An urn model of COVID-19 dynamics under social lockdown

Abstract

In 2020, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a global pandemic of the Coronavirus disease 2019 (COVID-19). It could be helpful to be able to simulate the dynamics of the transmission of the virus so that relevant authorities and prepare and allocate resources to help infected individuals or help curb further widespread transmission. In this paper, we use a mathematical model- the urn model to map the behaviour of virus transmission in a social lockdown environment. We also simulated the dynamics of the virus transmission to observe trends and behaviour using the Gillespie algorithm. We review the effectiveness and accuracy of the mathematical model and algorithm used in our simulation. We propose that the algorithm could be useful to accurately simulate such dynamics in future relevant studies.