As a new assistant professor joint with the Department of Mathematics, Saad-Roy will study infectious disease dynamics using computational modelling.

By Sarah Anderson, PhD

Chadi Saad-Roy tends to go the extra mile. He participated in his first science fair at the age of 10. He had three PhD advisors during his graduate studies. And, literally speaking, he recently walked about 5.5 miles (9 kilometres) home from UBC, just for the exercise and fresh air.

Saad-Roy’s favorite science fair project focused on magnetic trains; he studied how different types of magnets and their spacing affected how fast the train could go. “It was fun to do, and I learned a lot of statistics and also general scientific methods from it,” he said. 

Having grown up with two biologists as parents, perhaps Saad-Roy inherited his natural scientific curiosity. Uniquely his own, however, was his incredible aptitude for math. Although he didn’t find the subject to be migraine-inducing, he wasn't necessarily interested in pursuing advanced mathematics after high school.

But as an undergraduate student at the University of Victoria, Saad-Roy developed an appreciation for challenging, college-level mathematics. Partway through his studies, he decided to participate in a research assistantship with mathematician Pauline van den Driessche. There, he was introduced to mathematical epidemiology and discovered that he could apply his skills to understand and predict the spread of disease. Captivated by this interdisciplinary field of study, he worked with van den Driessche each subsequent summer and eventually received his Bachelor’s degree in mathematics and statistics with a minor in biology. He then earned a PhD in quantitative and computational biology at Princeton University and completed a research fellowship at the Miller Institute for Basic Research in Science at the University of California, Berkeley. 

Saad-Roy’s research focuses on developing mathematical models for infectious disease dynamics at different scales, from the individual host to society at large. By capturing various immunological, ecological, evolutionary, and epidemiological processes in a system of equations, he can examine the effects of parameters such as transmission rate and time to recovery on the prevalence and severity of infectious disease. 

Amid the uncertainty of 2020, Saad-Roy developed a “simple” computational model to explore how specific immunological variables might impact the magnitude of future COVID-19 cases, drawing on closely related coronaviruses to make assumptions about the transmissibility and seasonality of the then uncharacterized SARS-CoV-2 virus. He found that, depending on two key parameters — how long someone is immune for after infection and how susceptible they are to reinfection after their immunity wanes — the disease outcomes ranges from severe epidemics to near elimination. And as scientists raced to develop a COVID-19 vaccine, he also modeled the effects of vaccination and vaccine hesitancy and found that the disease burden increases if unvaccinated people have more contact relative to the rest of the population. 

“That’s the beauty of modeling — you can do experiments on the computer that you can't test otherwise, like what happens if you vaccinate only a fraction of people,” Saad-Roy said. “But on the flip side, it also informs what kinds of data need to be collected.” For example, his study underscored the importance of understanding the immune response to SARS-CoV-2 in order to project and prepare for the disease landscape five years down the road. 

Saad-Roy has also developed mathematical models to evaluate the consequences of individual and collective decision making related to infectious disease. One such model predicted that stockpiling of the COVID-19 vaccine among affluent nations would increase disease incidence in low-access regions and heighten the risk of new variants emerging globally, supporting the benefits of equitable vaccine distribution. “Sometimes results seem intuitive, but we can actually show these kinds of things and add scientific backing to verbal arguments,” Saad-Roy said. 

Other findings have been less intuitive. For example, if people can choose whether or not to adhere to behavioural interventions such as masking and social distancing and if partial adherence is the long-term outcome, the number of infections remains constant regardless of the transmission rate. “The idea is that people are adhering more or less in a way that totally compensates,” Saad-Roy explained. “It shows that we need to think about the system more completely when designing potential interventions.”  

Saad-Roy is eager to continue pursuing these questions as he launches his career as an independent investigator at UBC. He looks forward to connecting with colleagues in microbiology and immunology, mathematics, and beyond, serving as a mentor to his students, and ideally inspiring the next generation of mathematician-biologists. As the newest member of the PrePARE research cluster, he is excited to further explore the evolutionary dynamics of infectious disease, specifically how pathogens evolve in response to a host’s immune life history. 

Saad-Roy hopes that his research provides a helpful starting point for guiding the development of vaccination regimens, nonpharmaceutical interventions, and other infectious disease control strategies. “I have a set of skills that I want to use to improve society in whatever ways I can,” he said. “The global burden of disease is growing, and I think it’s important to try to use our knowledge to anticipate and prevent that.”