[xpost] Coronavirus: the math & stats behind the news + the role of genetic data

This is a cross-posting, please RSVP on our partner's eventbrite page (the event is free, but RSVP is required):

https://www.eventbrite.ca/e/bc-data-colloquium-series-february-27-caroline-colijn-tickets-92251794601

We are happy to cross-post a UBC PIMS bcdata Colloquim Series event again!

Coronavirus 2019: the math and stats behind the news, and the role of genetic data, Caroline Colijn, SFU

Registration, Networking and Refreshments: 18:00
Talk: 18:30

Abstract:

The coronavirus that was reported in Wuhan, China in December 2019 has caused much concern in the media, in scientific and in public health communities due to its human-to-human transmission, virulence and transmissibility. In this era of open data, the scientific community has been quick to respond, with a wide range of early analyses estimating key epidemiological parameters and dynamics: the basic reproduction number, the serial interval, the time of origin of the virus and forecasts of future importations and spread. In this talk I will describe how this analysis is done and point out key areas of uncertainty as a new infection emerges. There is also, more broadly in the field, considerable interest in using genetic data in epidemiology, as these data can give a high-resolution picture of transmission and pathogen evolution. I will describe some of my group’s work on genomic epidemiology and phylogenetic trees and will show how these tools can be applied to the coronavirus data that are available as of early February 2020.

Biography:

Caroline's work is at the interface of mathematics and the epidemiology and evolution of pathogens. She holds an Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health. In her group they develop mathematical tools connecting sequence data to the ecology and evolution of infections. She also has a long-standing interest on the dynamics of diverse interacting pathogens. For example, how does the interplay between co-infection, competition and selection drive the development of antimicrobial resistance? To answer these questions, my group is building new approaches to analyzing and comparing phylogenetic trees derived from sequence data, studying tree space and branching processes, and developing ecological and epidemiological models with diversity in mind.