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DTSTART;TZID=America/New_York:20260924T104000
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DTSTAMP:20260918T172826Z
CREATED:20260824T222944Z
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UID:2329-1790246400-1790249400@biomath.math.ufl.edu
SUMMARY:Toni Gui (UF\, Biostatistics)
DESCRIPTION:Incorporating Genomic Sequences into Stochastic Transmission Modeling to Improve the Analysis of SARS-CoV-2 Transmission Dynamics \nThe SARS-CoV-2 pandemic has highlighted the growing importance of infectious disease analysis. An accurate and robust model can empower public health leaders to make timely decisions on social distancing and vaccination policies\, thereby reducing the number of cases\, hospitalizations and deaths. However\, the emergence of new variants and subvariants can significantly alter the transmissibility\, immune escape capacity and virulence of the pathogen in a short time\, making the number of cases\, hospitalizations and deaths difficult to predict. To enhance the timeliness and accuracy of forecasting\, SARS-CoV-2 sequencing data can be utilized. These data constitute a vast and continuously growing resource\, with millions of sequences collected and reported over the past few years. By incorporating the evolution of SARS-CoV-2 virus into classic transmission models\, we conclude that genomic data is crucial for capturing trends in epidemiological data when new variants and subvariants emerge\, leading to the development of a more reliable model and enhancing our knowledge of transmission dynamics and control.
URL:https://biomath.math.ufl.edu/event/dr-toni-gui-university-of-florida-biostatistics-department/
LOCATION:423 Little Hall
CATEGORIES:Fall 2026
ATTACH;FMTTYPE=image/jpeg:https://biomath.math.ufl.edu/wp-content/uploads/sites/607/Toni-e1787606205641.jpeg
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