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Deterministic and stochastic simulation of the COVID-19 epidemic with the SEIR model

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Detalhes bibliográficos
Resumo:This work regards the simulation of the spread of the COVID-19 disease in a community by applying the deterministic and stochastic Susceptible-Exposed-Infective-Recovered (SEIR) epidemic models. The developed computational method for the stochastic variant allows to realistically simulate the spread of COVID-19 in a medium-sized community and to study the effect of preventive measures such as quarantine and vaccination. The results of the simulations are compared with the deterministic version of the SEIR model. The comparison makes it possible to conclude that the epidemic outbreak can be prevented even though the basic reproduction number is greater than one.
Autores principais:Balsa, Carlos
Outros Autores:Guarda, Teresa; Lopes, Isabel Maria; Rufino, José
Assunto:SEIR model COVID-19 Numerical simulations
Ano:2021
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:português
Origem:Biblioteca Digital do IPB
Descrição
Resumo:This work regards the simulation of the spread of the COVID-19 disease in a community by applying the deterministic and stochastic Susceptible-Exposed-Infective-Recovered (SEIR) epidemic models. The developed computational method for the stochastic variant allows to realistically simulate the spread of COVID-19 in a medium-sized community and to study the effect of preventive measures such as quarantine and vaccination. The results of the simulations are compared with the deterministic version of the SEIR model. The comparison makes it possible to conclude that the epidemic outbreak can be prevented even though the basic reproduction number is greater than one.