Ranking non-pharmaceutical interventions for SARS-CoV-2 pandemic using Global Sensitivity Analysis

Without an effective pharmaceutical intervention against SARS-CoV-2, policymakers worldwide encourage people to practice social distancing, use face masks and frequent hand washing to control disease transmission. However, implementing all these interventions create a significant socio-economical strain on the general public. Therefore, it is crucial to identify the individual effects of these interventions. In this study, we propose the Global Sensitivity Analysis (GSA) as a tool to rank these non-pharmaceutical interventions and provide a mathematical perspective of the impact of each of these interventions. The mathematical model consists of a compartmental model that includes social distancing and the use of face masks as non-pharmaceutical interventions. Further, the model uses a fear-based behavioral model that leads the transmission from unmasked to masked susceptible compartments. The model parameters are estimated using the reported deaths for the United States of America and Florida. Maximum hospital usage and the total number of deaths are used as the quantity of interest for the GSA. The Sobol indices are used to obtain the rankings of the input parameters.