Explore the dissolving boundary between science and science fiction with news from the front lines of discovery and imaginative speculation on how each one could change our world.
Here’s one for all you WebMD hypochondriacs. Last month a team from the Harvard Medical School published an article on a new field they term “digital epidemiology”: using the internet and social media to research how disease impacts human populations. Researchers could mine digital data sets to detect the spread of unusual illnesses, estimate the activity levels of certain diseases, or track potential infections by observing people’s geographic movement during outbreaks. Social media could also reveal much about emerging health trends, such as fad cures or new recreational drugs.
Over the past few months, digital epidemiology helped public health officials better understand outbreaks of the Middle East Respiratory Syndrome Coronavirus and Avian Influenza A H7N9. “It is clear that the importance of digital epidemiology will only increase in the future as more people get mobile access to broadband around the globe,” said a member of the Harvard team who uses data from social media in his research to study how sentiments about vaccination spread in populations. “With 6.8 billion mobile-phones and 2.9 billion people online, it’s getting increasingly hard for any micro-organism to spread undetected for long.”
This promising new technique is not without challenges. Aside from the daunting volume of data, collecting information from personal accounts poses legal and ethical challenges. But as globalization enables the spread of diseases at increasingly rapid rates, studying it digitally may help us get ahead of the curve.
So this is how the zombie apocalypse will go down. An overlooked local news blog mentions bite attacks, several Instagram photos showcasing putrid undead flesh, and then an explosion of tweets devoting all 140 characters to “braaaaaaaains”. Facetiousness aside, digital epidemiology could drastically impact the way we study and combat infectious diseases.
For a small-scale example, think of a site like WebMD. A spike in queries on fever and aches, all originating from IP addresses in the northeastern US, could suggest a flu outbreak. Tracking the dates of the searches may show that the searches—and possibly the epidemic—started in New Jersey in early December. Now expand that model to a planet’s worth of texts, tweets, blogs, and posts. Social media has made us all a bit narcissistic: we love to share about ourselves, and illness is no exception. Insert your own punchline about “going viral”!
The potential research value is undeniable. But how will we act upon this data once we’ve interpreted it? Imagine that digital sources reveal a sudden outbreak of virulent avian flu in China. Officials might quarantine the region, and other nations might close their borders to travelers before the disease could spread. What if social media revealed that AIDS sufferers in an African village were popularizing a dangerous new “cure”–would authorities intervene? How could digital epidemiology help in a bioterrorism scenario? The ethics mutate as quickly as the diseases.