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

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org /10.1101/2020.03.22.20040642 doi: medRxiv preprint Figure 4 : Estimated cumulative COVID-19 infections with and without anti-contagion policies. The predicted cumulative number of COVID-19 infections based on each country's actual policy deployments (blue) and in the "no policy" counterfactual scenario (red). Sub-national infection growth rates from Figure 3 are integrated adjusting for SIR system dynamics in each sub-national unit (see Methods). Shaded areas show uncertainty based on 1,000 simulations where estimated parameters are resampled from their joint distribution (dark = inner 70% of predictions; light = inner 95%). Black circles show the cumulative number of reported infections observed in the data. In both scenarios, the sample is restricted to units we analyze in Figures 2 and 3 . Note that infections are not projected for administrative units that never report infections in the data, but which plausibly would have experienced infections in a "no policy" scenario. The jump in infections in France on March 2, 2020 occurs due to administrative units entering the sample. . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.