A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys

Hagai Rossman; Ayya Keshet; Smadar Shilo; Amir Gavrieli; Tal Bauman; Ori Cohen; Ran Balicer; Benjamin Geiger; Yuval Dor; Eran Segal

Although our approach has many possible clinical implications, we have so far encountered several challenges. Asking participants to fill the survey may raise issues of information privacy related to the collection of medical data, to avoid any privacy issues that may occur, our survey is filled anonymously. Moreover, since our survey is anonymous we cannot link the same responder's daily questionnaires, which can provide an individual trend as we proceed. However, our goal is to provide a macro-management tool which is still feasible. Finally, a main challenge when relying on this data is that it is prone to selection bias. We notice that regions with relatively high response rate are regions associated with higher socioeconomic status. It may also be assumed that people who answer these surveys tend to be more adherent to healthcare protocols and thus less likely to be infected. While some bias may decrease as these surveys become more popular and known and thus better reflect the true population, we intend to model and adjust for different factors such as age and location.