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Impact of Using Soft Exposure Thresholds in Automatic Contact Tracing

Published

Author(s)

Kamran Sayrafian, Brian D. Cloteaux, Vladimir Marbukh

Abstract

Current automatic exposure notification apps primarily operate based on hard distance/time threshold guidelines (e.g., 2 m/15 min in the United States) to determine exposures due to close contacts. However, the possibility of virus transmission through inhalation for distances over the specified distance threshold might necessitate consideration of soft distance/time thresholds to accommodate all transmission scenarios. In this paper, using a simplifying approximation on the instantaneous rate of the viral exposure versus distance, we extend the definition of "contact" by proposing a soft distance/time threshold which includes the possibility of getting exposed at any distance (within certain limits) around an infected person. We then analyze the performance of automatic exposure notification with Bluetooth-based proximity detection by comparing the exposure results when soft or hard thresholds are used. This study is done through an agent-based simulation platform that allows for a comprehensive analysis using several system parameters. By tuning the parameters of the proposed soft thresholds, a more accurate determination of possible exposures at any distance would be possible. This would enhance the effectiveness of an automatic contact tracing system. Our results indicate the noticeable impact of using the soft distance/time threshold on the exposure detection accuracy.
Conference Dates
October 17-19, 2022
Conference Location
Genoa, IT
Conference Title
2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)

Keywords

Proximity Detection, Bluetooth, Exposure Determination, COVID-19, Contact Tracing

Citation

Sayrafian, K. , Cloteaux, B. and Marbukh, V. (2022), Impact of Using Soft Exposure Thresholds in Automatic Contact Tracing, 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom), Genoa, IT, [online], https://doi.org/10.1109/HealthCom54947.2022.9982790, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935550 (Accessed April 23, 2024)
Created December 21, 2022, Updated March 28, 2024