Disaster documentation has traditionally been considered a single location, post-event activity, but increasingly there is the recognition that disasters can impact multiple communities over a relatively short period of time and that there is significant value in understanding in near real-time the population’s response, as a threat moves across communities. To this end, this study will use on-the-ground observers to capture perishable data at 11 domestic and 5 international locations for 2 months related to street-level behavior of individuals leaving COVID-19 medical facilities. The documentation will include gender, touch behavior, mask usage, and destination and transportation choices. By revisiting a subset of healthcare facilities documented over 9 weeks in the Spring 2020 study, critical longitudinal data will be generated for that study’s 8 most documented site, and by extending the approach to 3 other US cities and 5 hospitals in 3 foreign cities, the approach’s robustness across different cultures and communities can begin to be tested. Given the spread of disease across different communities both nationally and internationally, this broader set of data will be especially important in addressing strategies for containing COVID-19 across the U.S.
This project is expected to collect 14,000+ records on COVID-19 related behaviors outside of medical facilities. This project will also investigate whether the use of standardized software and protocols can enable delivery to the world community near real-time individual, spatial behavioral data. Finally, the project will consider the remote deployment of student researchers through 3 different means: (1) hiring an institution’s students at home locations (domestic and foreign) away from the main campus using a virtual coordinator; (2) using resources at an American University operating an overseas campus; and (3) using resources at a non-American University operating overseas. Training, coordination, deployment, and data harvesting issues will be evaluated in terms of difficulty, effectiveness, and quality. This project will train 29 young researchers in novel fieldwork, which will translate into a unique, public dataset of high usability information related to COVID-19.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
