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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...

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Autores principales: Moreno López, Jesús A., Arregui García, Beatriz, Bentkowski, Piotr, Bioglio, Livio, Pinotti, Francesco, Boëlle, Pierre-Yves, Barrat, Alain, Colizza, Vittoria, Poletto, Chiara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2021
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.
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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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