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

We combine the estimates above with our data on the timing of hundreds of policy deployments to estimate the total effect to date of all policies in our sample. To do this, we use our estimates above to predict the growth rate of infections in each locality on each day given the policies in effect at that location on that date ( Figure 3 , blue markers). We then use the same model to predict what counterfactual growth rates would be on that date if all policies were removed ( Figure 3 , red), which we refer to as a "no policy" scenario. The difference between these two predictions is our estimated effect that all anti-contagion policies actually deployed had on the growth rate of infections on that date. We estimate that since the beginning of our sample, on average, all anti-contagion policies combined have slowed the average daily growth rate of infections −0.166 per day (±0.015, p < 0.001) in China, −0.276 (±0.066, p < 0.001) in South Korea, −0.158 (±0.071, p < 0.05) in Italy, −0.292 (±0.037, p < 0.001) in Iran, −0.132 (±0.053, p < 0.05) in France and −0.044 (±0.059, p = 0.45) in the US. Taken together, these results suggest that anti-contagion policies currently deployed in the first five countries are achieving their intended objective of slowing the pandemic, broadly confirming epidemiological simulations. We estimate that anti-contagion policies have not yet had a substantial nor significant impact suppressing overall infection growth rates in the US.