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Sandra Williams
MIS 406
Assignment 1
January 25, 2015
Predicting Disease Outbreaks Based on Internet Search Trends
Everyone wants to know more about themselves- whether for fun, to increase
productivity or other ways to better themselves. Recently there’s been a trend in the Quantified
Self movement. People are collecting data about their day to day lives usually through some sort
of technology. In data mining, predictive analytics can take all of the collected data and extract
important information and use it to predict behavioral trends.
People use technology for many aspects of their lives so it is not uncommon for people to
look up their symptoms online when they are sick. WebMD has even become a common site that
can be a resource in helping people understand issues when they are sick. People might find it
easier to stay at home and research their own symptoms, less expensive than visiting a hospital,
or just curiosity as part of understanding their bodies more. But, as a result, the searches done
online can be used as important data in themselves. Location, time, and what you are searching
for as symptoms can all be traced and predictive analytics can predict disease outbreaks.
I was first interested in this idea in a creative coding class when we were data mining
certain hashtags on Twitter through a Twitter API. It’s interesting how much data we are
constantly creating through day to day activities and sharing (willingly or not). My dad also uses
data mining at work and mentioned that Google can predict a disease epidemic before the Center
for Disease Control. I was curious how much truth his statement had.
The four articles I looked at are:
Pelat, Camille et al. “More Diseases Tracked by Using Google Trends.”Emerging Infectious
Diseases 15.8 (2009): 1327–1328. PMC. Web. Jan. 2015.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2815981/
This article was interesting because they did a couple of different studies, discussed
different key words (some in French) and correlations. They found that “ for each of 3 infectious
diseases, 1 well-chosen query was sufficient to provide time series of searches highly correlated
with incidence. We have shown the utility of an Internet search engine query data for
surveillance of acute diarrhea and chickenpox in a non–English-speaking country. Thus, the
ability of Internet search-engine query data to predict influenza in the United States presented by
Ginsberg et al. appears to have a broader application for surveillance of other infectious diseases
in other countries”. Overall, it proved that the trends in searches were definitely helpful in
understanding sicknesses and could be used in different countries.
Varian, Hal & Choi, Hyunyoung. “Predicting the Present with Google Trends.” Economic
Record Volume 88 (2012): 2-9. Wiley Online Library. Web. Jan. 2015.
http://onlinelibrary.wiley.com/doi/10.1111/j.1475-4932.2012.00809.x/full
This article didn’t discuss as much medical. But, it talked about understanding data
mining using Google to overall find patterns and applying it with lots of aspects of life.
Pervaiz, Fahad et al. “FluBreaks: Early Epidemic Detection from Google Flu Trends.” Ed.
Gunther Eysenbach. Journal of Medical Internet Research 14.5 (2012): e125. PMC. Web. Jan.
2015.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3510767/
This article mentioned exactly what my dad told me about: “The Google Flu Trends
service was launched in 2008 to track changes in the volume of online search queries related to
flu-like symptoms. Over the last few years, the trend data produced by this service has shown a
consistent relationship with the actual number of flu reports collected by the US Centers for
Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance
of CDC records.” It’s interesting that it could identify/predict so much faster than the CDC. I’m
curious of the reasons. I was bummed though when it said that the Google Flu Trends service
can’t simply predict epidemics- that it’s only a “baseline indicator of the trend, or changes, in the
number of disease case”. I’m sure there will be ways to tweek it and make it more powerful in
the future so that it can full on predict epidemics of lots of different diseases.
Eysenbach, Gunther. “Infodemiology: Tracking Flu-Related Searches on the Web for Syndromic
Surveillance.” AMIA Annual Symposium Proceedings 2006 (2006): 244–248. Print
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839505/
This article did a study in Canada for 33 weeks in 2004/2005- gathering data from the
internet from flu-related searches. It discussed a lot more infodemiology which studies how
information for health is spread by the public. “The Internet has made measurable what was
previously immeasurable: The distribution of health information in a population, tracking health
information trends over time, and identifying gaps between information supply and demand.”
They also discuss patterns of “(mis)information” outbreaks and needing to fill gaps in knowledge
that the public could have.
Some concerns I have are privacy- does the greater good of predicting and hopefully
stopping an outbreak of a disease trump privacy issues with gathering people’s data and
searches? Also, how reliable are people’s search habits on Google. When Ebola was first
breaking the news, I’m sure a lot of people were Googling the symptoms. Wouldn’t that cause
false ideas of an epidemic based on what’s popular in the media? Is it risky that people can go
online and self-diagnose? There’s always the joke that people go on WebMD and self-diagnose
themselves with crazy things just because some of the symptoms match. Are there other ways
Google could stop diseases? Perhaps countries that don’t have good medical supplies could
connect online and other countries would know how to best aid the people when they are sick. Or
by picking up information from people traveling it could prevent diseases from spreading from
one country to another by predicting and quarantining people who could be carrying a disease.