Predicting disease outbreaks using social media

University of Waterloo researchers have developed a method to predict disease outbreaks by analyzing vaccine sentiment on social media. Using a machine learning model based on the mathematical concept of tipping points, the team can identify when vaccine skepticism is rising, which often precedes outbreaks. Their model was tested by analyzing public posts on X (formerly Twitter) before a 2014 measles outbreak in California, providing a much earlier warning than traditional methods. This approach can be adapted for other platforms like TikTok and Instagram. The research highlights the potential of applied mathematics in public health monitoring and decision-making.