Cross-Correlation plot between the government stringency index and covid severity is the correlation plot between both de-trended time series at different lags of covid severity. This plot helps us understand how long it takes for changes in government stringency measures to take effect on covid severity. The red lines indicates the significance interval, which means correlation values more than that threshold can be considered significant. The plot shows us that there is maximum interaction between covid severity and government response is around the window of 180-200 days. The plot signifies that the government stringency is affected by the covid severity in the country and not vice versa. Thus we can say that any change in covid severity today would cause a change in how stringent the government is 6-7 months down the line.

The above bar graph shows how stringency in various government policies (such as cancelling public events, international travel control etc) affect COVID severity. Each bar represents the relative percentage drop in COVID severity from baseline, while keeping all other factors constant.

For example; high government stringency in policies for cancelling public events would lead to a 55-60% drop in COVID severity from the baseline. We can observe that high government stringency in cancelling public events, controlling international travel, public information campaigns and testing policies leads to a higher decline in the COVID severity.

Hence we can say that in the event of a pandemic in the future, the government should focus on these aspects more first. Our analysis showed that the stringency in vaccination policies and facial covering did not have a very significant impact on the covid severity, thus telling us that breaking the interation between people is the best way to move forward in the case of a pandemic.