Balancing health and economic impacts from targeted pandemic restrictions

Abstract

The COVID-19 pandemic has highlighted the necessity for policymakers to design interventions that allow to promptly resume economic activities while taking control of the healthcare emergency. We analyze the response of differentiated policy measures by exploiting a meta-population SEIR model based on transaction data that map human mobility through daily physical transactions performed by cardholders of a major Italian bank. We calibrate multiple counterfactual scenarios and study the impact of alternative combinations of tailored mobility restrictions with different intensity across sectors. Although the Retail sector accounts for the largest portion of mobility and drive results in terms of infections and consumption dynamics, other economic activities, such as those related to Restaurants, have a relevant role in the design of the optimal policy. Finally, we show how the proposed approach can be used by policymakers to evaluate the trade-off between economic and healthcare impacts by identifying the alternative policy restrictions that minimize either the economic impact given a certain level of infections or the spread of contagion for a target value of economic impact.