The Effect of Large-Scale Anti-Contagion Policies on the Coronavirus (COVID-19) Pandemic

Solomon Hsiang; Daniel Allen; Sebastien Annan-Phan; Kendon Bell; Ian Bolliger; Trinetta Chong; Hannah Druckenmiller; Andrew Hultgren; Luna Yue Huang; Emma Krasovich; Peiley Lau; Jaecheol Lee; Esther Rolf; Jeanette Tseng; Tiffany Wu

Policy Data Policies in administrative units were coded as binary variables, where the policy is coded as either 1 (after the date that the policy was implemented, and before it is removed) or 0 otherwise, for the affected administrative units. There were instances when a policy implementation only affected a portion of the administrative units (e.g. half of the counties within the state). In an attempt to accurately represent the locality and impact of policy implementation, policy variables were weighted by the percentage of population within the administrative unit that was treated by the policy. The most recent estimates available of population data for countries' administrative units were used (see the Population Data section in the Appendix). Additionally, in order to standardize policy types across countries, we mapped country-specific policies to one of our broader policy categories used as variables in our analysis. In this exercise, we collected 130 policies for China, 37 for South Korea, 195 for Italy, 26 for Iran, 59 for France, and 498 for the United States (see Appendix Table A1 ).