COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing

Prateek Gupta*, Tegan Maharaj*, Martin Weiss*, Nasim Rahaman*, Hannah Alsdurf**, Abhinav Sharma**, Nanor Minoyan**, Soren HarnoisLeblanc**, Victor Schmidt, Pierre-Luc St. Charles, Tristan Deleu, AndrewWilliams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Ga ́etan Marceau Caron, PierreLuc Carrier, Satya Ortiz-Gagn ́e, Marc-Andre Rousseau, David Buckeridge et al. (9 additional authors not shown)

Keywords: Digital contact tracing, Agent-based model, COVID-19 pandemic

TL;DR: We propose the agent-based compartmental simulator COVIsim and demonstrate its use by comparing a Feature-based Contact Tracing (FCT) method and Binary Contact Tracing method.

Abstract:

Background: The rapid global spread of COVID-19 has led to an unprecedented demand for effective methods to mitigate the spread of the disease, and variousdigital contact tracing (DCT) methods have emerged as a component of the solution.In order to make informed public health choices, there is a need for tools whichallow evaluation and comparison of DCT methods.
Methods: We introduce an agent-based compartmental simulator we call COVIsim, integrating detailed consideration of virology, disease progression, social contact networks, and behaviour/mobility patterns, based on parameters derived from empirical research. We verify by comparing to real data that COVIsim is able to reproduce realistic COVID-19 spread dynamics, and perform a sensitivity analysis to verify thatthe relative performance of contact tracing methods are consistent across a range of settings. We use COVIsim to perform cost-benefit analyses comparing no DCT to: 1) standard binary contact tracing (BCT) that assigns binary recommendationsbased on binary test results; and 2) a rule-based method for feature-based contact tracing (FCT) that assigns a graded level of recommendation based on diverse individual features.
Findings: We find all DCT methods consistently reduce the spread of the disease, and that the advantage of FCT over BCT is maintained over a wide range of adoption rates. Feature-based methods of contact tracing avert more disability-adjusted life years (DALYs) per socioeconomic cost (measured by productive hours lost).
Interpretation: This research provides a useful testbed to compare and optimize real-world implementations of contact tracing (CT) schemes, a first step in re-sponsible and informed use of CT as an epidemic intervention tool. Our results suggest any DCT method can help save lives, support re-opening of economies, and prevent second-wave outbreaks, and that FCT methods are a promising direction for enriching BCT using self-reported symptoms, yielding earlier warning signals and a significantly reduced spread of the virus per socioeconomic cost.