Math helps to understand how human behaviour spreads infectious diseases

According to a study, current models used to predict the emergence and evolution of pathogens within populations do not include social behaviour.

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Washington: Turns out, mathematics can help public health workers understand and influence human behaviours that lead to the spread of infectious diseases.

According to a study from the University of Waterloo, current models used to predict the emergence and evolution of pathogens within populations do not include social behaviour.

Co-author Chris Bauch said, "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. This gives us a better appreciation of how social reactions to infectious diseases can influence which strains become prominent in the population."

This new addition to disease modelling could allow scientists to better prevent undesirable outcomes, such as more dangerous mutant strains from evolving and spreading. 

By adding dynamic social interactions to the models already used for disease outbreaks and evolution, researchers could better anticipate how a pathogen strain may emerge based on how humans attempt to control the spread of the disease.

The social modelling could impact public health responses to emerging infectious diseases like Ebola and Severe Acute Respiratory Syndrome (SARS). 

Human behaviour during these outbreaks often changes dramatically. People may start using face masks, or stop using them prematurely. Also, public fear of the pathogens may end up driving the wrong type of behaviour if the public's information is incorrect.

Bauch and his co-author Joe Pharaon formulated the new mathematical model to study the influence of social behaviour on the competition between pathogen strains with different virulence.