Optimal Lockdown Policy with Virus Mutation

Quentin Batista, Masakazu Emoto, Naoki Maezono and Taisuke Nakata
Additional contact information
Quentin Batista: Amazon Japan, Inc.
Masakazu Emoto: Hitotsubashi University
Naoki Maezono: The University of Tokyo
Taisuke Nakata: The University of Tokyo

No CARF-F-618, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo

Abstract: We examine the implications of virus mutation for optimal lockdown policy in an epimacro model. We consider three ways of modelling virus mutation—one deterministic setup and two stochastic setups featuring a two-state and three-state Markov process. We find that the effects of virus mutation are asymmetric. In particular, a future reduction in the transmission rate increases lockdown intensity by more than a future rise in the transmission rate lowers it. As a corollary to this asymmetry, an increase in uncertainty about future mutation is non-neutral and reduces lockdown intensity under the optimal policy.

Pages: 22
Date: 2026-01
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Persistent link: https://EconPapers.repec.org/RePEc:cfi:fseres:cf618

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