PERSONICLE for tracking COVID-19 infection

Remote social interaction monitoring to predict the risk of novel coronavirus infection in the UCI community

Remote social interaction monitoring to predict the risk of novel coronavirus infection in the UCI community Contact Person:

Daniel Parker

Other PIs/Investigators/PhD students:

Ramesh Jain
Amir Rahmani
Nikil Dutt
Sanghyuk Shin
Saahir Khan

Project Summary:

In this project, we will investigate how COVID-19 risk is shaped by social contacts and geographic activity spaces in the University of California, Irvine (UCI) community. We hypothesize that there will be fatigue associated with social distancing efforts over time, whereby people cease to isolate themselves from others, resulting in a growth in the average number of social contacts and in the geographic spaces that are traversed daily. We also hypothesize that this eventual expansion of human contacts will result in an increased risk of acquiring COVID-19, relating directly to the number of contacts and the size of the activity space of individuals. We will use smart multi-modal personal lifelogging and remote monitoring technology, Personicle, together with wearable sensors for this purpose.