Public reaction to an infectious disease outbreak could affect how it spreads. Researchers at University of Waterloo are applying math to better understand that dynamic, through a new predictive model that factors how pathogen strains of varying virulence respond to social intervention and compete for dominance.
Computer simulations allowed Chris Bauch, a professor in Waterloo’s Department of Applied Mathematics, and PhD candidate Joe Pharaon to assess the behaviour of competing pathogens as the public adopts various defensive strategies to avoid infection. Drawing on the events of past outbreaks, they modelled how scenarios such as the widespread use of facemasks, or a premature halt in using facemasks, could affect the evolution of the strain.
“We tend to treat disease systems in isolation from social systems, and we don’t often think about how they connect to each other or influence each other,” Bauch observes. “This gives us a better appreciation of how social reactions to infectious disease can influence which strains become prominent in the population.”
In turn, public health officials could use this information to identify and promote more effective responses to an outbreak, including steps people can take to protect themselves. Bauch and Pharaon’s recently published paper on this new factor in disease modelling can be found in the Journal of Theoretical Biology.