncbi.nlm.nih.gov/pubmed/33941793 http://dx.doi.org/10.1038/s41598-021-88768-6 |
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author | Pandl, Konstantin D. Thiebes, Scott Schmidt-Kraepelin, Manuel Sunyaev, Ali |
author_facet | Pandl, Konstantin D. Thiebes, Scott Schmidt-Kraepelin, Manuel Sunyaev, Ali |
author_sort | Pandl, Konstantin D. |
collection | PubMed |
description | To combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing. |
format | Online Article Text |
id | pubmed-8093197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80931972021-05-05 How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 Pandl, Konstantin D. Thiebes, Scott Schmidt-Kraepelin, Manuel Sunyaev, Ali Sci Rep Article To combat the COVID-19 pandemic, many countries around the globe have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective technology for contact tracing. Nature Publishing Group UK 2021-05-03 /pmc/articles/PMC8093197/ /pubmed/33941793 http://dx.doi.org/10.1038/s41598-021-88768-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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 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 Pandl, Konstantin D. Thiebes, Scott Schmidt-Kraepelin, Manuel Sunyaev, Ali How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title | How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title_full | How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title_fullStr | How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title_full_unstemmed | How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title_short | How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19 |
title_sort | how detection ranges and usage stops impact digital contact tracing effectiveness for covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093197/ https://www.ncbi.nlm.nih.gov/pubmed/33941793 http://dx.doi.org/10.1038/s41598-021-88768-6 |
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