Enhancing Infectious Disease Outbreak Surveillance via Bidirectional Contact Tracing

Contact tracing remains essential in mitigating the spread of pandemics (including COVID-19). Specifically, backward contact tracing helps find superspreaders and hidden chains of transmission from asymptomatically infected users. However, most literature proposing contact tracing frameworks and apps deployed by various countries do not attempt backward contact tracing. In this work, we present a novel approach for Bidirectional contact tracing. The proposed approach works using Bluetooth low-energy sensors that detect the presence of users in a vicinity and inform a central backend server of user presence. By fixing BLE-S in buildings, the proposed framework can trace the contacts resulting from contamination of a location ( indirect contacts ). We present two algorithms using which the proposed framework can trace forward and backward contacts. Using a simulation, we also track the spread of infection among different 'Generations' of the infected and the impact of backward tracing on preventing the spread across generations. We observe the effect of critical epidemiological parameters such as the reproduction number (R) and the overdispersion parameter (k) specifically on backward contact tracing efficiency.