  We use mobile device data to construct empirical interpersonal physical
contact networks in the city of Portland, Oregon, both before and after social
distancing measures were enacted during the COVID-19 pandemic. These networks
reveal how social distancing measures and the public's reaction to the
incipient pandemic affected the connectivity patterns within the city. We find
that as the pandemic developed there was a substantial decrease in the number
of individuals with many contacts. We further study the impact of these
different network topologies on the spread of COVID-19 by simulating an SEIR
epidemic model over these networks, and find that the reduced connectivity
greatly suppressed the epidemic. We then investigate how the epidemic responds
when part of the population is vaccinated, and we compare two vaccination
distribution strategies, both with and without social distancing. Our main
result is that the heavy-tailed degree distribution of the contact networks
causes a targeted vaccination strategy that prioritizes high-contact
individuals to reduce the number of cases far more effectively than a strategy
that vaccinates individuals at random. Combining both targeted vaccination and
social distancing leads to the greatest reduction in cases, and we also find
that the marginal benefit of a targeted strategy as compared to a random
strategy exceeds the marginal benefit of social distancing for reducing the
number of cases. These results have important implications for ongoing vaccine
distribution efforts worldwide.
