RAPID Collaborative proposal: Spatial dynamics of COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2028097
Grant search
Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$124,654Funder
National Science Foundation (NSF)Principal Investigator
Andrew KramerResearch Location
United States of AmericaLead Research Institution
University of South FloridaResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
This project will develop a set of mathematical models of the spread of SARS-CoV-2, the cause of COVID-19. The 2019-2020 global corona virus pandemic is ongoing and poses an unprecedented challenge to the normal movement of people within and between countries. The models developed by this research will provide the means to determine how the risk of transmission varies over time between specific locations and can be combined with other data sources to help determine the primary routes of transmission and the actions that are successful in slowing or halting the spread. These methods are designed to provide initial models with limited data, while allowing for the integration of more robust datasets as they become available. The proposed project will produce information directly applicable to managing the geographic spread of SARS-CoV-2, will inform CDC decisions and responses to the pandemic, and will provide a way to assess changes to importation risk in close to real-time. In addition,the proposed project will contribute to the training of a graduate student and an undergraduate student.
Stochastic spatial models provide the means for determining the time-varying risk of pathogen transmission between specific locations. This project will develop extensions of these models that will be more effective at analyzing and forecasting spatial spread of emerging disease. The project will develop a spatial model that incorporates time-varying cases in each location, including a reliable method for parameterization. It will use those models to estimate the effects of travel restrictions and quarantines on the spread globally and within the U.S. By closely studying the spread at the source of the outbreak it will assess how travel patterns and interventions altered the pandemic trajectory. The models will also assist in identifying areas at greatest risk of importation of new cases when local transmission is controlled. These aims will be accomplished by using publicly available data sources and compiling new information on the timeline of interventions.
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.
Stochastic spatial models provide the means for determining the time-varying risk of pathogen transmission between specific locations. This project will develop extensions of these models that will be more effective at analyzing and forecasting spatial spread of emerging disease. The project will develop a spatial model that incorporates time-varying cases in each location, including a reliable method for parameterization. It will use those models to estimate the effects of travel restrictions and quarantines on the spread globally and within the U.S. By closely studying the spread at the source of the outbreak it will assess how travel patterns and interventions altered the pandemic trajectory. The models will also assist in identifying areas at greatest risk of importation of new cases when local transmission is controlled. These aims will be accomplished by using publicly available data sources and compiling new information on the timeline of interventions.
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.