A dynamic multistate and control model of the COVID-19 pandemic

Publication Date

1-1-2023

Document Type

Article

Publication Title

Journal of Public Health (Germany)

DOI

10.1007/s10389-023-02014-z

Abstract

Aim: We specify a multistate dynamic model of COVID-19 states and investigate the efficiency of lockdown policies in a control application. Method: Computational and analytical methods are implemented to indicate parameter sensitivities of the multistate model. An objective function in a control specification is then used to evaluate the cost efficacy of lockdowns to manage the diffusion of infection before the availability of a vaccine. Results: Results of the control model indicate differences in cost–cost offsets over time in a lockdown under different levels of wage and mortality rates. We show the range of conditions under which cost offsets of a lockdown can exceed costs. Conclusions: Lockdowns have been initiated due largely to the headline numbers of mortality rates, “pain and suffering” of those infected, and burdens on health care systems. We show that lockdowns can be cost-efficient over a range of wage and mortality rates provided that they are maintained in place for certain lengths of time. The time intervals we investigate have been demonstrated to be feasible across a wide range of countries.

Funding Sponsor

Natural Sciences and Engineering Research Council of Canada

Keywords

Control models, COVID-19, Dynamic multi-state models, Lockdown policy

Department

Marketing and Business Analytics

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