On March 14 of this year, an orange dot popped up on the disease-tracking website, HealthMap, describing a "mystery hemorrhagic fever" that had killed several people in Guinea.
Nine days later, the World Health Organization issued an alert sounding the alarm that 29 people had died after contracting the Ebola virus in the West African country. The WHO alert marked the first official confirmation of what has become the worst outbreak of the disease, which has now claimed more than 1000 lives.
Watch "Ebola: Are We Next?" on Thursday, Sep. 18, starting at 9/8c on both Discovery Channel and Discovery Fit & Health.
For diseases that can spread rapidly like Ebola, early detection is crucial. There is still no cure or effective treatment against the Ebola virus, so isolating patients is the only way of avoiding an epidemic. Any methods or tools that could speed up the detection of outbreaks, even if only by a few days, could be a huge help in containing the disease.
That's exactly what HealthMap is trying to do. It was introduced in 2006 by two researchers at Boston Children's Hospital: John Brownstein, an epidemiologist and professor of pediatrics, and Clark Freifeld, a software developer who is now studying for his PhD in biomedical engineering at Boston University. The software tool they built collects data from the Internet in real time, looking at a wide variety of sources, including Twitter feeds, local newspaper articles, eyewitness reports as well as official data from governments and organizations like the WHO and then plots pertinent information on an interactive map.
"We use natural language processing, machine learning, and cluster detection to represent a global view of epidemics," explains Brownstein. "As these sources build up, they bring together a picture of a serious situation for us. Our analysts work to synthesize and we disseminate the information via various channels."
HealthMap's Web-scraping algorithms are optimized to ignore unreliable and irrelevant sources. But another layer of sorting is provided by a team of humans that manually picks through the parser results to remove any suspicious entries before adding them to the map.