The results of the 2016 US presidential election and the UK vote to leave the European Union (Brexit) have raised questions about the influence of fake online news and social-media 'echo chambers' (see also P. Williamson Nature 540, 171; 2016). The propagation of such information through social networks bears many similarities to the evolution and transmission of infectious diseases. Analysis of transmission dynamics could therefore provide insight into how misinformation spreads and competes online.

For example, disease strains can evolve and compete in a host population, much like rumours, and infections and opinions are both shaped by social contacts. Modelling of competing disease strains indicates that, as contacts become more localized, the diversity of circulating strains can increase (see C. O' F. Buckee et al. Proc. Natl Acad. Sci. USA 101, 10839–10844; 2004). Network structure can also suppress the invasion of new disease strains (see G. E. Leventhal et al. Nature Commun. 6, 6101; 2015).

As more people turn to social networks as a primary news source, transmission models combined with appropriate data could help in exploring the dynamics of this new media landscape.