Dr. Robert Smith?

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Video

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Full Name

Dr. Robert Smith?

Academic Profile

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

Long description

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.

Type of institution

University

Address

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

Institution

University of Ottawa

I have a knowledge mobilization grant.

Yes

Website

http://www.uottawa.ca

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

Video Transcript

Transcription

Transcript (English)
 
Introduce your team
 
My name is Dr. Robert Smith?. I’m a professor in the Department of Mathematics and Statistics at the University of Ottawa, but I’m also cross appointed to the Faculty of Medicine where I’m in the Department of Epidemiology. I have been at the University of Ottawa for 11 years now.
 
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.
 
Transcript (French)
 
Introduisez votre équipe
 
Mon nom est Dr. Robert Smith?. Je suis professeur au Département de mathématiques et statistique à l’Université d’Ottawa, mais je travaille aussi conjointement à la Faculté de médecine, dans le Département d’épidémiologie. Je travaille à l’Université d’Ottawa depuis 11 ans déjà.
 
Decrivez votre recherche
 
Dans le cadre de ma recherche, je traduis des problèmes réels liés aux maladies infectieuses dans le langage des mathématiques, et je considère qu’il s’agit d’un langage. L’idée est que nous avons un langage très complexe, mais c’est très utile parce qu’elle nous donne accès à la logique et à la rigueur, ce qui nous permet d’analyser les problèmes d’une manière qui serait très difficile dans le monde réel.
 
Ceci nous donne une façon de faire briller la lumière dans l’obscurité et dans mon cas, j’utilise les équations différentielles qui sont essentiellement un moteur de changement. On construit ce moteur en fonction de notre compréhension de la biologie, des mécanismes impliqués dans la façon dont les gens interagissent ou dont cellules interagissent avec les virus ou quoi que ce soit d’autre qui est à l’étude, et on essaie ensuite d’arriver à une conclusion.
 
Cette conclusion pourrait être: mettre tant de gens en quarantaine, ou pouvons-nous vacciner un tel nombre de personnes, ou la conclusion peut être que le monde est dans une situation très difficile — selon la situation. Ensuite, nous pouvons comparer cela avec des données er retourner au monde réel afin de voir comment cela a un effet.
 
Je travaille aussi avec des biologistes, des épidémiologistes, les gens du gouvernement, etc., pour m’aider à faire cette traduction vers le monde réel. Une fois que j’ai le modèle mathématique, je peux faire les calculs et résoudre les problèmes. Mes étudiants et moi y travaillons tout le temps. Mais ils est difficile de faire la traduction entre le monde réel et les mathématiques,  et savoir le faire précisément est encore plus difficile quelques fois.
 
Soit j’utilise ma propre expérience, soit je fais appel à d’autres personnes qui peuvent le faire afin que nous puissions mieux comprendre essentiellement comment maîtriser les maladies, et je suis particulièrement par la façon dont nous pouvons intervenir. Que pouvons-nous faire pour changer cela? Peut-on prendre un meilleur régime médicamenteux ou vacciner plus fréquemment ou répandre de l’insecticide ou quoi que ce soit d’autre que nous   essayons de combattre — pouvons-nous le faire?
 
Quelle est son importance
 
Une grande qualité des mathématiques est que, comme des boules de cristal, elles permettent de prédire l’avenir. C’est l’une des rares choses que nous avons qui peut nous dire ce qui va se passer d’une manière fiable.
 
Bien sûr, ce n’est pas parfait.  Ça dépend des hypothèses que l’on a. À savoir, étant donné ces hypothèses, que va-t-il se passer? Mais nous pouvons vraiment le décortiquer. Pour moi, c’est ça la grande force des mathématiques.
 
Ce que j’essaie toujours de faire, est essentiellement de dire : si cette maladie existe en ce moment ou se manifeste dans le futur, que va-t-il se passer et quels en seront les effets? J’essaie toujours de prédire les conséquences à long-terme, à court-terme et ainsi de suite; mais pas de ne pas prédire une seule conséquence.
Souvent, on veut prédire une variété de conséquences. Compte tenu de toute l’incertitude présente dans le monde, quelles sont les conséquences possibles? Cela nous dit aussi ce qui ne va pas arriver. Cela est très utile également.
 
Par exemple, m’en suis servi dans le passé pour étudier le vaccin contre le VPH. Le vaccin contre le virus du papillome humain est sorti vers 2004 et a été lancé en Ontario en 2008. Nous avons analysé, en collaboration avec l’Agence de la santé publique du Canada, quel serait l’effet de standardiser ce vaccin à travers le Canada? Est-ce qu’on a besoin de le faire, étant donnée les différents âges et le nombre différent de doses et ainsi de suite?
 
Nous avons découvert que l’âge n’était pas très pertinent, mais que le nombre de doses l’était. Il s’avère que nous n’avons pas besoin d’autant de doses que ce qui avait été prédit, dans le sens qu’il est préférable d’avoir moins de doses que plus de gens prennent que d’avoir plus de doses que moins de gens prennent.
 
En fait, le Québec a  sa politique à la suite de cette modélisation, et ceci n’est qu’un exemple parmi tant d’autres des nombreuses applications que nous faisons. Je suis un mathématicien très appliqué et j’ai travaillé avec des gens en Afrique sur les insecticides pour combattre la paludisme, j’ai travaillé sur de nombreux problèmes lié au VIH à travers le monde, sur la lèpre. Toutes sortes de choses en fait car je considère que l’interface entre les mathématiques et la biologie est très gratifiante.
 
J’aime vraiment la façon dont ils s’associent et j’aime que mes outils théoriques en mathématiques puissent être utiles pour résoudre des problèmes mondiaux. Pour moi, c’est extrêmement gratifiant.