The impact of COVID pandemic has varied globally over geography and time, as measured by number of cases and deaths, depending on demographics of the local population as well as the public health policies implemented in response. One such policy response has been is usage of masks or face covering. Its usage has been very controversial in US due to perceived impingement over individual freedom.
This programme can be used to understand the impact of mask policies at local and national scale. Internally, the tool uses data about COVID19 cases and mask adherence and also applies the emerging technique of Robust Synthetic Control (RSC) (Amjad, Shah, and Shen 2018) to give counterfactual insights about how similar regions with different mask decisions diverged in COVID19 case count.
COVID19 cases by counties, as per (NYTimes 2020)
The user inputs the state and the target county, along with the time period in question. In preprocessing, counties of the same state with similar trend in Covid cases are considered for the donor pool. The final donor pool will be the target value + counties that did not enact mask mandates. After which RSC is performed to give a counterfactual scenario, where masks were not made mandatory and estimate the percentage difference in the number of Covid cases.