University of Louisiana Mathematicians Receive Grant to Model COVID-19 Mitigation Measures such as Social Distancing

Apr 26, 2020 | Contact-Tracing, COVID-19, Simulation, Social Distancing

University of Louisiana Mathematicians Receive Grant to Model COVID-19 Mitigation Measures such as Social Distancing

Two University of Louisiana at Lafayette professors, Cameron Browne and Hayriye Gulbudak, received grants from the National Science Foundation to study the impact of social distancing, quarantines, and contact tracing in actually slowing the SARS-CoV-2, the pathogen behind the COVID-19 pandemic. U.S. Sen. John N. Kennedy, R-Louisiana announced the grant as part of the Coronavirus Aid, Relief and Economic Security Act—the CARES Act. Both will employ mathematical modeling, actually simulating real-life situations, to predict the spread of infectious diseases. These models can potentially augment real-world analyses as often health agency decision makers lack complete data sets.

Data Key to Understanding

As communities combat the COVID-19 pandemic and the fight moves toward the effort to not only “flatten the curve” but also pivot and transition toward opening up economies—key activities from ongoing testing programs to contact tracing represent vital steps toward normalcy. In an ideal world all of the data required for superior decision making would be in place but this isn’t of course an ideal world and much data is not available. Hence, the professors note in their NSF proposal that modeling and analysis “can provide important insights into the efficacy of contact-based, non-pharmaceutical interventions” including quarantining, social distancing and contact tracing.

The researchers propose models that incorporate numbers of reported cases and data involving how the virus mutated and migrated in a quest to put together what hopefully will be a more accurate and comprehensive understanding of COVID-19’s effect.

Critical Question: How do we know how well our efforts are working?

For activities such as quarantining, social distancing and even the imminent contact tracing, a fundamental question is posed: how do we know how well these initiatives are protecting us? We are aware that these activities do lessen the spread; the impact of COVID-19 but by how much?

Well their goals are to develop mathematical models that can simulate the real-world scenarios for how to optimize activities to now only flatten, but actually shrink the pandemic curve by employing social distancing and contact tracking—now and in anticipation of forthcoming waves of outbreaks. The pair will access data from China as well.

Lead Research/Investigator

Cameron Browne, PhD

Hayriye Gulbudak, PhD

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