By Dr. Navideh Noori
Navideh talks with Robert J. Smith?, Full Professor in Department of Mathematics and Statistics at University of Ottawa and recipient of the 2018 Distinguished Service Award.
You won the Distinguished Service Award for successfully using pop culture to showcase the power of mathematical modeling of infectious diseases, sparking the interest of mathematical and non-mathematical audiences worldwide. Could you first tell us about your research background, and how you arrived in your current position?
I didn’t come from an academic background at all (my father dropped out of high school and didn’t even understand what university was when I wanted to go), so it meant I had to do everything the hard way and make all the rookie mistakes. But I slowly learned how to do research and what academia was all about. I did three postdocs, one at the University of Western Ontario in an applied math department, one at UCLA in a disease modelling lab and one at the University of Illinois at Urbana-Champaign, in the pathobiology department, where I was the only mathematician. So I got increasingly less mathematical as I went on, which helped me understand the need for mathematics in non-mathematical fields. From there, I wasn’t sure if I wanted to be the math guy in a biology department or a biomathematician in a math department. I eventually decided on the latter when I took my current position at the University of Ottawa, but I’m also cross-appointed to epidemiology, in the faculty of medicine.
What attracted you to your field of research?
I was always interested in mathematics, but I didn’t quite know what I wanted to do with it. I loved applied mathematics and initially did environmental cleanup stuff for my PhD. But when I started my first postdoc I discovered that you could use mathematics to study infectious diseases, and it was like a light going on. At last, I knew what I wanted to do when I grew up!
What do you foresee as the biggest challenges in your field?
Across different mathematical biology fields I am engaged in, I think how to understand biological or behavioral data with the power of mathematics remains a big challenge. I believe that dynamical systems, stochastic processes, these types of modelling techniques in individual domains, are really beneficial to this end, in addition to statistical, AI and machine learning techniques.
What are you currently researching?
I’m quite interested in the diseases that nobody thinks much about. There are a lot of people modelling “the big three” (HIV, malaria, TB) and various exciting or terrifying diseases like Ebola. I do those as well, but I’m most interested in the neglected tropical diseases. These are a set of diseases (e.g., leprosy, elephantitis, river blindness etc) that don’t kill so many people (which is largely why nobody pays them much attention) but instead disable a lot of people. What’s sad is that there’s also a dearth of models about these diseases, when modelling is something that’s much easier (and cheaper) to do than most other science. We urgently need a diversity of voices in the modelling, but there isn’t one.
What do you foresee as the biggest challenges in modeling of infectious diseases?
Incorporating humans is one of the biggest challenges that modelling is facing. We as scientists are great at quantifying things that can be quantified. We’re not so good at predicting human behaviour. And people can be very unpredictable and sometimes act against their own best interests (e.g., refusing vaccines). However, there’s an enormous amount of work that’s been done in the humanities about this, so I think the next big challenge will be melding modelling with social science. I have something of a social-science background, so I’m quite comfortable with this stuff, but few modellers do. I suspect mathematics is going to trample through the social sciences in the next few decades much that it trampled through biology.
Have you encountered any surprising results in your research?
Yes, many! Generally, I always structure my research around trying to discover what’s surprising or unexpected. That to me is the core of what research should be. If you just confirm the same old results, what’s the point?
One of my first projects was looking at a potential HIV vaccine, which would allow you to become infected but modify the disease. We showed that a disease-modifying vaccine with low efficacy was highly likely to make things worse. That was a real surprise, because you’d think vaccine = good. However, we were also able to find conditions on the transmissibility that would compensate for this.
We studied polio vaccination and found that synchronising the National Immunisation Days across different health regions would make a big difference, overcoming the issue of people who slipped through the cracks due to migration. The only exception was if adjacent areas were out of phase in their seasonal transmission. In that case, you need to decouple the regions and vaccinate before the high season. However, if migration is sufficiently high, then that overwhelms the seasonal effects, and they need to be re-linked. This was not only surprising, it also went against the existing strategy, which simply linked them all because they didn’t know what else to do. Modelling shows that it’s more nuanced than that.
Guinea-worm disease is a disease spread through the drinking water in Africa. It’s very close to being eradicated and will likely be the third disease we’ve ever eradicated (after smallpox and rinderpest, both of which were eradicated thanks to vaccination). There’s no treatment, no immunity and no vaccine, so eradicating falls back on “soft” science options. We examined the three possible interventions (educating people about the disease transmission, providing cloth filters to stop transmission and clorinating the water to kill the parasite). We showed that education is far and away the best option, meaning that the final push for eradication should concentrate on talking to people and providing information and alternatives such as separate water sources for worm disposal. The great thing about education is that you don’t have to sit around and wait for someone to invent a vaccine, you can start right now. And it’s pretty cheap too! It won’t win anybody a Nobel prize, but it can do a lot of good, if applied carefully and with cultural sensitivity.
The World Health Organization adopted a program called “Test and Treat” with the aim of scaling up testing of HIV and then immediately treating anyone found HIV positive. It sounds like an appealing idea, but it doesn’t account for drug resistance. We showed that this program is highly likely to produce an epidemic of drug resistance… unless the program can be supplemented with education. It turns out that education is absolutely critical, and that if it can be tied to these programs, then the outcome will switch from being a public-health disaster to a success.
Do you have a favorite research paper written by another mathematical biologist?
Wahl LM, Nowak MA. Adherence and drug resistance: predictions for therapy outcome. Proceedings of the Royal Society of London. Series B: Biological Sciences. 2000, 267(1445):835-43.
This was a hugely influential paper for me. It quantified the effects of adherence to HIV medication in the case of both perfect and imperfect adherence, showing that different patterns of adherence could lead to very different results.
What is your favorite research paper that you have written?
R.J. Smith?, A.B. Hogan, G.N. Mercer, Unexpected infection spikes in a model of Respiratory Syncytial Virus vaccination. Vaccines, 2017, 5:12.
This was an investigation into a disease that babies get, where I worked alongside biologists to expand an existing model to account for a possible vaccine (as the vaccine development is quite advanced). We used modelling to look at two potential vaccines: a single-shot maternal vaccine and regular post-birth vaccinations. The former was a continuous model, while the latter used impulsive differential equations. During the course of this, we found conditions that gave really strange results that turned out to be a destabilisation of the disease-free equilibrium. And in finding bounds on the impulsive system, I came up with a new quantity: the impulsive reproduction number. Biologically, we were able to find conditions on the strength and frequency of the vaccination that would predict eradication. It’s a really nifty confluence of both mathematical and biological results.
How have you found working with experimentalists?
I love taking mathematics to the masses! I spent a long time being the only mathematician in the room, working with doctors who had very little mathematical background and working with health agencies who were initially extremely hostile to the very idea of modelling. But I’m very patient and happy to explain things again and again, in a different way each time, because I genuinely want people to learn (this is the educator in me). After a while, I realised it was a language issue, but if you could speak the language of policymakers or experimentalists or doctors, then you could actually communicate with them and make a difference. It took much longer than I’d imagined to learn this language, but now that I know it, it’s very handy.
What impact has your research had outside of academia?
In 2009, I published a mathematical model of zombies, which took the world by storm. I’d always been a science-fiction fan, but I’d kept my mathematical career and my sci-fi life separate. Until I touched the two together and everyone went crazy. It was the #1 news story in the world (admittedly it was a slow news week!). For a number of years, my zombie paper was the #1 pdf on Google. We even won a Guinness World Record for it! What was so appealling about it was that it took mathematics to where people live. Instead of making people learn equations, we showed that mathematics could be fun and potentially useful. It raised a huge awareness of the power of modelling, as many people reported that they’d never even heard of such a thing as disease modelling until they’d seen our paper. It inspired any number of people to study disease modelling and essentially invented the academic sub-discipline that is mathematical modelling of zombies. I’m amazed by how influential it was, for something that came out of a class project. However, it was that very educational idea — using the fun hook of zombies to showcase how disease modelling works — that had an extremely broad appeal, even among a wide selection of people who openly told me they hated mathematics, but they read every word of the zombie paper.
In more serious research, I worked with the Public Health Agency of Canada (PHAC) on a model of HPV vaccination, comparing the difference vaccination schemes in the various Canadian provinces (which vaccinated at different school grades and with different doses). We showed that the different grades and different doses didn’t matter, what was important was to adjust to the particular province in order to maximise vaccine uptake. PHAC were initially quite skeptical of modelling, but they eventually came round and then wholeheartedly embraced it. The end result was that Quebec changed its vaccination policy in order to streamline more uptake, which is something I’d incredibly proud of. It’s astonishing to me that my proficiency in mathematics has resulted in lives being saved.
What advice would you give to a junior mathematical biologist?
Find your niche. Bring something original to the table, both mathematically and also in the applications. It’s easy to fall in with the crowd, but the whole point of academia is to be original and creative, so find something that no one else is doing and lean into it. And then do it again. Keep harnessing your creativity. The whole point of academia is to have ideas. Lots of ideas. So have them.
What is the best part of your job? What is the worst part of your job?
The best part of my job is working with people all around the world, from my graduate students to non-math collaborators to overseas students. I teach regularly at the African Institute for Mathematical Sciences in Senegal and Cameroon, and also summer schools in places like Nepal, and have made amazing connections and inspired people and been inspired. I’m amazed that a supposedly solitary profession like mathematics is actually so collaborative, which I just adore.
The worst part is watching the slow dismantling of higher education. There’s a concerted effort to take people who think like academics out of middle and upper management and replace them with people who think like accountants. I think the grant system is fundamentally broken and actively discourages people from doing big things or thinking outside the box, which is the opposite of what academia should be. These things make researchers far more conservative than they should be, and for no reason. The long-term result is a devaluing of academia, which is going to have a detrimental effect on society.
What do you do in your spare time?
I write and edit books on pop culture. I have 18 books to my name and counting. I have a book series called “Outside In” that examines a variety of science-fiction TV shows (Doctor Who, Star Trek, Buffy, Angel, Firefly, The X-Files…) with a series of mind-boggling twists. I also write episode guides to Doctor Who on both TV and in novel form. I love writing, which many scientists really don’t, so I credit that with a large part of my success. Writing a paper is pretty easy for me and a lot quicker than writing a book!