Epidemiology and Public Health December 16, 2020


Daniel Coombs, PhD – University of British Columbia

Daniel Coombs is an internationally recognized expert in mathematical modelling applied to human health, immunity, and disease. Dr. Coombs obtained his MSc and PhD in applied mathematics from the University of Arizona and did postdoctoral work at Los Alamos National Lab, before joining the Department of Mathematics at the University of British Columbia (UBC) as a faculty member in 2003. Dr. Coombs contributes to our understanding of infections and immunity across scales: from subcellular processes of immunological recognition to virus dynamics at the single-patient level, to epidemiological modelling across human communities. He works closely with experimental scientists at UBC and BC Children’s Hospital Research Centre and public health experts at the BC Centre for Disease Control. Dr. Coombs is a member of the Canadian Chief Science Advisor’s expert panel on COVID-19.

My most important opinions about mathematical epidemiology

Over the last eleven months we have all grown accustomed to mathematical modelling as a tool for projecting and predicting the development of the covid-19 pandemic. Besides working on different kinds of modelling for the pandemic, I have had many conversations with mathematicians, other scientists, public health officials and journalists about “the numbers” and “the models”. Along the way I have learned some facts and developed a number of opinions about the whole process. In this talk I will share a selection of the opinions (and maybe even a few facts) related to the crucial whats, whys and hows related to epidemic modelling, communicating our findings, working with others, and the future of this area of science. 

Michael Otterstatter, PhD – BC Centre for Disease Control

Michael Otterstatter is a Senior Scientist at the BC Centre for Disease Control and an Assistant Clinical Professor in the School of Population and Public Health at UBC. His research and teaching focus on theory and methods for the analysis, modeling and visualization of health data. Dr. Otterstatter works with government and non-government stakeholders as a consultant and scientific advisor in epidemiology and biostatistics. He holds a doctorate from the University of Toronto, as well as MSc and BSc degrees from the University of Calgary. Previously, Dr. Otterstatter worked in cancer surveillance with the Public Health Agency of Canada in Ottawa.

The focus of my presentation will be to help inform career options in epidemiology and public health, particularly for students and early-career researchers transitioning from academia to industry. I will discuss aspects of my own career path, what we do at the BC Centre for Disease Control (in terms of epidemiology specifically), and what we look for when hiring in positions involving math, statistics and computation.

Steven Pridie – Unity 3D

Steven Pridie is a Research & Development Engineering Lead at Unity3D (Formerly Finger Food Studios). He is a P.Eng registered in BC and has an extensive background in electrical engineering including subsea electronics, IoT devices, robot mission planning, and projection systems. His current focus is on technical scoping, solution trials and product envisioning for industrial projects at Unity.

From Research to Impact:
Commercial Application of Epidemiological Modeling

This presentation outlines the development of a commercial software application that includes epidemiological modeling as a core feature. Commercial applications of epidemiological modeling are not common and infrequently discussed in detail. Challenges encountered during development are presented and learnings discussed as they relate to communicating accurate model outputs to a non-technical audience.

Julien Arino, PhD – University of Manitoba

Julien Arino is a professor in the Department of Mathematics and an affiliate of the Data Science Nexus at the University of Manitoba. He is a member of the Canadian Centres for Disease Modelling and the Canadian COVID-19 Mathematical Modelling Task Force. His work is in mathematical ecology and epidemiology, with particular focus on population mobility and its consequences. In the context of COVID-19 response, he has focused on global and local importation risks.

Quarantine and the risk of COVID-19 importation.

COVID-19 has spread to most country-level jurisdictions. Zooming in, though, it is apparent that not all lower level jurisdictions (e.g., cities) see active disease propagation at all times. This effect is particularly evident in isolated locations such as those in northern Canada or the Maritime provinces. Some locations see active transmission chains for a while, following which no new cases are detected for some time, followed in turn by renewed detections. Two main mechanisms can explain this phenomenon: silent transmission chains and case importations from other locations.

Dane Sheppard – The Black Arcs

Dane is the Director of Technology for The Black Arcs. He is responsible for long-term technology strategy and guides the development team as they transform synthetic population generation, Geographic Information System data, activity-based transportation modelling into an engaging, intuitive civic simulator. Dane regularly works with domain experts on a variety of simulation-related topics as part of delivering technical content for company projects.

The silo effect and the importance of good data visualization

Sharing information on complex issues can be tremendously difficult, particularly when multiple stakeholders are involved. Collaborative projects spanning multiple teams or departments can have widely varied technical language and subject-matter expertise. This presentation will discuss data visualization for COVID-19 and how the team at The Black Arcs is using environmental modelling, computational fluid dynamics, GiS data, and transportation modelling to aid communication about these issues.

Dr. Ram Tiwari – FDA

Ram C. Tiwari, Ph.D. is the Director for Division of Biostatistics, CDRH, since 2016. He joined FDA in April 2008 as Associate Director for Statistical Science and Policy in the Immediate Office, Office of Biostatistics, CDER. Prior to joining FDA, he served as Program Director and Mathematical Statistician in the Division of Cancer Control and Population Sciences at National Cancer Institute, NIH; and as Professor and Chair, Department of Mathematics, University of North Carolina at Charlotte.

Dr. Tiwari received his MS and PhD degrees from Florida State University in Mathematical Statistics. He is a Fellow of the American Statistical Association and a past President of the International Indian Statistical Association.

New Statistical Initiatives in the FDA CDRH

In this presentation, I will give an overview of some recent initiatives in the Division of Biostatistics at the Center for Devices and Radiological Health (CDRH) at FDA. These include innovative statistical methods for benefit-risk assessment, leveraging external evidence in medical decision-making, and site selection for inspections.

In this work, we focus on importations. We consider a location in which there are few or no local transmission events. A stochastic model is used to describe the spread of COVID-19 within the location and the response of the model to both single and multiple importation events is evaluated. This allows us to quantify the risk of importation as a function of both the frequency of importations and the intensity of local public health effort. We then use the same model to describe individual infection histories, obtaining a quantification of the efficacy of quarantine as a function of its duration and disease characteristics.


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