DP15229 Pandemic Control in ECON-EPI Networks

Author(s): Marina Azzimonti, Alessandra Fogli, Fabrizio Perri, Mark Ponder
Publication Date: August 2020
Keyword(s): Complex Networks, COVID-19, epidemiology, SIR, social distance
JEL(s): D85, E23, E65, I18
Programme Areas: Public Economics, Macroeconomics and Growth
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=15229

We develop an ECON-EPI network model to evaluate policies designed to improve health and economic outcomes during a pandemic. Relative to the standard epidemiological SIR set-up, we explicitly model social contacts among individuals and allow for heterogeneity in their number and stability. In addition, we embed the network in a structural economic model describing how contacts generate economic activity. We calibrate it to the New York metro area during the 2020 COVID-19 crisis and show three main results. First, the ECON-EPI network implies patterns of infections that better match the data compared to the standard SIR. The switching during the early phase of the pandemic from unstable to stable contacts is crucial for this result. Second, the model suggests the design of smart policies that reduce infections and at the same time boost economic activity. Third, the model shows that re-opening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.