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.

Keywords

• Contact tracing
• privacy protection
• mobile phones
• location
• infection risks