Detecting Regions At Risk for Spreading COVID-19 Using Existing Cellular Wireless Network Functionalities

• Published in: IEEE open journal of engineering in medicine and biology Vol. 1; pp. 187 - 189
• Main Authors: Alsaeedy, Alaa A. R., Chong, Edwin K. P.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical engineering; Cellular communication; Cellular networks; Coronaviruses; COVID-19; Density; Disease transmission; Handover; infectious diseases; Privacy; Risk; Risk management; tracking; Wireless networks
• ISSN: 2644-1276; 2644-1276
• DOI: 10.1109/OJEMB.2020.3002447

Goal: The purpose of this article is to introduce a new strategy to identify areas with high human density and mobility, which are at risk for spreading COVID-19. Crowded regions with actively moving people (called at-risk regions) are susceptible to spreading the disease, especially if they contain asymptomatic infected people together with healthy people. Methods: Our scheme identifies at-risk regions using existing cellular network functionalities- handover and cell (re)selection-used to maintain seamless coverage for mobile end-user equipment (UE) . The frequency of handover and cell (re)selection events is highly reflective of the density of mobile people in the area because virtually everyone carries UEs. Results: These measurements, which are accumulated over very many UEs, allow us to identify the at-risk regions without compromising the privacy and anonymity of individuals. Conclusions: The inferred at-risk regions can then be subjected to further monitoring and risk mitigation.