Guest Post: Kenia Pujols
Keywords: Pandemic, virtual reality, health, data science, mandates, government, collaboration, diagnostics, depression, social isolation, learning, COVID-19.
A recording of this event is available on the Northeast Big Data Innovation Hub’s YouTube Channel and the COVID Information Commons website at covidinfocommons.net. The COVID Information Commons is an NSF-funded project brought to you by the Big Data Innovation Hubs, led by the Northeast Big Data Innovation Hub at Columbia University.
The March 2022 COVID Information Commons (CIC) webinar took place on March 4th, 2022. In this forum, leading COVID-19 scientists funded by the NSF presented their current research on the global pandemic. Florence Hudson, Executive Director of the Northeast Big Data Innovation Hub at Columbia University and COVID Information Commons Principal Investigator (PI), and Kenia Pujols, CIC Program Manager, moderated the discussion. The researchers presented a wide variety of topics, each touching on broader themes related to the COVID-19 pandemic. All four projects are funded by the National Science Foundation (NSF).
The first speakers, Yifeng Cai and Kate Mason from Brown University, presented their research Understanding the Process of Social Change through the Transitional Period of the COVID-19 Pandemic.
Yifeng Cai and Kate Mason from Brown University studied how over a billion people in China were capable of complying with some of the strictest COVID control measures in the world for a long period of time. They noted that once the COVID-19 outbreak emerged, the Chinese government mandated mask-wearing and mobilized a tracking application called Health Code as early as April 2020. The population selected for this research included people from diverse backgrounds and socioeconomic statuses from Shanghai. The methods to gather data were through interviews and social media posts. The results showed that Chinese people complied with strict measures because they felt they needed to protect their families, the economy, and their own financial futures in the long term. Strong nationalist pride was also a contributing factor in their decision-making. For this reason, people trusted the government and followed their directives even if the information provided to them was considered incomplete. You can watch the video and read an English transcript of their talk here.
Next, Joe Cecil from Oklahoma State University shared insights about his research: A Virtual Reality simulator to train first responders involved in health care efforts related to the COVID-19 virus outbreak.
Joe Cecil and other researchers noticed a shortage of nurses along with the social distancing mandates restrictions and wanted to create cyber-based training which would be always available to use regardless of the timing. The objective was to increase the number of first responders who were fully trained to do COVID testing. This study produced a 3D environment with virtual reality where trainees can wash their hands, put on personal protective equipment, and take samples in different virtual rooms. They added distractions to simulate a real in-person environment and an immersive full training module. This training helped to increase the trainee’s skills and knowledge. with virtual reality. You can watch the video and read an English transcript of the talk here.
Next, Maria Jose Miguez from Florida International University talked about the Lateral flow home-use diagnostic for detection of COVID-19.
Maria Jose Miguez shared that the high rate of false COVID at-home test results prompted her to propose the development of another COVID test, which is a 5th Generation Combo Antigen/Antibody test. They began their study in Florida and are now following 400 individuals. They were able to detect more COVID cases with their testing technique. In order to understand why this new test was detecting more cases, they went back to the animal models to try to replicate the study. More details will be shared once the study has progressed to more advanced phases. You can watch the video and read an English transcript of her talk here.
The last speakers, Lilian Azer and Rachel Wu from the University of California-Riverside discussed the results of their research on Older adults’ learning and adaptation as resilience processes to counter social isolation during the COVID-19 pandemic.
Lilian Azer and Rachel Wu described the results from their first wave of data on subjective executive functioning and skill learning during the pandemic and how it may predict mental health outcomes. While social distancing measures reduce the probability of getting infected with COVID-19, less social interaction leads to a greater risk of perceived loneliness. Despite the popularity of virtual interactions during the pandemic, older adults may have not been able to use such resources for social interaction due to the digital divide. Another way to engage people during the lockdown is by encouraging learning a new skill or participating in leisure activities. These activities are associated with a lower prevalence of perceived loneliness and depressive symptoms. Surprisingly, the researchers found that participants who spent more time learning new behaviors or skills were predicted to report more symptoms of depression. This finding is worth exploring in other research studies. You can watch the video and read an English transcript of their talk here.
Following the fantastic presentations, Florence Hudson and Kenia Pujols hosted a Q&A session where the audience engaged in a rich discussion with the researchers. These talks offered great insights about attitudes toward government mandates outside the U.S., virtual reality models being applied to health care, new COVID tests, and the prediction of mental health outcomes during the pandemic. Moreover, PIs shared datasets, tools, and techniques with the research community to build collaborations and find immediate answers to the needs of our population. Visit our website to find more details about the researchers.
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