Mathematics can help public health workers better understand and influence human behaviours that lead to the spread of infectious disease, according to a study from the University of Waterloo.
Mathematics can help public health workers better understand and influence human behaviours that lead to the spread of infectious disease, according to a study from the University of Waterloo.
Current models used to predict the emergence and evolution of pathogens within host populations do not include social behaviour.
“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,” said Chris Bauch, co-author and a professor in the Department of Applied Mathematics at Waterloo. “This gives us a better appreciation of how social reactions to infectious diseases can influence which strains become prominent in the population.”
By adding dynamic social interactions to the models already used for disease outbreaks and evolution, researchers could better anticipate how a virulent pathogen strain may emerge based on how humans attempt to control the spread of the disease. This new addition to disease modelling could allow scientists to better prevent undesirable outcomes, such as more dangerous mutant strains from evolving and spreading.
Read more at University of Waterloo
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