Kalev Leetaru considers the role that online data – even blogs – could have in halting diseases like Ebola:
It turns out that monitoring the spread of Ebola can teach us a lot about what we missed — and how data mining, translation, and the non-Western world can help to provide better early warning tools.
Earlier this month, Harvard’s HealthMap service made world headlines for monitoring early mentions of the current Ebola outbreak on March 14, 2014, “nine days before the World Health Organization formally announced the epidemic,” and issuing its first alert on March 19. Much of the coverage of HealthMap’s success has emphasized that its early warning came from using massive computing power to sift out early indicators from millions of social media posts and other informal media.
As one blog put it: “So how did a computer algorithm pick up on the start of the outbreak before the WHO? As it turns out, some of the first health care workers to see Ebola in Guinea regularly blog about their work. As they began to write about treating patients with Ebola-like symptoms, a few people on social media mentioned the blog posts. And it didn’t take long for HealthMap to detect these mentions.”
The unfortunate flip side:
But there was some great news today:
Meanwhile, Maryam Zarnegar Deloffre assesses the latest US role in combatting the Ebola epidemic – boots on the ground: