Title: Genomic Epidemiology in SARS-CoV-2: new tools and challenges 

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Abstract: Scientists around the world have sequenced over 2 million SARS-CoV-2 genomes in an effort to monitor and understand the evolution and transmission of this virus. Virus sequences can help us understand the emergence of new variants with new phenotypes, track the virus' geographical movements and can help us to understand local transmission. However, there are mathematical and statistical challenges in making the most of this potentially rich source of information about viruses and how they spread.  In this talk I will introduce the field of genomic epidemiology in general, and then describe recent research in our group.  We have developed a method to use SARS-CoV-2 genomes to estimate serial intervals: the time between symptoms (or in some cases, sample collection) in infector-infectee pairs. Serial intervals are important because they underlie estimates of the reproductive number, Rt, which in turn is used to help understand the strength of transmission and the impact of different levels of vaccine coverage. I will describe the results of this method applied to data from Victoria, Australia. I will conclude by noting some broader challenges and opportunities for the genomic surveillance of SARS-CoV-2. 

About AI4PAN Artificial Intelligence for Pandemics Seminar Series centred at UQ

Welcome to AI4PAN, the Artificial Intelligence for Pandemics group centered at The University of Queensland (UQ). The group's focus is the application of data science, machine learning, statistical learning, applied mathematics, computation, and other "artificial intelligence" techniques for managing pandemics both at the epidemic and clinical level.