Quantifying and comparing the impact of combinations of non-pharmaceutical interventions on the spread of COVID-19

Abstract

In this paper, we quantify the impact of non-pharmaceutical interventions (NPIs) on the spread of COVID - both individually and in various combinations. We utilize the previously developed Pan-Sim agent-based model to accurately capture various aspects of the epidemic and the interventions and show how the transmission rate (β) commonly used in compartmental ODE models can be matched to the agent-based model and used to compare interventions. Through a specific example of targeting a desired level of peak hospitalization, we give several equivalent intervention packages that can be imposed at various times during a single wave to achieve this goal. By mapping out the effect of different combinations of interventions on the transmission rate, we pave the way for coupling the PanSim model with advanced feedback control.