  This study compared the effectiveness of COVID-19 control policies, including
wearing masks, and the vaccine rates through proportional infection rate in 28
states of the United States using the eSIR model. The effective rate of
policies was measured by the difference between the predicted daily infection
proportion rate using the data before the policy and the actual daily infection
proportion rate. The study suggests that both mask and vaccine policy had a
significant impact on mitigating the pandemic. We further explored how
different social factors influenced the effectiveness of a specific policy
through the linear regression model. Out of 9 factors, the population density,
number of hospital beds per 1000 people, and percent of the population over 65
are the most substantial factors on mask policy effectiveness, while public
health funding per person, percent of immigration have the most significant
influence on vaccine policy effectiveness. This study summarized the
effectiveness of different policies and factors they associated with. It can be
served as a reference for future covid-19 related policy.
