A simple planning problem for COVID-19 lockdown: a dynamic programming approach
- PMID: 37360773
- PMCID: PMC10105532
- DOI: 10.1007/s00199-023-01493-1
A simple planning problem for COVID-19 lockdown: a dynamic programming approach
Abstract
A large number of recent studies consider a compartmental SIR model to study optimal control policies aimed at containing the diffusion of COVID-19 while minimizing the economic costs of preventive measures. Such problems are non-convex and standard results need not to hold. We use a Dynamic Programming approach and prove some continuity properties of the value function of the associated optimization problem. We study the corresponding Hamilton-Jacobi-Bellman equation and show that the value function solves it in the viscosity sense. Finally, we discuss some optimality conditions. Our paper represents a first contribution towards a complete analysis of non-convex dynamic optimization problems, within a Dynamic Programming approach.
Keywords: Controlled SIRD model; Optimal control with state space constraints; Optimal lockdown policies; Optimality conditions; Viscosity solutions.
© The Author(s) 2023.
Conflict of interest statement
Conflict of interestThe authors have no competing interests to declare that are relevant to the content of this article.
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- Alvarez, F.E., Argente, D., Lippi, F.: A simple planning problem for COVID-19 lockdown. Technical report, National Bureau of Economic Research (2020)
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