How to Stop Contagion: Applying Network Sci. to Evaluate COVID-19 Vaccine Plans

• In Event: Networks, Governance, and Cooperation

Abstract

The novelty of the Covid-19 virus effectively set up a natural experiment of policy-making under conditions of incomplete information. Combined with President Trump's haphazard decision to delegate Covid-19 vaccine distribution to US states, these conditions allow for evaluating vaccine prioritization policies within a quasi-experimental design. Despite clear agreement on the goal, state-formulated vaccine distribution plans diverged beyond initial priority groups: some continued prioritizing vaccinations based on mortality risks (i.e., age), while others determined eligibility based on risks of occupational exposure. I leverage this divergence as an identification strategy to test a key insight from network theory: reducing contagion requires disabling the transmission potential of the most connected actors. This strategy is consistent with occupation-based, as opposed to the age-based vaccine prioritization. The analysis of daily Covid-19 data in a matched sample of Oregon and California counties shows strong support for this theory.

Author

• Olga Chyzh, University of Toronto