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Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection
The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital conta...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034853/ https://www.ncbi.nlm.nih.gov/pubmed/33712416 http://dx.doi.org/10.1126/sciadv.abd8750 |
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author | Moreno López, Jesús A. Arregui García, Beatriz Bentkowski, Piotr Bioglio, Livio Pinotti, Francesco Boëlle, Pierre-Yves Barrat, Alain Colizza, Vittoria Poletto, Chiara |
author_facet | Moreno López, Jesús A. Arregui García, Beatriz Bentkowski, Piotr Bioglio, Livio Pinotti, Francesco Boëlle, Pierre-Yves Barrat, Alain Colizza, Vittoria Poletto, Chiara |
author_sort | Moreno López, Jesús A. |
collection | PubMed |
description | The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan. |
format | Online Article Text |
id | pubmed-8034853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-80348532021-04-21 Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection Moreno López, Jesús A. Arregui García, Beatriz Bentkowski, Piotr Bioglio, Livio Pinotti, Francesco Boëlle, Pierre-Yves Barrat, Alain Colizza, Vittoria Poletto, Chiara Sci Adv Research Articles The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan. American Association for the Advancement of Science 2021-04-09 /pmc/articles/PMC8034853/ /pubmed/33712416 http://dx.doi.org/10.1126/sciadv.abd8750 Text en Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Moreno López, Jesús A. Arregui García, Beatriz Bentkowski, Piotr Bioglio, Livio Pinotti, Francesco Boëlle, Pierre-Yves Barrat, Alain Colizza, Vittoria Poletto, Chiara Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title | Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title_full | Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title_fullStr | Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title_full_unstemmed | Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title_short | Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection |
title_sort | anatomy of digital contact tracing: role of age, transmission setting, adoption, and case detection |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034853/ https://www.ncbi.nlm.nih.gov/pubmed/33712416 http://dx.doi.org/10.1126/sciadv.abd8750 |
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