Easing or tightening control strategies: determination of COVID-19 parameters for an agent-based model

Ali Najmi (), Sahar Nazari (), Farshid Safarighouzhdi (), Eric J. Miller (), Raina MacIntyre () and Taha H. Rashidi ()
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Ali Najmi: The University of New South Wales
Sahar Nazari: Macquarie University
Farshid Safarighouzhdi: The University of New South Wales
Eric J. Miller: University of Toronto
Raina MacIntyre: Arizona State University College of Health Solutions
Taha H. Rashidi: The University of New South Wales

Transportation, 2022, vol. 49, issue 5, No 1, 1265-1293

Abstract: Abstract Some agent-based models have been developed to estimate the spread progression of coronavirus disease 2019 (COVID-19) and to evaluate strategies aimed to control the outbreak of the infectious disease. Nonetheless, COVID-19 parameter estimation methods are limited to observational epidemiologic studies which are essentially aggregated models. We propose a mathematical structure to determine parameters of agent-based models accounting for the mutual effects of parameters. We then use the agent-based model to assess the extent to which different control strategies can intervene the transmission of COVID-19. Easing social distancing restrictions, opening businesses, speed of enforcing control strategies, quarantining family members of isolated cases on the disease progression and encouraging the use of facemask are the strategies assessed in this study. We estimate the social distancing compliance level in Sydney greater metropolitan area and then elaborate the consequences of moderating the compliance level in the disease suppression. We also show that social distancing and facemask usage are complementary and discuss their interactive effects in detail.

Keywords: Social distancing; Compliance level; Agent-based disease spread model; Facemask; Control strategies (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11116-021-10210-7

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