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.
@article{arxiv.2111.12825,
title = {Engineering and Implementation of SimAEN},
author = {Gwendolyn Gettliffe and Adam Norige and Ted Londner and Jonathan Saunders and Dieter Schuldt and William Streilein},
journal= {arXiv preprint arXiv:2111.12825},
year = {2021}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2012.04399