COVID-19 RAPID: Decision Making Outside of Medical Facilities During Pandemic

灾害记录传统上被认为是一个单一的地点，事件后的活动，但越来越多的人认识到灾害可以在相对较短的时间内影响多个社区，并且随着威胁跨越社区，了解人口的近实时反应具有重要价值。为此，本研究将利用实地观察员在11个国内和5个国际地点收集与离开COVID-19医疗机构的个人街头行为相关的易腐数据，为期2个月。这些文件将包括性别、触摸行为、口罩使用情况、目的地和交通选择。通过重新访问2020年春季研究中记录的9周以上的医疗机构子集，将为该研究中记录最多的8个地点生成关键的纵向数据，并将该方法扩展到其他3个美国城市和3个国外城市的5家医院，可以开始测试该方法在不同文化和社区中的稳健性。鉴于疾病在国内和国际上不同社区的传播，这一更广泛的数据集对于制定在美国遏制COVID-19的战略尤为重要。该项目预计将收集14,000多份医疗设施外与COVID-19相关的行为记录。该项目还将调查使用标准化软件和协议是否能够向国际社会提供接近实时的个人空间行为数据。最后，该项目将考虑通过3种不同的方式远程部署学生研究人员：(1)使用虚拟协调器在远离主校区的家庭地点（国内和国外）雇用机构的学生；(2)利用美国大学海外分校的资源；(3)利用在海外运营的非美国大学的资源。培训、协调、部署和数据收集问题将根据难度、有效性和质量进行评估。该项目将培训29名年轻研究人员进行新颖的实地考察，并将其转化为与COVID-19相关的独特、高可用性信息的公共数据集。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.