Funding Source
National Science Foundation (NSF), 2031546
Project Period
7/1/20 – 6/30/22
Principal Investigator
Temiloluwa Prioleau, PhD (Dartmouth College)
Other Project Staff
Kang Gu
Project Summary
At its core, this RAPID project aims to develop and leverage datasets to advance investigations on COVID-19 and inform existing knowledge gaps about the pandemic. This will be achieved through three aims: 1) develop and deploy a data collection platform for collating experiential data from persons who have recovered from COVID-19, including a population of Black Americans to elucidate insights on health disparities, 2) develop computational tools to transform unstructured and distributed data from reputable online sources into a machine-readable format on a centralized platform for research, 3) apply data analytics methods to the above datasets to discover insights about contraction, transmission, severity, coping strategies, and much more. This research has potential to advance science and engineering through data-driven investigations that can increase knowledge on the COVID-19 and enable greater understanding of health disparities associated with the pandemic. Such knowledge can have a profound impact nationally and globally given the large footprint of the virus.
Public Health Relevance
Comprehensive knowledge about the novel coronavirus is significantly hampered by sparsity and in many cases a complete absence of data about the millions of people who have been affected. There are still many unanswered questions about symptoms, transmissibility, severity, treatment, and recovery. In addition, it is not fully understood why COVID-19 disproportionately affected certain racial and ethnic populations in the United States. This project aims to improve collective understanding of COVID-19 incidences by collating and learning from the first-hand experiences of survivors. The large majority of whom are amongst the affected individuals that journeyed through their illness in isolation with little to no medical guidance due to limitations in testing and overburdening of healthcare facilities. This project is advancing science by building experiential datasets on COVID-19 to support further research, helping the society at-large understand the different facets of the virus, and training a next generation of data and computer scientists.