An agent-based tool for impact assessment of non-pharmaceutical interventions against COVID-19
Abstract
Non-Pharmaceutical Interventions (NPI) are currently the only mechanism governments can use to mitigate the impact of the COVID-19 epidemic. Similarly, to the actual spread of the disease, the dynamics of the contention patterns emerging from the application of NPIs are complex and depend on interactions between people within a specific region as well as other stochastic factors associated to demographic, geographic, political and economical conditions. Agent-based models simulate microscopic rules of simultaneous interactions of multiple agents within a population in an attempt to reproduce the complex dynamics of the effect of the contention measures. In this way it is possible to design individual behaviors along with NPI scenarios, measuring how the simulation dynamics is affected and therefore, yielding rapid insights to perform a broad assessment of the potential of composite interventions at different stages of the epidemic. In this paper we describe a model and a tool to experiment with this kind of analysis, considering a number of widely-applied NPIs such as social distancing, case isolation, home quarantine, total lockdown, sentinel testing, mask wearing and a novel “zonal” enforcement requiring these interventions to be applied gradually to separated districts (zones). The choice of the most adequate interventions, or mixture of interventions, ultimately will depend on the socio-economic and health conditions of a particular territory and on further large-scale simulation and feasibility estimation of those scenarios yielding a potential mitigation impact, using the insights discovered with the simulation tool.
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