Measuring Public Policy Effectiveness in the Age of Data and AI: Insights from COVID-19

Countries have implemented non-clinical measures to control the transmission of COVID-19, instigating high socio-economic costs. Therefore, the impact of these policies needs to be assessed appropriately. We propose a methodology inspired by event study analysis in econometrics to quantify the effect of the initial major COVID-19 non-clinical interventions, i.e., nationwide school closure and lockdown, across 7 European countries. We focus on the first implementation of these policies as the initial response to a pandemic is critical for controlling disease spread and providing robust evidence for government action and policy decision-making at the earliest pandemic stage. Besides an average mobility reduction of 7.5% (±7.0) after school closure and 13.6% (±12.1) after lockdown, we found a higher percentage of overall mobility reduction in countries that implemented lockdown within five days of school closure. COVID-19-related fatalities were significantly lower in countries that took school closure and lockdown measures at the earliest stage of the pandemic. The close succession of school closures and lockdown policies impacts mobility, lowering COVID-19-related cases and deaths. The lockdown has nearly as double an impact as the school closure impacts on mobility. This implies that the implementation of school closure policies by itself cannot be used as a replacement for the lockdown policy. Our findings provide important insight into how government policies should be shaped and implemented in future pandemics similar to COVID-19.