Modeling the Epidemiological Trend and Behavior of COVID-19 in Italy.
Cureus
; 12(8): e9884, 2020 Aug 20.
Article
in English
| MEDLINE | ID: covidwho-742989
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
Language:
English
Journal:
Cureus
Year:
2020
Document Type:
Article
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