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The spreading of SARS-CoV-2: Interage contacts and networks degree distribution

Notable cross-country differences exist in the diffusion of the Covid-19 and in its lethality. Contact patterns in populations, and in particular intergenerational contacts, have been argued to be responsible for the most vulnerable, the elderly, getting infected more often and thus driving up morta...

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Detalles Bibliográficos
Autores principales: Sage, Lucas, Albertini, Marco, Scherer, Stefani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386875/
https://www.ncbi.nlm.nih.gov/pubmed/34432818
http://dx.doi.org/10.1371/journal.pone.0256036
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author Sage, Lucas
Albertini, Marco
Scherer, Stefani
author_facet Sage, Lucas
Albertini, Marco
Scherer, Stefani
author_sort Sage, Lucas
collection PubMed
description Notable cross-country differences exist in the diffusion of the Covid-19 and in its lethality. Contact patterns in populations, and in particular intergenerational contacts, have been argued to be responsible for the most vulnerable, the elderly, getting infected more often and thus driving up mortality in some context, like in the southern European one. This paper asks a simple question: is it between whom contacts occur that matters or is it simply how many contacts people have? Due to the high number of confounding factors, it is extremely difficult to empirically assess the impact of single network features separately. This is why we rely on a simulation exercise in which we counterfactually manipulate single aspects of countries’ age distribution and network structures. We disentangle the contributions of the kind and of the number of contacts while holding constant the age structure. More precisely, we isolate the respective effects of inter-age contact patterns, degree distribution and clustering on the virus propagation across age groups. We use survey data on face-to-face contacts for Great Britain, Italy, and Germany, to reconstruct networks that mirror empirical contact patterns in these three countries. It turns out that the number of social contacts (degree distribution) largely accounts for the higher infection rates of the elderly in the Italian context, while differences in inter-age contacts patterns are only responsible for minor differences. This suggests that policies specifically targeting inter-age contacts would be little effective.
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spelling pubmed-83868752021-08-26 The spreading of SARS-CoV-2: Interage contacts and networks degree distribution Sage, Lucas Albertini, Marco Scherer, Stefani PLoS One Research Article Notable cross-country differences exist in the diffusion of the Covid-19 and in its lethality. Contact patterns in populations, and in particular intergenerational contacts, have been argued to be responsible for the most vulnerable, the elderly, getting infected more often and thus driving up mortality in some context, like in the southern European one. This paper asks a simple question: is it between whom contacts occur that matters or is it simply how many contacts people have? Due to the high number of confounding factors, it is extremely difficult to empirically assess the impact of single network features separately. This is why we rely on a simulation exercise in which we counterfactually manipulate single aspects of countries’ age distribution and network structures. We disentangle the contributions of the kind and of the number of contacts while holding constant the age structure. More precisely, we isolate the respective effects of inter-age contact patterns, degree distribution and clustering on the virus propagation across age groups. We use survey data on face-to-face contacts for Great Britain, Italy, and Germany, to reconstruct networks that mirror empirical contact patterns in these three countries. It turns out that the number of social contacts (degree distribution) largely accounts for the higher infection rates of the elderly in the Italian context, while differences in inter-age contacts patterns are only responsible for minor differences. This suggests that policies specifically targeting inter-age contacts would be little effective. Public Library of Science 2021-08-25 /pmc/articles/PMC8386875/ /pubmed/34432818 http://dx.doi.org/10.1371/journal.pone.0256036 Text en © 2021 Sage et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sage, Lucas
Albertini, Marco
Scherer, Stefani
The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title_full The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title_fullStr The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title_full_unstemmed The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title_short The spreading of SARS-CoV-2: Interage contacts and networks degree distribution
title_sort spreading of sars-cov-2: interage contacts and networks degree distribution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386875/
https://www.ncbi.nlm.nih.gov/pubmed/34432818
http://dx.doi.org/10.1371/journal.pone.0256036
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