Rational social distancing policy during epidemics with limited healthcare capacity
PLoS Comput. Biol.(2022)
摘要
Epidemics of infectious diseases posing a serious risk to human health have
occurred throughout history. During recent epidemics there has been much debate
about policy, including how and when to impose restrictions on behaviour.
Policymakers must balance a complex spectrum of objectives, suggesting a need
for quantitative tools. Whether health services might be `overwhelmed' has
emerged as a key consideration. Here we show how costly interventions, such as
taxes or subsidies on behaviour, can be used to exactly align individuals'
decision making with government preferences even when these are not aligned. In
order to achieve this, we develop a nested optimisation algorithm of both the
government intervention strategy and the resulting equilibrium behaviour of
individuals. We focus on a situation in which the capacity of the healthcare
system to treat patients is limited and identify conditions under which the
disease dynamics respect the capacity limit. We find an extremely sharp drop in
peak infections at a critical maximum infection cost in the government's
objective function. This is in marked contrast to the gradual reduction of
infections if individuals make decisions without government intervention. We
find optimal interventions vary less strongly in time when interventions are
costly to the government and that the critical cost of the policy switch
depends on how costly interventions are.
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