Statistics Associate Professor Alex Bouchard-Côté and co-researchers have been awarded a CANSSI Collaborative Team Grant to support the project "Statistical Methods for Challenging Problems in Public Health Microbiology”. The three-year $180,000 grant will support the team's development of methods that will help public heath authorities control the development of drug resistance and the spread of epidemic outbreaks.
From the project proposal:
Pathogenic microbial organisms cause a significant burden of disease not only in low-resource countries, but also in high-income countries, especially in hospital settings. One problem that is particularly relevant today is the problem of drug resistance, whereby a pathogen no longer responds to a drug treatment. Additionally, the appearance of pathogen outbreaks requires the development of surveillance tools to rapidly track, prevent, and ultimately disrupt the chain of transmissions.
The availability of fast, reliable and affordable whole-genome sequencing (WGS) methods has the potential to be a major boon for public health authorities attempting to control the development of drug resistance and the spread of epidemic outbreaks. However, in order to fully harness the power of these methods there is an urgent need for novel statistical and algorithmic techniques for microbial WGS data, but these methods are still in their infancy. Our project consists of tackling three challenging and currently unsolved statistical problems that arise in public health microbiology, and deploying the methods we develop in a publicly available computational platform. These challenges naturally arose in the course of our work on our respective CIHR/Genome Canada projects (A toolkit for microbial GWAS, henceforth abbreviated to “GWAS”; Kamphir; PathOGiST), all of which focus on pathogens.
The team of lead investigators is as follows.
Luis Barreiro, Centre Hospitalier Universitaire Sainte-Justine, Montréal
Alexandre Bouchard-Côté, Department of Statistics, University of British Columbia
Leonid Chindelevitch, School of Computing Science, Simon Fraser University
Art Poon, Department of Pathology and Laboratory Medicine, University of Western Ontario
Jesse Shapiro, Department of Biological Sciences, Université de Montréal
Liangliang Wang, Department of Statistics and Actuarial Science, Simon Fraser University