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Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy

As of May 14, 2020, Italy has been one of the red hotspots for the COVID-19 pandemic. In particular, the regions of Emilia Romagna, Piedmont, and especially Lombardy were the most affected and had to face very serious health emergencies, which brought them to the brink of collapse. Since the virus h...

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Detalles Bibliográficos
Autores principales: Rovetta, Alessandro, Bhagavathula, Akshaya S, Castaldo, Lucia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505530/
https://www.ncbi.nlm.nih.gov/pubmed/32968550
http://dx.doi.org/10.7759/cureus.9884
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author Rovetta, Alessandro
Bhagavathula, Akshaya S
Castaldo, Lucia
author_facet Rovetta, Alessandro
Bhagavathula, Akshaya S
Castaldo, Lucia
author_sort Rovetta, Alessandro
collection PubMed
description As of May 14, 2020, Italy has been one of the red hotspots for the COVID-19 pandemic. In particular, the regions of Emilia Romagna, Piedmont, and especially Lombardy were the most affected and had to face very serious health emergencies, which brought them to the brink of collapse. Since the virus has demonstrated local properties, i.e., greater severity and contagiousness in specific regions, the aim of this study is to model the complex behavior of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy. In particular, we further investigated the results of other articles on the correlation with particulate matter pollution 10 (PM 10) and 2.5 (PM 2.5) by extending the research at the intra-regional level, as well as calculated a more plausible number of those infected compared to those officially declared by Civil Protection. Through a computational simulation of the Susceptible-Exposed-Infectious-Recovered (S.E.I.R.) model, we also estimated the most representative basic reproduction number [Formula: see text] for these three regions from February 22 to March 14, 2020. In doing so, we have been able to evaluate the consistency of the first containment measures until the end of April, as well as identify possible SARS-CoV-2 local behavior mutations and specificities.
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spelling pubmed-75055302020-09-22 Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy Rovetta, Alessandro Bhagavathula, Akshaya S Castaldo, Lucia Cureus Epidemiology/Public Health As of May 14, 2020, Italy has been one of the red hotspots for the COVID-19 pandemic. In particular, the regions of Emilia Romagna, Piedmont, and especially Lombardy were the most affected and had to face very serious health emergencies, which brought them to the brink of collapse. Since the virus has demonstrated local properties, i.e., greater severity and contagiousness in specific regions, the aim of this study is to model the complex behavior of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy. In particular, we further investigated the results of other articles on the correlation with particulate matter pollution 10 (PM 10) and 2.5 (PM 2.5) by extending the research at the intra-regional level, as well as calculated a more plausible number of those infected compared to those officially declared by Civil Protection. Through a computational simulation of the Susceptible-Exposed-Infectious-Recovered (S.E.I.R.) model, we also estimated the most representative basic reproduction number [Formula: see text] for these three regions from February 22 to March 14, 2020. In doing so, we have been able to evaluate the consistency of the first containment measures until the end of April, as well as identify possible SARS-CoV-2 local behavior mutations and specificities. Cureus 2020-08-20 /pmc/articles/PMC7505530/ /pubmed/32968550 http://dx.doi.org/10.7759/cureus.9884 Text en Copyright © 2020, Rovetta et al. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Epidemiology/Public Health
Rovetta, Alessandro
Bhagavathula, Akshaya S
Castaldo, Lucia
Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title_full Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title_fullStr Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title_full_unstemmed Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title_short Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy
title_sort modeling the epidemiological trend and behavior of covid-19 in italy
topic Epidemiology/Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505530/
https://www.ncbi.nlm.nih.gov/pubmed/32968550
http://dx.doi.org/10.7759/cureus.9884
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