Cargando…
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...
Autores principales: | , , |
---|---|
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 |
_version_ | 1783584832545095680 |
---|---|
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. |
format | Online Article Text |
id | pubmed-7505530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT rovettaalessandro modelingtheepidemiologicaltrendandbehaviorofcovid19initaly AT bhagavathulaakshayas modelingtheepidemiologicaltrendandbehaviorofcovid19initaly AT castaldolucia modelingtheepidemiologicaltrendandbehaviorofcovid19initaly |