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Title: Pandemic Control in ECON-EPI Networks

Author(s): Marina Azzimonti, Alessandra Fogli, Fabrizio Perri and Mark Ponder

Publication Date: August 2020

Keyword(s): Complex Networks, COVID-19, epidemiology, SIR and social distance

Programme Area(s): Macroeconomics and Growth and Public Economics

Abstract: 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.

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Bibliographic Reference

Azzimonti, M, Fogli, A, Perri, F and Ponder, M. 2020. 'Pandemic Control in ECON-EPI Networks'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15229