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Impact of the Exposure Time and Distance Thresholds on the Performance of Automatic Contact Tracing
Published
Author(s)
Brian D. Cloteaux, Vladimir Marbukh, Kamran Sayrafian
Abstract
Automatic exposure notification apps operate based on guidelines that specify distance and time thresholds to measure the occurrence of contacts with infected individuals. In the United States 2 m/15 min thresholds are used to determine exposures due to a close contact. In this paper, using a simplifying approximation for the probability of infection versus exposure time, we provide a mathematical framework to investigate the impact of these thresholds on the performance of the contact tracing system. We consider the number of unnecessary quarantines and the undetected infections as metrics for the system performance. This study is done through an agent-based simulation platform which emulates automatic exposure notification with Bluetooth-based proximity detection. The platform allows for a comprehensive analysis with several user-controlled parameters that can specify different scenarios. Our analysis highlights the trade-off between unnecessary quarantines and undetected infections and would pave the way for the optimization of the exposure thresholds based on factors such as the surrounding environment (e.g., indoor vs. outdoor), an individual's health, the severity of the outbreak in the community, transmissibility of the virus, etc. The ultimate objective is to enhance the effectiveness of automatic contact tracing during pandemics.
Conference Dates
May 28-June 1, 2023
Conference Location
Rome, IT
Conference Title
2023 IEEE International Conference on Communications Workshops (ICC Workshops)
Cloteaux, B.
, Marbukh, V.
and Sayrafian, K.
(2023),
Impact of the Exposure Time and Distance Thresholds on the Performance of Automatic Contact Tracing, 2023 IEEE International Conference on Communications Workshops (ICC Workshops), Rome, IT, [online], https://doi.org/10.1109/ICCWorkshops57953.2023.10283674, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936336
(Accessed October 9, 2025)