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

4. " adm2_name ": If the dataset contains observations at the "Adm2" level, then this is the name of the "Adm2" region to which this observation belongs. 5. " adm [1, 2] _id ": Any alphanumeric ID scheme to identify different administrative units (e.g. FIPS code). 6. " lat ": The latitude of the centroid of the administrative unit. 7. " lon ": The longitude of the centroid of the administrative unit. 8. " policies_enacted ": The number of active policies that are in place for the administrative unit as of that date. This variable is not population weighted. 9. " testing_regime ": A categorical variable used to identify when an administrative region (or country) changed their COVID-19 testing regime. This is zero-indexed, with the ordering only indicating chronological progression (there is no external meaning to Regime 2 vs. Regime 1 vs. Regime 0, and there is no consistency enforced for coding across countries). For example, if China changes their testing regime twice, all observations prior to the first regime change would be coded " testing_regime =0," all observations in between the two changes would be coded " testing_regime =1," and all observations after the second change would be coded " testing_regime =2."