New Approach to Policy Effectiveness for Covid-19 and Factors Influence Policy Effectiveness

Abstract

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.