Although it would seem logical that the more people stay within their own social groups and avoid others, the less likely a small disease outbreak will turn into full-blown epidemic. Now, a new paper suggests otherwise.
Researchers at the multidisciplinary Santa Fe Institute in New Mexico contend that when two separate diseases interact with each other, a population clustered into relatively isolated groups can ignite epidemics that spread like wildfire.
The work by Drs. Laurent Hébert-Dufresne and Benjamin Althouse has been published in the Proceedings of the National Academy of Sciences.
“We thought we understood how clustering works,” Hébert-Dufresne said, ”but it behaves exactly opposite to what we thought once interactions are added in. Our intuition was totally wrong.”
At the heart of the new study are two effects that have gained a lot of attention in recent years — social clustering and co-infection — but haven’t been studied together. That, Hébert-Dufresne and Althouse say, turns out to be a major omission.
Ordinarily, the pair says, clustering limits outbreaks. Maybe kids in one preschool get sick, for example, but because those kids don’t see kids from other preschools very often, they’re not likely to spread the disease very far.
Co-infection often works the other way. Once someone is sick with, say, pneumococcal pneumonia, they’re more likely than others to come down with the flu, lowering the bar for an epidemic of both diseases.
Researchers learned that when the two effects are coupled, an unexpected result occurs. Computational modeling showed that when you put the effects together, you get something that is more, and different, than the sum of its parts.
While clustering works to prevent single-disease epidemics, interactions between diseases like pneumonia and the flu help keep each other going within a social group long enough that one of them can break out into other clusters, becoming a foothold for the other, or perhaps a spark in a dry forest.
Once co-infection happens, the diseases, Althouse says, “can catch fire.” The end result is a larger, more rapidly developing epidemic than would otherwise be possible.
That conclusion has immediate implications for public health officials, whose worst-case scenarios might be different or even tame compared with the outbreaks Hébert-Dufresne and Althouse hypothesize.
But there are interesting implications for network scientists and complex systems researchers, who often think in epidemiological terms. Two ideas, for example, might interact with one another such that both spread more rapidly than they would on their own, just as diseases do.
“We hope to take this work in new and different directions in epidemiology, social science, and the study of dynamic networks,” Althouse says. “There’s great potential.”
The Santa Fe Institute explores the common fundamental principles in complex physical, computational, biological, and social systems that underlie many of the most profound problems facing science and society today. According to the institute, complex problems require novel ideas that result from thinking about non-equilibrium and highly connected complex adaptive systems.