Computation of Infection Risk via Confidential Locational Entries: A Precedent Approach for Contact Tracing With Privacy Protection

Abstract

To effectively mitigate the COVID-19 pandemic, various methods have been proposed to control the infection risk using mobile phone technologies. In this respect, short-range Bluetooth in mobile phones has been mostly used to detect contacts with other devices that approach within a certain range for a specific duration and to notify residents regarding potential contact with infected patients. However, the technology can only detect direct contacts and neglects various modalities of infection, which might have contributed to the pandemic worldwide. In this article, we proposed an approach that evaluates the infection risk for residents, using the locational information of their mobile phones and confidential information of infected patients. The article first outlines the proposed method, the Computation of Infection Risks via Confidential Locational Entries method. Moreover, a comparative evaluation is qualitatively and quantitatively performed against the Bluetooth method. Results highlight the advantages of the proposed method and suggest that it could work in a complementary manner with the Bluetooth method toward effective mitigation of infection risks, while protecting privacy.

Cultural Implications Regarding Privacy in Digital Contact Tracing Algorithms: Method Development and Empirical Ethics Analysis of a German and a Japanese Approach to Contact Tracing

“…The second case is the so-called CIRCLE method. In many Asian countries such as Japan, South Korea, or Taiwan, differing approaches for DCTAs have been discussed and tested as early as 2010 [ 39 ]. The CIRCLE method is one of the young offspring of this family of approaches.…”

CIRO: COVID-19 infection risk ontology

“…The study used RDF to express location information of cases released by local governments to alert residents in the regions. PLOD can provide personalized exposure notification to cell-phone users, by combining mobility information of their devices stored by cell phone carriers without violating the privacy of patients and residents [ 20 ].…”

Contact Tracing Over Uncertain Indoor Positioning Data

“…Contact Tracing. There are two mainstream contact tracing technologies, namely proximity-based solutions [3], [4], [5], [6], [7], [8], [9], [25], [26], [27], [28], [29] and location-based solutions [10], [11], [12], [13], [14], [15], [16], [17], [21].…”

“…Location-based contact tracing methods identify close contact pairs using historical location data instead of wireless proximity information. Different from our work on efficient contact tracing over historical data, many works focus on developing the contact tracer as an administrative web-based system [11], a privacy-enhanced mobile application [10], [12], [15], or a decentralized Blockchain-based system [16]. Several works [13], [14], [17] consider the efficiency of close contact search.…”

“…However, these methods need to install apps on devices, and they do not consider spatial information and thus fail to customize close contact criteria. There also exist location-based contact tracing methods [10], [11], [12], [13], [14], [15], [16], [17] that find spatially close people based on their spatial distances in the historical times. However, these methods mainly focus on outdoor spaces and neglect the indoor topology in our problem setting.…”