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Optimal control of prevention and treatment in a basic macroeconomic–epidemiological model

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  • La Torre, Davide
  • Malik, Tufail
  • Marsiglio, Simone

Abstract

We analyze the optimal control of disease prevention and treatment in a basic SIS model. We develop a simple macroeconomic setup in which the social planner determines how to optimally intervene, through income taxation, in order to minimize the social cost, inclusive of infection and economic costs, of the spread of an epidemic disease. The disease lowers economic production and thus income by reducing the size of the labor force employed in productive activities, tightening thus the economy’s overall resources constraint. We consider a framework in which the planner uses the collected tax revenue to intervene in either prevention (aimed at reducing the rate of infection) or treatment (aimed at increasing the speed of recovery). Both optimal prevention and treatment policies allow the economy to achieve a disease-free equilibrium in the long run but their associated costs are substantially different along the transitional dynamic path. By quantifying the social costs associated with prevention and treatment we determine which policy is most cost-effective under different circumstances, showing that prevention (treatment) is desirable whenever the infectivity rate is low (high).

Suggested Citation

  • La Torre, Davide & Malik, Tufail & Marsiglio, Simone, 2020. "Optimal control of prevention and treatment in a basic macroeconomic–epidemiological model," Mathematical Social Sciences, Elsevier, vol. 108(C), pages 100-108.
  • Handle: RePEc:eee:matsoc:v:108:y:2020:i:c:p:100-108
    DOI: 10.1016/j.mathsocsci.2020.03.005
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    1. Natali Hritonenko & Olga Yatsenko & Yuri Yatsenko, 2022. "Model with transmission delays for COVID‐19 control: Theory and empirical assessment," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1218-1244, October.
    2. Davide Torre & Simone Marsiglio & Franklin Mendivil & Fabio Privileggi, 2024. "Stochastic disease spreading and containment policies under state-dependent probabilities," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(1), pages 127-168, February.
    3. Davide Torre & Danilo Liuzzi & Rosario Maggistro & Simone Marsiglio, 2022. "Mobility Choices and Strategic Interactions in a Two-Group Macroeconomic–Epidemiological Model," Dynamic Games and Applications, Springer, vol. 12(1), pages 110-132, March.
    4. Chen, Naixi & Fan, Hong, 2023. "Credit risk contagion and optimal dual control—An SIS/R model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 448-472.
    5. Davide La Torre & Danilo Liuzzi & Simone Marsiglio, 2022. "Geographical heterogeneities and externalities in an epidemiological‐macroeconomic framework," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1154-1181, October.
    6. La Torre, Davide & Marsiglio, Simone & Mendivil, Franklin & Privileggi, Fabio, 2021. "Generalized Fractal Transforms with Condensation: a Macroeconomic-Epidemiological Application," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202107, University of Turin.
    7. David Desmarchelier & Magali Jaoul-Grammare & Guillaume Morel & Thi Kim Cuong Pham, 2021. "Infectious disease and endogenous cycles: lockdown hits two birds with one stone," Working Papers of BETA 2021-23, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    8. Christopher J. Coyne & Thomas K. Duncan & Abigail R. Hall, 2021. "The political economy of state responses to infectious disease," Southern Economic Journal, John Wiley & Sons, vol. 87(4), pages 1119-1137, April.
    9. La Torre, Davide & Liuzzi, Danilo & Marsiglio, Simone, 2021. "Epidemics and macroeconomic outcomes: Social distancing intensity and duration," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    10. Zachariah Sinkala & Vajira Manathunga & Bichaka Fayissa, 2022. "An Epidemic Compartment Model for Economic Policy Directions for Managing Future Pandemic," Papers 2202.05374, arXiv.org.

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