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.