In the past 20 years, two revolutions
have unfolded that will change epidemiology forever.
The first one is the Internet.
Almost everyone nowadays is connected to the Internet in one way or another.
The second is the mobile phone revolution. In 2014 there will be more
mobile phones than there will be people. A consequence of these two revolutions is
that all types of modern communication are now digital, and a large fraction of what
we do and say is stored electronically often
in accessible form and thus amenable to analysis.
Part of what we say and do is relevant for epidemiology, such as
deciding on preventive measures and treatment
choices, as well as reporting disease symptoms.
Let's recall what the world was like 20 or 30 years ago.
If you came down with a fever and a
nasty cough, you will probably go and see a doctor.
The doctor, who would see many patients like
you, would maybe be reporting to health authorities
and inform them perhaps on a weekly basis
about what's going on in his or her clinic.
Health authorities would collect
this information from as many doctors as possible, and that would eventually
give them a coherent picture of the epidemiological situation on the ground.
Now, fast forward to the present.
Let's say you came down with a fever and a nasty cough today.
Perhaps you would turn to Google and type in
your symptoms to see if you can diagnose yourself.
You probably
wouldn't go to work and you would perhaps inform your
friends through Facebook and Twitter that you're not feeling well.
You would probably still set up a doctor's appointment, but by the time you get to
see the doctor, the fact that you have
symptoms is already old news on the internet.
Google Flu Trends is an example of a service that makes use of this real-time
information stream.
Google Flu Trends is based on the idea that
certain search terms are good indicators of flu incidence.
So Google takes those millions of flu-related
searches, aggregates them, runs them through a
computational model, and then makes predictions about
flu incidence in a given geographic region.
This is a great demonstration of digital epidemiology.
The downside here is that only Google has
access to the underlying data limiting the research possibilities.
Twitter data, on the other hand, is public by default.
Twitter, as you may know, is a very popular online social network.
When people make health decisions, for example whether to get vaccinated against
the flu or not, or when they feel sick, for example when
they come down with a cold, they may share this information publicly on Twitter.
We can mine and analyze these real-time data streams for epidemiological purposes.
For example, we can build real-time maps of where people seem to
express certain symptoms, or where sentiments
about vaccinations seem to be particularly negative.
My own research
has shown that the sentiments expressed about influenza, H1N1
vaccination in 2009 were a good predictor of vaccination rates in the US.
Being able to use social media data, like data from
Twitter, for public health purposes is an increasingly active research area.
There are many, many other examples. One study
demonstrated how mobile phone data could be used to track population
movement after the Haiti earthquake in 2010, suggesting that estimates of
population movements during disasters and outbreaks can be delivered rapidly, and
with potentially high validity in areas with high mobile phone use.
Another study has demonstrated that over the past years, the time delay between
the onset of a disease outbreak, and the discovery, and reporting of a
disease outbreak, had steadily decreased which
is a result of increased electronic communication.
This is an exciting new field with a vast potential for public health.
But there are a number of challenges ahead.
I'm just going to mention two. The first one is a technical challenge.
Getting a good diagnosis from a doctor is straightforward.
Teaching a computer how to diagnose someone based on what they
say on social media is a challenge to say the least.
The second challenge is of social nature.
Who owns the data and who ensures that privacy is respected?
These are big questions and epidemiology is not
the only field that is going to struggle with
these questions.
But there is no doubt that the internet
and the mobile phone revolution, especially the smart
phone revolution, will continue to push epidemiology into
digital future where diseases can be tracked even faster.