New Faculty Q&A: Dr. Justin Slater

We spoke to Dr. Justin Slater from the Department of Mathematics and Statistics about his research on developing novel data science and statistical methods in epidemiology. Slater recently joined the College of Engineering and Physical Sciences on January 1st, 2023.

Can you tell us about your career path up until this point? 
I am currently wrapping up my PhD in Statistical Sciences at the University of Toronto, where I developed statistical methods for infectious diseases (COVID-19). Prior to that, I worked as a statistical consultant at Cytel, and an analyst at the Institute for Clinical Evaluative Sciences (IC/ES). In these roles, I was working with leading public health experts (e.g Physicians, epidemiologists) to assess the efficacy of medical interventions, the effectiveness of certain public policies, the cardiovascular effects of injection drug use, and more. I also have an MSc in Statistics (Queen’s), and a BSc in Math and Statistics (Dalhousie). 

What will your focus of research be here at the University of Guelph? 
I try to answer difficult questions in epidemiology by developing novel data science and statistical methods. “How many people in Canada had COVID-19 prior to this date?” or “What is my risk of infection if I travel to Postal code X” are both examples of such questions, each requiring vast amounts of data, novel statistical methods, an interdisciplinary team of researchers, and effective science communications to answer in the real world. My work aims to develop practical quantitative tools that can be used to inform policy makers in public health.

What originally attracted you to studying statistical/data science methods in epidemiology, and what keeps you motivated as a researcher in this field?
The sheer demand for strong quantitative researchers in epidemiology led to me being presented with a ton of interesting opportunities early in my career. I’ve worked on problems in COVID-19 modelling, the opioid epidemic, kidney health, etc. where each problem presents its own unique statistical challenges. 

Since I began working in the field, I have found a nice balance between stimulating my intellectual curiosity and solving real-world problems that affect the health of people around the globe. The statistical problems themselves are often comprehensible to lay audiences, but the solutions are technically very deep, involving extensive mathematical/statistical/computational expertise.

What is a recent research project/initiative that you are especially excited about?
One problem that epidemiologists have faced over the past 2.5 years is that the number of COVID-19 infections over time is unknown; all we know is the number of positive tests (this is what is returned if you google “COVID-19 cases Ontario”). As such, many policies are employed based on trends (i.e are cases going up or down and at what rate?), but even these trends are not estimated well due to the underreporting problem. Under a weak assumption, I have shown that we can recover the trends of the true number of cases based on testing data. Sometime in late 2023, I will make this method available to epidemiologists across the globe who study infectious disease epidemics.

In the next 5 years, what do you hope to achieve?
In the coming years, I hope to collaborate with (mostly non-profit) agencies that have interesting data and are working on problems that affect the health of Canadians today. I hope to develop novel statistical methods that they can readily utilize to inform policy decisions. Furthermore, I hope to inspire statistics and data science students at Guelph to solve real-world problems and foster connections that will shape their future careers.

Will you be looking for undergraduate, graduate, or postdoctoral students in the near future?
I am on the lookout for graduate students who have similar research interests to mine and encourage enthusiastic students to reach out and tell me their story. Postings for specific positions can be found on my website: https://www.justinslater.ca/ 
 

Dr. Justin Slater is an Assistant Professor of Statistics in the Department of Mathematics and Statistics.