University of Waterloo researchers using social media to predict disease outbreaks

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Researchers at the University of Waterloo are using social media in an attempt to forecast when we may see future outbreaks of diseases like COVID-19 and measles.

Using simulations, researchers at the school developed a method that uses social media interactions to predict when an outbreak appears likely.

It considers how a series of small incidents, like people espousing anti-vaccine views, would grow to cause a larger, more important change, such as an outbreak of measles.

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“It’s looking for signals that indicate a bout of vaccine hesitancy or vaccine refusal might be coming, based on characteristics of how people interact on Twitter,” Waterloo professor Chris Bauch told Global News through email.

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He said their “hypothesis is that a bout of vaccine refusal would then lead to an outbreak.”

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Bauch, who is the study’s lead researcher, says the method could be used by decision-makers to determine where we are most likely to have an outbreak.

“Once they’ve identified populations that are exhibiting these signals,



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