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Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion
The COVID-19 pandemic has sparked an intense debate about the hidden factors underlying the dynamics of the outbreak. Several computational models have been proposed to inform effective social and healthcare strategies. Crucially, the predictive validity of these models often depends upon incorporat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716563/ https://www.ncbi.nlm.nih.gov/pubmed/34976909 http://dx.doi.org/10.3389/fpubh.2021.724362 |
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author | Gandolfi, Daniela Pagnoni, Giuseppe Filippini, Tommaso Goffi, Alessia Vinceti, Marco D'Angelo, Egidio Mapelli, Jonathan |
author_facet | Gandolfi, Daniela Pagnoni, Giuseppe Filippini, Tommaso Goffi, Alessia Vinceti, Marco D'Angelo, Egidio Mapelli, Jonathan |
author_sort | Gandolfi, Daniela |
collection | PubMed |
description | The COVID-19 pandemic has sparked an intense debate about the hidden factors underlying the dynamics of the outbreak. Several computational models have been proposed to inform effective social and healthcare strategies. Crucially, the predictive validity of these models often depends upon incorporating behavioral and social responses to infection. Among these tools, the analytic framework known as “dynamic causal modeling” (DCM) has been applied to the COVID-19 pandemic, shedding new light on the factors underlying the dynamics of the outbreak. We have applied DCM to data from northern Italian regions, the first areas in Europe to contend with the outbreak, and analyzed the predictive validity of the model and also its suitability in highlighting the hidden factors governing the pandemic diffusion. By taking into account data from the beginning of the pandemic, the model could faithfully predict the dynamics of outbreak diffusion varying from region to region. The DCM appears to be a reliable tool to investigate the mechanisms governing the spread of the SARS-CoV-2 to identify the containment and control strategies that could efficiently be used to counteract further waves of infection. |
format | Online Article Text |
id | pubmed-8716563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87165632021-12-31 Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion Gandolfi, Daniela Pagnoni, Giuseppe Filippini, Tommaso Goffi, Alessia Vinceti, Marco D'Angelo, Egidio Mapelli, Jonathan Front Public Health Public Health The COVID-19 pandemic has sparked an intense debate about the hidden factors underlying the dynamics of the outbreak. Several computational models have been proposed to inform effective social and healthcare strategies. Crucially, the predictive validity of these models often depends upon incorporating behavioral and social responses to infection. Among these tools, the analytic framework known as “dynamic causal modeling” (DCM) has been applied to the COVID-19 pandemic, shedding new light on the factors underlying the dynamics of the outbreak. We have applied DCM to data from northern Italian regions, the first areas in Europe to contend with the outbreak, and analyzed the predictive validity of the model and also its suitability in highlighting the hidden factors governing the pandemic diffusion. By taking into account data from the beginning of the pandemic, the model could faithfully predict the dynamics of outbreak diffusion varying from region to region. The DCM appears to be a reliable tool to investigate the mechanisms governing the spread of the SARS-CoV-2 to identify the containment and control strategies that could efficiently be used to counteract further waves of infection. Frontiers Media S.A. 2021-12-16 /pmc/articles/PMC8716563/ /pubmed/34976909 http://dx.doi.org/10.3389/fpubh.2021.724362 Text en Copyright © 2021 Gandolfi, Pagnoni, Filippini, Goffi, Vinceti, D'Angelo and Mapelli. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Gandolfi, Daniela Pagnoni, Giuseppe Filippini, Tommaso Goffi, Alessia Vinceti, Marco D'Angelo, Egidio Mapelli, Jonathan Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title | Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title_full | Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title_fullStr | Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title_full_unstemmed | Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title_short | Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion |
title_sort | modeling early phases of covid-19 pandemic in northern italy and its implication for outbreak diffusion |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716563/ https://www.ncbi.nlm.nih.gov/pubmed/34976909 http://dx.doi.org/10.3389/fpubh.2021.724362 |
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