Colloquium Talk: Leonid Chindelevitch
Mathematical Modelling Helps Understand Infectious Disease Epidemics
Infectious diseases continue to affect the lives of millions of people around the world, but we still understand relatively little about how exactly they spread through populations. I will discuss an epidemiological model of the joint epidemic of tuberculosis and HIV in South Africa as an example of the kind of tools policymakers had at their disposal until recently. I will then go on to show how genotypic information can be harnessed to interrogate an epidemic, using the example of complex tuberculosis infections. I will conclude with a mechanistic model that describes the way bacterial pathogens may evolve resistance to drugs, and speculate on what challenges await us in the next few decades.
Bio: I started working in bioinformatics as an undergraduate, when I did my first research project – and published my first paper – with Mathieu Blanchette at McGill University. I continued working in this field in graduate school under Bonnie Berger, and acquired expertise in the analysis of biological networks, at the interface of computational and systems biology. After a brief foray into the pharmaceutical industry, where I developed a platform for the analysis of various omics data, I returned to academia. My postdoctoral fellowship focused on a new area of application – epidemiology – and I became an expert in the rapidly developing field of molecular epidemiology, the study of epidemics through the prism of the information contained in the genomes of infectious disease-causing pathogens. My current work encompasses all of these subfields and focuses on infectious diseases. I really enjoy forming collaborations to explore various aspects of infectious diseases, ranging from their molecular biology all the way to population-level health policies.