A stochastic epidemic model of COVID-19 disease

Xavier Bardina; Marco Ferrante; Carles Rovira

doi:10.3934/math.2020490

A stochastic epidemic model of COVID-19 disease

Xavier Bardina, Marco Ferrante, Carles Rovira^*

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Article › Research › peer-review

10 Citations (Scopus)

Abstract

To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynamics of such diseases.

Original language	English
Pages (from-to)	7661-7677
Number of pages	17
Journal	AIMS Mathematics
Volume	5
Issue number	6
DOIs	https://doi.org/10.3934/math.2020490
Publication status	Published - 26 Sept 2020

Keywords

COVID-19
Reproduction number
SIR model

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10.3934/math.2020490

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title = "A stochastic epidemic model of COVID-19 disease",

abstract = "To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynamics of such diseases.",

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AU - Ferrante, Marco

AU - Rovira, Carles

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AB - To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynamics of such diseases.

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KW - Reproduction number

KW - SIR model

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DO - 10.3934/math.2020490

M3 - Article

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JO - AIMS Mathematics

JF - AIMS Mathematics

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A stochastic epidemic model of COVID-19 disease

Abstract

Keywords

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