Debapriyo Chakraborty: Viral phylodynamics at the human-animal interface

I am interested in epidemiological problems that are unique to rapidly evolving viruses (e.g., vaccine resistance, increase in virulence and transmission rate) as a result of interactions between their ecology and evolution (“phylodynamics”). These viruses are often found at the human-animal interfaces and are epidemiologically most consequential. These problems can be tackled using viral genomic data. For example, in 2016–17, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8 in the poultry industry. I combined genomic data with non-genomic data—including geographical and epidemiological data—using a GLM-based phylodynamics model (MASCOT) that afforded hypothesis testing related to viral spread. This allowed me to identify the impact of preventive culling and ban on duck transport on the viral spread between duck farms—in addition to reconstructing the history of the spread. Next, my goal is to estimate epidemiological parameters (e.g., R0 and infectious period) directly from viral genomic data. Using this approach, I am studying the evolution and epidemiology of the SARS-CoV-2 variants in Mexico. According to ongoing analyses, SARS-CoV-2 transmission was structured by age-cohorts—similar to most countries—but differed considerably in details indicating difference in contact networks.