Engineering and Implementation of SimAEN

TL;DR

SimAEN is an agent-based simulation tool designed to help public health officials understand and evaluate the impact of Automated Exposure Notification and manual contact tracing on controlling COVID-19 spread.

Contribution

This paper introduces SimAEN, a configurable simulation platform that models interactions between individuals and public health systems to assess intervention strategies.

Findings

SimAEN can simulate various public health intervention scenarios.

The model incorporates over 70 adjustable parameters.

SimAEN helps optimize AEN sensitivity settings.

Abstract

This paper presents SimAEN, an agent-based simulation whose purpose is to assist public health in understanding and controlling AEN. SimAEN models a population of interacting individuals, or 'agents', in which COVID-19 is spreading. These individuals interact with a public health system that includes Automated Exposure Notifiation (AEN) and Manual Contact Tracing (MCT). These interactions influence when individuals enter and leave quarantine, affecting the spread of the simulated disease. Over 70 user-configurable parameters influence the outcome of SimAEN's simulations. These parameters allow the user to tailor SimAEN to a specific public health jurisdiction and to test the effects of various interventions, including different sensitivity settings of AEN.