Title : Estimating the effectiveness of non-pharmaceutical interventions during Covid-19
Abstract:
During the initial outbreak of COVID-19, governments worldwide implemented various non-pharmaceutical interventions (NPIs) to help control the spread of the virus. Our study focused on assessing the impact of these interventions in the United States during the first wave of the pandemic. We conducted three separate analyses. First, a prototypical Bayesian hierarchical model was employed to gauge the effectiveness of five NPIs - gathering restriction, restaurant capacity restriction, business closure, school closure, and stay-at-home order, in the 42 states that experienced over 100 deaths by the end of the wave. The effectiveness of a sixth NPI, the mandate to wear facemasks, was assessed using counterfactual modeling which is a variant of the prototypical Bayesian hierarchical model that allows us to answer the question what if the state had imposed the mandate or not. The third analysis used an advanced Bayesian hierarchical model to evaluate the effectiveness of all six NPIs in all 50 states and the District of Columbia, and thus provide a full-scale estimation of the effectiveness of NPIs and the relative effectiveness of each NPI in the entire USA. Our results reinforce earlier results on the general effectiveness of NPIs in arresting the spread of the disease.
