Social Distancing and Symptom Modeling

(Wojtusiak, Bagchi, Pfoser, Roess, Durbha, Mobahi, Mogharab Nia)

Do people follow social distancing rules?
How do they move during pandemics?
Do they self-quarantine when reporting symptoms?
How to accurately simulate movement in populations?

These are just a few questions this project aims to answer. Our team is engaged an intensive study of how people move during pandemics and if this movement is related to the symptoms they report. We are utilizing machine learning, computational and simulation methods study detailed movements of individuals and simulate whole populations.

The study is currently recruiting volunteer participants from among Mason students, staff and faculty. Without participants, this research is impossible. If you are interested in participating, please sign consent form at https://hi.gmu.edu/distancing2 or contact Dr. Janusz Wojtusiak.

 

This is the only comprehensive study that looks at multiple sources of data on individual level to understand social distancing. GPS data are used to understand macro-level movements. WIFI data are used to understand movements inside buildings. HealthCheck data are used to track symptoms and test results. Finally, survey data are used to understand knowledge and attitudes towards social distancing. This all comes together in a model of individual movement during pandemics.

On the technical side, after several preprocessing steps to eliminate errors in the data, GPS data go through spatiotemporal clustering to discover places that people visit, and model large-scale daily movements. WiFi data are used to model small-scale movements within buildings (also see WiFi contact prediction). Daily symptoms are modeled as time series and linked to the previously processed GPS data.

Some of the early results of the study have been presented at ICHI 2020 conference and later published in health informatics research journal.

References

Wojtusiak, J., Bagchi, P., Durbha, S., Mobahi, H., Mogharab Nia, R. and Roess, A., “COVID-19 Symptom Monitoring and Social Distancing in a University Population,” Journal of Health Informatics Research, 2021.

Wojtusiak, J., Bagchi, P., Durbha, S., Mobahi, H., Mogharab Nia, R. and Roess, A., “COVID-19 Symptom Monitoring and Social Distancing in a University Population,” IEEE International Conference on Healthcare Informatics (ICHI), November, 2020.