A Large-scale Disease Outbreak Analytics System based on Wi-Fi Session Logs

Guilherme Augusto Zagatti, Tingfeng Wu, See-Kiong Ng, Stéphane Bressan

Abstract: Unraveling human mobility patterns is critical for understanding disease spread and implementing effective controls during large-scale disease outbreaks such as the COVID-19 pandemic. Given the urgency associated with such situations, it is important to leverage on the common existing digital infrastructures that can be readily activated for disease outbreak analytics. We introduce an integrated system for disease outbreak investigation using data from Wi-Fi sessions. The system offers outbreak analytics, simulation, and visualization capabilities to assist in the identification of infection hot-spots and in contacttracing exercises. The system has been developed and experimentally deployed for research purposes on a large local university campus in Singapore.