Healthcare
Case StudyBlueDot

BlueDot identified Wuhan pneumonia outbreak from social media posts before WHO made public announcement on COVID-19

BlueDot picked up on a cluster of “unusual pneumonia” cases happening near a market in Wuhan, China, and flagged it. This would become better known as the epicentre of what would come to be known as COVID-19. This was nine days before the World Health Organization released its statement alerting people to the emergence of a novel coronavirus in China.

Context

BlueDot was set up to monitor for, observe and predict risk of disease outbreaks, with a focus on providing early warning against disease spread vectors.

The Project

BlueDot is proprietary software-as-a-service (SAAS) designed to track, locate and visualise infectious disease spread. It uses natural language processing and machine learning to cull data from multiple sources, including official public health statements, digital media, global airline ticketing data, livestock health reports and population demographics. It updates every 15 minutes. Experts review the AI findings and create reports that are sent out. “We don’t use artificial intelligence to replace human intelligence, we basically use it to find the needles in the haystack and present them to our team,” Khan said [to CNBC].

Data

Multiple data sources including public statements and movement vector information (e.g. ticketing).

Results

BlueDot alerted its subscribers to an emerging disease risk in Wuhan 9 days before the World Health Organisation went public on the issue.

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