RAPID: Tackling the Psychological Impact of the COVID-19 Crisis
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2027689
Grant search
Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$199,871Funder
National Science Foundation (NSF)Principal Investigator
Munmun De ChoudhuryResearch Location
United States of AmericaLead Research Institution
Georgia Tech Research CorporationResearch Priority Alignment
N/A
Research Category
Policies for public health, disease control & community resilience
Research Subcategory
Communication
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Computer and Information Science and Engineering - The physical isolation of shelter-in-place, as demanded during the ongoing COVID-19 pandemic, stresses psychological well-being. It pushes people to connect via social media. While social media platforms enable online connection, they can sensationalize some narratives and ignore others, fomenting anxiety and fear. This project will use artificial intelligence to analyze social media data and model psychological wellbeing, distress, and vulnerability. It will provide tools to help understand community social anxiety in relationship to nearby COVID-19 outbreaks. The outcomes of this work have the potential to support public health organizations in (1) responding to the psychological needs and demands of communities affected by the COVID-19 crisis in a timely and proactive fashion; and (2) brainstorming strategies to counter experiences of COVID-19 related anxiety and improve people?s quality of life through resource allocation and prioritization.
This project will assess COVID-19 pandemic impacts and improve the nation?s resilience by: (1) developing data- and theoretically-driven scientific computational methods to identify social media based linguistic and social network markers associated with COVID-19 crisis-related anxiety, stress, and other downturns in psychological wellbeing in affected communities within the United States; (2) developing predictive models to forecast which communities will be most vulnerable to these psychological downturns; (3) leveraging epidemiological models of disease spread to derive holistic views of communities? online activity and their offline spatiotemporal geographical context in relationship to their proximity to the virus; (4) conducting a human-centered evaluation; and (5) providing data, an open-source toolkit, and data-driven presentations of how particular communities are vulnerable to the COVID-19 pandemic to support public health workers and the general public in creating timely and proactive interventions. On the whole, through the iterative involvement of transdisciplinary domain experts, new computational artifacts will transform the COVID-19 response, taking into account the larger sociotechnical context of the crisis.
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.
This project will assess COVID-19 pandemic impacts and improve the nation?s resilience by: (1) developing data- and theoretically-driven scientific computational methods to identify social media based linguistic and social network markers associated with COVID-19 crisis-related anxiety, stress, and other downturns in psychological wellbeing in affected communities within the United States; (2) developing predictive models to forecast which communities will be most vulnerable to these psychological downturns; (3) leveraging epidemiological models of disease spread to derive holistic views of communities? online activity and their offline spatiotemporal geographical context in relationship to their proximity to the virus; (4) conducting a human-centered evaluation; and (5) providing data, an open-source toolkit, and data-driven presentations of how particular communities are vulnerable to the COVID-19 pandemic to support public health workers and the general public in creating timely and proactive interventions. On the whole, through the iterative involvement of transdisciplinary domain experts, new computational artifacts will transform the COVID-19 response, taking into account the larger sociotechnical context of the crisis.
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.