Optimal Lockdown Policy with Virus Mutation

Quentin Batista, Masakazu Emoto, Naoki Maezono and Taisuke Nakata

No e221, Working Papers from Tokyo Center for Economic Research

Abstract: We examine the implications of virus mutation for optimal lockdown policy in an epi-macro model. We consider three ways of modelling mutation---one deterministic setup and two stochastic setups featuring a two-state and three-state Markov process. We find that the effects of mutation on optimal lockdown policy 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: 21 pages
Date: 2026-03
New Economics Papers: this item is included in nep-hea
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