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Twitter Can Track Disease -- Can ItPredict Outbreaks?


After analyzing 17 million mentions of
illness in Facebook posts and tweets
(separating "Bieber fever" from actual
fever) and plotting genuine ailment
mentions on a map, founder of
Sickweather, Graham Dodge, has noticed trends in how disease
spreads throughout the United States.
For one thing, disease spreads most
quickly between Hartford, Conn. and
Washington D.C., an area he has
dubbed "contagion alley." [More from Mashable: Why You Should Consider an Electric Vehicle] And it is impacted by big events like the Super Bowl. When the New York Giants played the New England
Patriots in Indianapolis this February,
Twitter mentions of illness in
Indianapolis spiked, more than
doubling those in demographically
similar city Dayton, Ohio. Several studies have already suggested that social media can
accurately track disease. But
observations like these, Dodge thinks,
can eventually be used to anticipate
outbreaks faster than ever before. [More from Mashable: 7 Alternatives to Airtime Video Chat ] His company, Sickweather, is the first consumer-facing product to take a
serious stab at tracking disease
through social media chatter. Its technology scans social networks
for mentions of 24 different
symptoms. Through semantic
analysis, it decides which mentions
actually refer to illness, and plots them
at the location where they originate. The result is an interactive map
searchable by location and illness.
Users can also add their ailments
directly to the map. Sickweather shows social media
mentions of disease symptoms on a
map Tracking disease through online
activity has been done before.
Researchers from Google and Yahoo found that search terms were good
indicators of flu activity in 2008 and
2009. In 2010 Google launched
Google Flu Trends, which provides
public estimations for flu activity. Social media, however, is an improved
digital disease indicator. "It inherently provides more context
to the individual's situation for natural
language processing to better qualify
what the person means, e.g. a tweet
of 'I have the flu' versus a search of
the word 'flu,'" Dodge explains. There are a variety of indicators that
help track disease, including
emergency room visits and over-the-
counter medication purchases, but,
says Mark Dredze -- who has co-
authored a study about Twitter's applicability to public health research
-- "social media is one of the fastest." While it might take weeks for the CDC
to report disease trends, social media
is rife with real-time data that can help
public health officials more quickly
anticipate demand for medication and
health services. Therefore, it's not a surprise that the
Department of Health and Human
Services is interested in the approach.
It recently launched a contest calling
for apps that not only track how
disease trends have developed in the past, but that also use social media as
an advance signal of a public health
emergency. ?When we looked back at the H1N1
pandemic, we saw that, in some
cases, social media trends provided
the first clues to flu outbreaks,? said
Dr. Nicole Lurie, the assistant secretary
for preparedness and response, when the contest launched in March. Sickweather is among the entrants
vying for the contest's USD 21,000
prize. Here's where it differs from the
methods that have been proven
before: Dodge believes that adding
data from travel patterns, event
schedules, weather patterns or
environmental roadside data into the mix could allow Sickweather to
anticipate outbreaks even faster than
social data alone. "Think of it like the early days of
weather forecasting," says Dodge.
"We're basically transitioning from the
Farmers' Almanac to Doppler radar." In one analysis of social media
mentions of illness, Sickweather
found a spike in mentions around
Indianapolis, during the weekend it
hosted the Superbowl.