The COVID-19 pandemic, while a global health crisis, gave scientists a unique chance to learn more about vaccines and public health strategies. At the same time, it opened the door to studying a different kind of contagion: the spread of ideas.

A study from the University of Vermont looks at how the structure of human interaction networks influences the spread of both disease and information. The goal is to understand how social connections affect not just the transmission of illness but also the spread of ideas and beliefs.

The researchers used a mixed approach to social networks, focusing not only on who interacts with whom but also on the rules that govern how diseases and information spread. “With the pandemic, we have more data than ever on diseases,” they say. “The question is: How do we use that data, and how much do we need to figure out how people are connected?”

The limits of data

The challenge lies in knowing the limits of the data and understanding how confident we can be when using models to predict the spread of diseases. The study suggests it’s easier to map social networks for diseases like COVID-19 or the common cold, but this method is less effective for highly contagious illnesses like measles.

Interestingly, when it comes to tracking the spread of trends or information, the study suggests it may be easier to follow their paths than it is for diseases. This finding could help future efforts to understand both contagion and the spread of misinformation.