COVID-19 Trend Estimation in the Elderly Italian Region of Sardinia.
COVID-19
SIRD-model
coronavirus
pandemic
public health emergency
Journal
Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579
Informations de publication
Date de publication:
2020
2020
Historique:
received:
02
04
2020
accepted:
14
04
2020
entrez:
12
5
2020
pubmed:
12
5
2020
medline:
12
5
2020
Statut:
epublish
Résumé
December 2019 saw a novel coronavirus (COVID-19) from China quickly spread globally. Currently, COVID-19, defined as the new pandemic by the World Health Organization (WHO), has reached over 750,000 confirmed cases worldwide. The virus began to spread in Italy from the 22nd February, and the number of related cases is still increasing. Furthermore, given that a relevant proportion of infected people need hospitalization in Intensive Care Units, this may be a crucial issue for National Healthcare System's capacity. WHO underlines the importance of specific disease regional estimates. Because of this, Italy aimed to put in place proportioned and controlled measures, and to guarantee adequate funding to both increase the number of ICU beds and increase production of personal protective equipment. Our aim is to investigate the current COVID-19 epidemiological context in Sardinia region (Italy) and to estimate the transmission parameters using a stochastic model to establish the number of infected, recovered, and deceased people expected. Based on available data from official Italian and regional sources, we describe the distribution of infected cases during the period between 2nd and 15th March 2020. To better reflect the actual spread of COVID-19 in Sardinia based on data from 15th March (first Sardinian declared outbreak), two Susceptible-Infectious-Recovered-Dead (SIRD) models have been developed, describing the best and worst scenarios. We believe that our findings represent a valid contribution to better understand the epidemiological context of COVID-19 in Sardinia. Our analysis can help health authorities and policymakers to address the right interventions to deal with the rapidly expanding health emergency.
Identifiants
pubmed: 32391308
doi: 10.3389/fpubh.2020.00153
pmc: PMC7193021
doi:
Types de publication
Journal Article
Langues
eng
Pagination
153Informations de copyright
Copyright © 2020 Puci, Loi, Ferraro, Cappai, Rolesu and Montomoli.
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