How society organizes affects different phenomena, from the transmission of data to the spread of contagious diseases. The more links we establish with one another via social and transportation networks, the more spread is favored. To review the dynamics of complex systems, resembling society, we are able to infer these networks – by which nodes, representing individuals, connect through lines – from real-world data. Nonetheless, these networks are frequently large, dense, and cumbersome to control.

In previous work, Luís M. Rocha’s group on the Instituto Gulbenkian de Ciência (IGC) found a strategy to simplify networks by extracting their backbones. The principle behind this method is kind of easy: it finds the shortest path to achieve every other point in a network and deletes redundant alternatives. But how will we find these shorter paths?

Within the three-dimensional world we live in, we’re used to pondering by way of shortest paths, as an illustration, the right way to go from home to work through the shortest/fastest possible route. But in multi-dimensional systems (adding traffic, multiple modes of transportation, and road constructions), the shortest path is just not necessarily the direct path between two points.”

Rion B. Correia, Postdoc, Instituto Gulbenkian de Ciência

Even when there are infinite ways to get from A to B, with this method researchers can concentrate on a very powerful paths. Since then, the researchers have applied it to review quite a lot of networks, from gene interactions to essential communication pathways within the brain.

Now, the team took this method to an entire recent level by testing it on real human contacts. For this, they used previously recorded contacts between nearly 3000 individuals using wearable proximity sensors in quite a lot of social settings, including schools, a hospital and an art exhibit. Then, they transformed this contact data into social networks, where links represent the period of time people spent together.

The researchers concluded that the backbones of social contact networks were very small. “Because of this plenty of connections in human communities are redundant”, Rion, first writer of this study, explains. Surprisingly, this backbone still preserved the community structure, stemming from people’s tendency to cluster in groups. And it did it a lot better than other methods.

Reduced to 6-20% of the unique networks, the backbones make it much easier to grasp how communities organize and study easy transmission dynamics. On this study, the researchers demonstrated that the backbone is a reliable tool to clarify how processes resembling viral infection spread in a population, in addition to to discover essentially the most relevant social contacts to stop contagion. However the implications of the backbone of social systems go much beyond epidemiology. “The recent pandemic demonstrated that our social lives and overall public health depends heavily on interactions that cross scales from the molecular network of minute pathogens to all our transportation, health, economy, ecology, and governance networks”, Luís highlights. “Our basic research on backbones adds one other tool within the study of networks that link the tiniest virus to essentially the most potent economy. It is simply through the basic understanding of how these systems interact that we are able to solve these XXI century problems”, he concludes.

Source:

Instituto Gulbenkian de Ciência

Journal reference:

Correia, R. B, et al. (2023) Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs. PLoS Computational Biology. doi.org/10.1371/journal.pcbi.1010854.