The COVID-19 crisis has produced worldwide changes from people's lifestyles to travel restrictions imposed by world's nations aiming to keep the virus out. Several countries have created digital information applications to help control and manage the COVID-19 crisis, such as the creation of contact tracing apps. The Peruvian government in collaboration with several institutions developed PerúEnTusManos, an epidemiological tracing application. The application uses georeferencing to study users' movements and creates individual mobility patterns from the Peruvian citizens as well as detects crowds. In this article, we present a process to detect possible infected individuals based on probabilities assigned to people that had contact with someone who tested positive for COVID-19, using data collected from PerúEnTusManos. The preliminary evaluation shows promising results when detecting probabilities of possible infected individuals as well as the most infected districts in Peru. The ultimate goal of the application in Peru is to provide reliable information to health authorities to make informed decisions about the assignations of the available clinical tests and the economic re-activation.
|Title of host publication
|Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
|Taesung Park, Young-Rae Cho, Xiaohua Tony Hu, Illhoi Yoo, Hyun Goo Woo, Jianxin Wang, Julio Facelli, Seungyoon Nam, Mingon Kang
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 16 Dec 2020
|IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Corea del Sur
Duration: 1 Dec 2020 → 1 Dec 2020
|IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
|1/12/20 → 1/12/20
Bibliographical notePublisher Copyright:
© 2020 IEEE.
- Peru' EnTusManos
- contact tracer
- mobility markov chains
- mobility model