Engineering and Implementation of SimAEN

11/24/2021
by   Gwendolyn Gettliffe, et al.
0

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.

READ FULL TEXT

page 22

page 33

page 34

page 35

research
02/10/2021

Epidemiological and public health requirements for COVID-19 contact tracing apps and their evaluation

Digital contact tracing is a public health intervention. It should be in...
research
05/27/2020

CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing Effort

Governments around the world have become increasingly frustrated with te...
research
07/15/2021

Public Health, Technology, and Human Rights: Lessons from Digital Contact Tracing

To mitigate inefficiencies in manual contact tracing processes, Digital ...
research
08/11/2020

Comparing manual contact tracing and digital contact advice

Manual contact tracing is a top-down solution that starts with contact t...
research
05/23/2019

Nature-Inspired Computational Model of Population Desegregation under Group Leaders Influence

This paper presents an agent-based model of population desegregation and...
research
03/11/2021

Preventing Extreme Polarization of Political Attitudes

Extreme polarization can undermine democracy by making compromise imposs...

Please sign up or login with your details

Forgot password? Click here to reset