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Optimal Lockdown Policy with Virus Mutation

Author

Listed:
  • Quentin Batista
  • Masakazu Emoto
  • Naoki Maezono
  • Taisuke Nakata

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.

Suggested Citation

  • Quentin Batista & Masakazu Emoto & Naoki Maezono & Taisuke Nakata, 2026. "Optimal Lockdown Policy with Virus Mutation," Working Papers e221, Tokyo Center for Economic Research.
    • Handle: RePEc:tcr:wpaper:e221
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