  The rapid early spread of COVID-19 in the U.S. was experienced very
differently by different socioeconomic groups and business industries. In this
study, we study aggregate mobility patterns of New York City and Chicago to
identify the relationship between the amount of interpersonal contact between
people in urban neighborhoods and the disparity in the growth of positive cases
among these groups. We introduce an aggregate Contact Exposure Index (CEI) to
measure exposure due to this interpersonal contact and combine it with social
distancing metrics to show its effect on positive case growth. With the help of
structural equations modeling, we find that the effect of exposure on case
growth was consistently positive and that it remained consistently higher in
lower-income neighborhoods, suggesting a causal path of income on case growth
via contact exposure. Using the CEI, schools and restaurants are identified as
high-exposure industries, and the estimation suggests that implementing
specific mobility restrictions on these point-of-interest categories are most
effective. This analysis can be useful in providing insights for government
officials targeting specific population groups and businesses to reduce
infection spread as reopening efforts continue to expand across the nation.
