Working Paper: CEPR ID: DP15229
Authors: Marina Azzimonti; Alessandra Fogli; Fabrizio Perri; Mark Ponder
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.
Keywords: complex networks; covid-19; epidemiology; sir; social distance
JEL Codes: D85; E23; E65; I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| severing of specific links (Y80) | reductions in infections (I14) |
| severing of specific links (Y80) | economic costs (D61) |
| severing of specific links (Y80) | marginal infection reductions (I14) |
| severing of specific links (Y80) | differential impacts on infections and economic activity (F69) |
| econepi network model (D85) | infection patterns align with observed data (Y10) |
| transition from unstable to stable contacts (C62) | accurately modeling infection dynamics (C59) |
| reduction in infection cases (I14) | increase in output (E23) |
| premature reopening of sectors (F41) | resurgence of infections (F44) |
| network structure (D85) | implications on infection spread (I14) |
| network structure (D85) | implications on economic outcomes (F61) |