I’ve written previously about the inherent unpredictability of viral content, and that this makes it next to impossible for any company to predict whether their content will go viral or not.

Nevertheless, understanding of this field continues to improve, especially as insights can be drawn from so many different areas.  Take a recent study for instance into disease control by MIT.

It explored whether the personal freedoms that most of us enjoy, cherish and protect actually harm our societies in the event of a disease outbreak.

“What we were trying to understand better is how actions, in terms of routing humans, could affect the spread of disease,” said study researcher Ruben Juanes, a geoscientist at MIT in Cambridge, Mass.

The study argued that the biggest threat to disease contagion was the dense commuter traffic that carries us to and from work each day.

The paper in particular used the game theory concept of the price of anarchy to explore their hypothesis.  Their experiments took the form of two distinct scenarios:

1. the first allowed free movement of people (ie to avoid infected areas, regardless of whether they themselves were infected),
2. a policy driven scenario saw government agencies dictate that infected individuals could only move within infected areas, whilst healthy individuals had to stay in unaffected areas

The debate was a clear one.  If the cost of personal freedom was low, ie that contagion remained static regardless of restrictions on movement, it provides clear implications for policy responses to infection.

Using commuter data from the census they ran their scenarios and found that restricting movements would benefit some areas much more than others.  If for example a population lived near a major highway, the cost of free movement became much higher, hence restrictions would help contain the disease.  When traffic, in other words movement, was low however, restrictions were much less important.

There were however some exceptions to this rule.  Restrictions of movement in high traffic areas only worked when people lived both in a high traffic area AND near to another high traffic area.

“It was only when we established the longer-range correlation [with neighboring high-traffic areas] that we could make sense of it,” Juanes said.

Of course, having this understanding, and being able to act upon it are often two very different things.  The financial and social cost of restricting movements of a huge group of people is enormous.

As for whether this understanding can provide us with any insights into how content spreads through a network, I’d be fascinated to hear your thoughts in the comments.