Pandemic Control in Econ-Epi Networks

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 reopening sectors characterized by numerous and unstable contacts (such as large events or schools) too early leads to fast growth of infections.

JUE Insight: The determinants of the differential exposure to COVID-19 in New York city and their evolution over time

“…Thus, it is likely that their entire community becomes infected. This argument is similar to that of Azzimonti et al. (2020) , who argue that infections occur in clusters defined by social and occupational networks.…”

Monetary Policy and COVID-19

“…Glover et al (2020) introduce a quantitative model to examine the interaction between macro-mitigation and micro-redistribution to find that optimal mitigation involves a mixture of such policies. Azzimonti et al (2020) study infection dynamics and reopening scenarios in a heterogeneous sectors and household network model. Kaplan et al (2020a) argue that the government policy must face trade-offs between lives and livelihoods and over who should bear the burden of the economic costs.…”

Integrated epi-econ assessment of vaccination

“…We suspect, however, that our result is a function of our different modeling of social interactions. Finally, and interestingly, there are attempts to develop theory of social interactions along the dimension of social networks, which appear important in this context; see Azzimonti et al. (2020) for a prominent example.…”