I-Corps: A spatiotemporal simulation system to predict COVID-19 case trajectories in schools
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2138914
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Key facts
Disease
COVID-19Start & end year
20212022Known Financial Commitments (USD)
$50,000Funder
National Science Foundation (NSF)Principal Investigator
Chaowei YangResearch Location
United States of AmericaLead Research Institution
George Mason UniversityResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
Innovation
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Adults (18 and older)
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
The broader impact/commercial potential of this I-Corps project is to enable safe reopening of college campuses and school systems, as well as companies and other organizations with a campus setting after the COVID-19 crisis. Due to the sudden outbreak of COVID-19, college campuses and school systems were shut down globally to slow down the spread of the disease. Despite being largely successful in controlling the spread of COVID-19, school closings caused health problems, including physical and psychological stresses, for students, staff, and faculty in addition to direct economic impacts. This project develops a system to better support school re-openings with specific policies based on scientific data and information. The potential product can simulate the trajectory of COVID-19 cases and provide potential customers with a reliable method to scientifically monitor the status of their campuses. This product has the potential to be used globally and also can be used to manage large events with a focused gathering site setting.
This I-Corps project is based on a spatiotemporal simulation/prediction system developed to address the urgent campus reopening questions caused by the COVID-19 pandemic. The system integrates investigation on spatiotemporal infrastructure including big data, cloud computing, analytics, and community outreach. Human behavior simulation, campus spatiotemporal dynamics, and public health data are combined to predicate possible viral case trajectories. The novel spatiotemporal simulation integrates agent-based people movement and public health risks as well as control policies (such as mask mandates, classroom size restrictions, test and tracking, and vaccination status) to derive accurate predictions. The system has been validated using data from several college campuses.
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 I-Corps project is based on a spatiotemporal simulation/prediction system developed to address the urgent campus reopening questions caused by the COVID-19 pandemic. The system integrates investigation on spatiotemporal infrastructure including big data, cloud computing, analytics, and community outreach. Human behavior simulation, campus spatiotemporal dynamics, and public health data are combined to predicate possible viral case trajectories. The novel spatiotemporal simulation integrates agent-based people movement and public health risks as well as control policies (such as mask mandates, classroom size restrictions, test and tracking, and vaccination status) to derive accurate predictions. The system has been validated using data from several college campuses.
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.