Early Detection of Pandemics and Outbreaks
In this article, we outline initial results from a system developed to detect near-real-time early signals of illnesses and their adverse effects within the vaping community.
The system was designed following the 2019 EVALI outbreak to raise alerts based on early online signals, and to create early awareness of potentially evolving clinical situations. We also present an initial analysis of COVID-19-related on line activity that was detected by this system. For both EVALI and COVID-19, we show that early signals and social media discussions precede official publications in news channels and can indeed provide authorities with crucial time to prepare for potential outbreaks.
We show that early signals and discussions on social networks precede official publications in traditional news channels. Applying advanced analytics platforms on a global scale can benefit decision-makers during outbreaks by detecting early signs for disease spread, associated symptoms, adverse events, and risk factors.Read the Report