On Wednesday, August 18, 2021, five researchers studying a wide range of topics on the global pandemic presented their work as part of the ongoing COVID-19 Research Webinar series organized through the COVID Information Commons (CIC). The COVID Information Commons is an NSF-funded project organized by the Big Data Innovation Hubs, led by the Northeast Big Data Innovation Hub at Columbia University.
First, Ali Vahdati (East Carolina University) presented a computational model used for multiscale investigation of regional lung dynamics. Next, Zhenlong Li (University of South Carolina) measured human movement using social media data, ultimately finding that social distancing orders resulted in decreased movement throughout the country. Deborah Salon (Arizona State University) asked whether behavioral changes that occurred as a result of the pandemic would persist even after the COVID-19 era. She created a widespread survey examining the following metrics: employment, working and studying, shopping and dining, transport, attitudes and demographics, and looked into increasing behaviors that people liked during the pandemic, such as walking. Up fourth, Sarah Stahl (University of Pittsburgh) promoted awareness of Prolonged Grief Disorder, explaining how COVID-19 risk factors exacerbated the severity of this condition among those who experienced loss during the pandemic, particularly of older age. Massood Tabib-Azar (The University of Utah) displayed electronic sensors used to detect COVID-19 quickly and effectively. Finally, Samson Qian (University of California, San Diego), the second place winner of the inaugural CIC Student Paper Challenge, presented his research leveraging Explainable Artificial Intelligence to identify pneumonia conditions in chest x-rays.
Individual videos of each of the lightning talks highlighting insights gained from the researchers’ NSF-funded projects are available on the CIC website in the “Meet the Researchers” tab. A full recording of the webinar is also available on the CIC website. A complete playlist of all videos from this event are available on the Hub’s YouTube channel.
After the six presentations, Executive Director of the Northeast Big Data Innovation Hub, Florence Hudson, introduced Orlando Lopez from the NIH, who introduced a new request for Information from the NIH. This new RFI invites input on an initiative to support the development of novel research approaches to tools, technologies, and informative biomarkers or biosignatures, and/or social and behavioral factors that enable the identification of patients or patient populations susceptible to developing post-acute-sequelae of SARS-CoV-2 infection (PASC).
The webinar concluded with a Q & A session where the researchers answered questions from members of our community. We would like to express thanks to our audience for participating in this webinar and for asking insightful questions on the research topics discussed.
The next CIC COVID-19 Research Webinar will be held on Wednesday, September 22nd from 2:30 – 4:00 p.m. (EST). Register to attend the September webinar and hear about other NSF- and NIH-funded research projects concerning COVID-19.
Speaker Lineup for the September CIC Webinar:
Janet Iwasa, University of Utah: Building a visual consensus model of the SARS-CoV-2 life cycle. Funded by NSF Biological Sciences / Division of Molecular and Cellular Biosciences (MCB).
Kristen Miller, MedStar Health National Center for Human Factors in Healthcare: CDC COVID-19 Community Research Partnership. Funded by the NIH / National Library of Medicine.
Jane Pan, Princeton University: Contradiction Detection of COVID-19 Randomized Controlled Trials via BERT Language Models. COVID Information Commons Undergraduate Student Paper Challenge 1st Place Winner.
Franchessa Sayler, ThruPore Technologies: Antiviral Activity of Novel Nitrogen-Doped, Carbon Supported Catalysts Against Covid-19 Surrogates. Funded by NSF Engineering / Industrial Innovation and Partnerships (IIP).
Ponisseril Somasundaran, Columbia University: Novel Foam formulations for decontamination of surfaces with minimum wastewater generation. Funded by NSF Engineering / Division Of Industrial Innovation and Partnerships.
George K. Thiruvathukal, Loyola University Chicago: Leveraging New Data Sources to Analyze the Risk of COVID-19 in Crowded Locations. Funded by NSF Computer and Information Science and Engineering / Office of Advanced Cyberinfrastructure (OAC).
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