Dr. Robert Smith?

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Video of the Researcher

Website

mysite.science.uottawa.ca/rsmith43

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Full name

Dr. Robert Smith?

Summary

Using differential equations to build models to prevent, stop and reverse epidemics, including determining who should get the HPV vaccine or where to spread insecticides to fight malaria

Type of researcher

Principal Investigator

Introduce yourself, your experience and your credentials

I started academic life in sewage. When it comes down to it, don’t we all, really? But I did so a bit more literally than most, since I was studying sewage treatment and toxic waste cleanup for my PhD. This is a process called self-cycling fermentation and is kinda funky after you’ve spent five years thinking about nothing but that.

Still, it gave me good training in Applied Mathematics (my pure math days started in Australia and had a brief flirtation in my Master’s degree in Canada, but then I gave into the dark side of mathematics and decided to apply myself). It also taught me Impulsive Differential Equations, which are a great tool and something more people should know about (although thanks to the zombies, now they probably do). It helps if you can think discontinuously, but that wasn’t too much of a problem for me.

After my PhD, I did a postdoc at the University of Western Ontario, where I discovered infectious diseases. At first it was just the one, you know? A little HIV, you know you want to, all your friends are doing it… Before I knew it, I was studying malaria, then it was human papillomavirus. After that, it was all a blur of neglected tropical diseases that kept coming and coming and, oh god, then I was into some really hardcore stuff, man. And once you’ve tried modelling zombies, you can never go back… *sobs*

Oh, right, sorry about that. Let me start over.

I started doing immunological modelling of HIV with Lindi Wahl and really enjoyed it. We came up with a series of papers, which involved applying my Impulsive Differential Equations skills to drug-taking in order to create a complex HIV model and then use that to discuss drug resistance. This led to one of the few papers to deal with the question of adherence (it started life as a collaboration with Lindi, but she kindly pushed me out of the nest). Which is a shame, as the US department of health and human services called it the most urgent unanswered question in HIV research.

My second postdoc was at UCLA, which everyone in Canada thought was a dream come true, but being Australian I’d experienced actual warmth before, so I seemed to fit right in. I was part of the Disease Modelling Group in the School of Medicine, working on epidemiological models of HIV under Sally Blower. And that still sounds fancy.

Sally and I published a paper on possible perverse outcomes of HIV vaccines. As well as being a pretty high profile publication academically, this was the first paper my parents could actually read and not be bamboozled by. I got a lot of postive comments from non-academic friends and family… I also got a lot of sympathetic murmers from pure mathematicians when I told them that not only did all my math work get put into an appendix, it got put into a web-only appendix. Such is the price of leaving the cosy world of mathematics.

Our group also published a paper on female sex workers and HIV vaginal microbicides. I started off in the rectal microbicide team, but then switched to the vaginal team. The jokes were never-ending, I can assure you.

I then moved to the University of Illinois, Urbana-Champaign, where I worked on zoonotic diseases, specifically malaria, Chagas’ disease and West Nile Virus. I even got to go on a West Nile Virus field trip and stand around at the creek where it all happened in Chicago. It took me a while to realise that hey, maybe all those mosquitoes buzzing around my bare arms might not be the best idea… But I think there are two types of disease modellers: those who let it get to them and think they’ve caught everything under the sun and those who become incredibly blase about it. Thankfully I’m in the latter category.

After a whirlwind interviewing tour of the continent, I ended up at the University of Ottawa. Now I teach, write grants and organise conferences like every other professor. Unlike most of them, I can skate to work, which is quite the achievement in the eyes of my Australian family and friends. I’m still working on HIV, but have become interested in Human Papillomavirus (thanks to the vaccine), malaria, various tropical diseases – and, of course, that terrifying infection known to humanity only as… zombies!

The zombies have grabbed quite a lot of attention. And rightly so, because who doesn’t love the flesh-eating undead? A surprising number of people have emailed me to tell me that the model doesn’t include the killing of the zombies (it does, in the impulsive eradication section) or that zombies don’t come back to life when you kill them (I’m sorry, but they do; Shaun hits one with his car in Shaun of the Dead and then it comes back to life). The fact that I can have this kind of discussion about my academic work thrills me to bits. Except for that one guy who asked, apparently in all seriousness, if I’d help him create a zombie virus. Now that’s scary.

Describe your research

My research involves taking real-world problems in infectious diseases and translating them into the language of mathematics, and I do think of it as a language. The idea is that you have a very dense language but it’s very useful because you have access to logic and rigor and so it means that you can analyze these problems in a way that you probably couldn’t so easily in the real world.

So it kind of gives you a way to shine the light in the darkness and in my case, I use differential equations which are essentially an engine of change.

You build this engine based on your understanding of biology, the mechanisms involved in how people interact or cells interact with virus or whatever it is that is under study and then try and come to some conclusion.

That conclusion may be: quarantine this many people, or can we vaccinate this many people or the conclusion may be that the world is in big trouble — depending on what the situation is. Then you can actually compare this with data, and go back to the real world and see how this has an effect.

I also work with people who are biologists or epidemiologists or government people and so on because they help me with this translation. Once I have the mathematical model, I can do the math and I can solve the problems. My students and I work on this all the time. But actually getting the translation between the real world and the mathematics is difficult and trying to get it very accurately is even more difficult sometimes.

Either I use my own experience or I draw on other people who can do this so that we can have a better understanding of essentially how to get a handle on diseases, and I’m particularly interested in how you intervene. What can you do to actually change this? Can you take a better drug regimen or vaccinate more often or spray insecticide or whatever it is that you’re actually trying to tackle — can you do this?

Explain its significance

One of the great things about mathematics is, like crystal balls, it can predict the future. It’s one of the very few things we have that can actually tell us what’s going to happen in any kind of reliable way.

Of course, it’s not perfect. It depends on the assumptions that you have, to try and see: given those assumptions, what’s going to happen? But you can actually roll it out. And so to me, that’s the great power of mathematics.

What I’m trying to do all the time is basically say: if this disease either exists currently or turns up in the future or something like that, what’s going to happen and what are the effects? I’m always trying to predict long-term outcomes, short-term outcomes and so on, but not just a single outcome.

Often you want to predict a variety of outcomes. Given all the uncertainty that we have in the world, what are the possible outcomes, which also tells you what is not going to happen. That’s actually also very useful, too.

For example, I’ve used this in the past to look at the HPV vaccine. The human papillomavirus vaccine came out in about 2004 and it was rolled out in Ontario in 2008. We looked at, along with the Public Health Agency of Canada, what would be the effect of standardizing this vaccine across Canada? Do we need to, given the different ages and different number of doses and so on?

We discovered that the ages was not that relevant but the number of doses actually, it turns out… you don’t need as many doses as was predicted, in the sense that you’re better off having fewer doses that more people take than more doses that fewer take.

In fact, Quebec changed its policy as a result of this modeling, and that’s just one example of lots and lots of applications that we do. I’m a very applied mathematician and so I’ve worked with people in Africa on spraying insecticide to combat malaria, I’ve worked on a lot of HIV problems throughout the world, on leprosy. All kinds of things actually because I find that the interface between math and biology is for me very rewarding.

I really, really like the way they join together and I really like that my theoretical tools in mathematics can be something that’s so useful in dealing with world problems and that to me is extremely rewarding.

Institution

Institution name

University of Ottawa

Address

University of Ottawa, Laurier Avenue East, Ottawa, ON, Canada

Type of institution

University

Industry

Professional, scientific and technical services

Professional, scientific and technical services

Public administration

Federal government public administration, Provincial and territorial public administration, Local, municipal and regional public adminstration, International and other extra-territorial public adminstration, Aboriginal public administration