Data-driven assessment of the effectiveness of non-pharmaceutical interventions on Covid spread mitigation in Italy

Abstract

To mitigate the impact of pandemics such as COVID-19, governments can implement various Non-Pharmaceutical Interventions (NPIs), ranging from the use of personal protective equipment to social distancing measures. While it has been demonstrated that NPIs can be effective over time, the assessment of their efficacy and the estimation of their cost-benefit ratio are still debated issues. For COVID-19, several authors have used case confirmation as a key parameter to assess the efficacy of NPIs. In this paper, we compare the efficacy of this parameter to that of the death rate, hospitalizations, and intensive care unit cases, in conjunction with human mobility indicators, in evaluating the effectiveness of NPIs. Our research uses data on daily COVID-19 cases and deaths, intensive care unit cases, hospitalizations, Google Mobility Reports, and NPI data from all Italian regions from March 2020 to May 2022. The evaluation method is based on the approach proposed by Wang et al., in 2020 to assess the impact of NPI efficacy and understand the effect of other parameters. Our results indicate that, when combined with human mobility indicators, the mortality rate and the number of intensive care units perform better than the number of cases in determining the efficacy of NPIs. These findings can assist policymakers in developing the best data-driven methods for dealing with confinement problems and planning for future outbreaks.