BIG DATA Can computer models By Caitlin Dawson Humanity and infectious diseases are locked in a deadly arms race. According to the most recent survey by the World Health Organization, more than six million people died from lower respiratory infections, tuberculosis (TB) and diarrheal disease in 2015. Despite major advances in treatment and prevention, these infectious diseases ranked in the top 10 causes of death worldwide, with HIV/AIDS and malaria accounting for an additional two causes in low-income countries. S imon Fraser University computing science professor Leonid Chindelevitch is on a mission to fight back against these lethal outbreaks using his weapon of choice: Data. Chindelevitch, a 2016 Sloan Research Fellow who completed his postdoctoral research at the Harvard School of Public Health, uses computational modelling to track and predict the spread of emerging infectious diseases. The stakes are high. While malaria and TB have plagued humanity for years, health authorities are now battling new outbreaks of emerging infectious diseases. In 2014, the Ebola virus swept through West Africa killing more than 10,000 people. Last year, the World Health Organization declared Zika an international public health emergency when the virus, which now threatens more than 60 countries, was discovered to cause severe birth defects. Potential triggers for new outbreaks include animal–human transmission and environmental factors such as increased international air travel and global warming. Using data from a variety of sources, including clinical, genomic and epidemiological data, Chindelevitch’s modelling work provides the ability to predict disease spread, assess risk and choose the best intervention strategies. His modelling framework can be applied to a variety of epidemics, including TB, HIV/AIDS and Lyme disease. We sat down with Chindelevitch to find out more about the evolution of infectious diseases, the perils of drug resistance and data’s role in predicting pandemics. What is your research focus? I’m primarily interested in understanding the development of infectious disease epidemics—everything from low-level changes in the bacteria or virus, all the way to the spread of disease through human populations. www.rehabmagazine.ca A great deal of my expertise lies in constructing models— I build mathematical models and develop computational algorithms to look at changes in the bacteria or virus, or how an epidemic unfolds over time. Ultimately, I’m looking for the best intervention to control these epidemics, especially in low-resource settings where infectious diseases tend to spread rapidly. Q How do you tackle this? First, I write down a model and then I see how closely the trends recapitulate the actual trends that we’ve observed in the past. By matching the past, we can have a reasonable idea of what the future is going to hold. That’s mostly at the population Q 16 WINTER 2017/18 Photo: Simon Fraser University Image: CanStock predict pandemics?