On the evolution of the COVID-19 epidemiological parameters using only the series of deceased. A study of the Spanish outbreak using Genetic Algorithms

Eduardo Acosta-González, Julián Andrada-Félix and Fernando Fernández-Rodríguez

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 197, issue C, 91-104

Abstract: We propose a methodology for estimating the evolution of the epidemiological parameters of a SIRD model (acronym of Susceptible, Infected, Recovered and Deceased individuals) which allows to evaluate the sanitary measures taken by the government, for the COVID-19 in the Spanish outbreak. In our methodology the only information required for estimating these parameters is the time series of deceased people; due to the number of asymptomatic people produced by the COVID-19, it is not possible to know the actual number of infected people at any given time. Therefore, among the different time series that quantify the pandemic we consider just the number of deceased people to minimize the square sum of errors.

Keywords: COVID-19; SIRD model estimation; Predictive modelling; Genetic Algorithm (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:197:y:2022:i:c:p:91-104

DOI: 10.1016/j.matcom.2022.02.007

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