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A statistical analysis of the novel coronavirus (COVID-19) in Italy and Spain.
Chu, Jeffrey.
  • Chu J; School of Statistics, Renmin University of China, Beijing, China.
PLoS One ; 16(3): e0249037, 2021.
Article in English | MEDLINE | ID: covidwho-1150553
ABSTRACT
The novel coronavirus (COVID-19) that was first reported at the end of 2019 has impacted almost every aspect of life as we know it. This paper focuses on the incidence of the disease in Italy and Spain-two of the first and most affected European countries. Using two simple mathematical epidemiological models-the Susceptible-Infectious-Recovered model and the log-linear regression model, we model the daily and cumulative incidence of COVID-19 in the two countries during the early stage of the outbreak, and compute estimates for basic measures of the infectiousness of the disease including the basic reproduction number, growth rate, and doubling time. Estimates of the basic reproduction number were found to be larger than 1 in both countries, with values being between 2 and 3 for Italy, and 2.5 and 4 for Spain. Estimates were also computed for the more dynamic effective reproduction number, which showed that since the first cases were confirmed in the respective countries the severity has generally been decreasing. The predictive ability of the log-linear regression model was found to give a better fit and simple estimates of the daily incidence for both countries were computed.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0249037

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0249037