Controlling COVID-19 Outbreaks with Financial Incentives

Int J Environ Res Public Health. 2021 Jan 15;18(2):724. doi: 10.3390/ijerph18020724.


In this paper, we consider controlling coronavirus disease 2019 (COVID-19) outbreaks with financial incentives. We use the recently developed susceptible-unidentified infected-confirmed (SUC) epidemic model. The unidentified infected population is defined as the infected people who are not yet identified and isolated and can spread the disease to susceptible individuals. It is important to quickly identify and isolate infected people among the unidentified infected population to prevent the infectious disease from spreading. Considering financial incentives as a strategy to control the spread of disease, we predict the effect of the strategy through a mathematical model. Although incentive costs are required, the duration of the disease can be shortened. First, we estimate the unidentified infected cases of COVID-19 in South Korea using the SUC model, and compute two parameters such as the disease transmission rate and the inverse of the average time for confirming infected individuals. We assume that when financial incentives are provided, there are changes in the proportion of confirmed patients out of unidentified infected people in the SUC model. We evaluate the numbers of confirmed and unidentified infected cases with respect to one parameter while fixing the other estimated parameters. We investigate the effect of the incentives on the termination time of the spread of the disease. The larger the incentive budget is, the faster the epidemic will end. Therefore, financial incentives can have the advantage of reducing the total cost required to prevent the spread of the disease, treat confirmed patients, and recover overall economic losses.

Keywords: COVID-19; SUC epidemic model; financial incentives; least-squares fitting.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19 / economics*
  • COVID-19 / prevention & control*
  • Disease Outbreaks
  • Humans
  • Models, Theoretical
  • Motivation*
  • Republic of Korea / epidemiology