That’s why in addition to R, scientists use a value called the dispersion factor (k), which describes how much a disease clusters. The lower k is, the more transmission comes from a small number of people. In a seminal 2005 Nature paper, Lloyd-Smith and co-authors estimated that SARS—in which superspreading played a major role—had a k of 0.16. The estimated k for MERS, which emerged in 2012, is about 0.25. In the flu pandemic of 1918, in contrast, the value was about one, indicating that clusters played less of a role.

Estimates of k for SARS-CoV-2 vary. In January, Julien Riou and Christian Althaus at the University of Bern simulated the epidemic in China for different combinations of R and k and compared the outcomes with what had actually taken place. They concluded that k for COVID-19 is somewhat higher than for SARS and MERS. That seems about right, says Gabriel Leung, a modeler at the University of Hong Kong. “I don’t think this is quite like SARS or MERS, where we observed very large superspreading clusters,” Leung says. “But we are certainly seeing a lot of concentrated clusters where a small proportion of people are responsible for a large proportion of infections.” But in a recent preprint, Adam Kucharski of LSHTM estimated that k for COVID-19 is as low as 0.1. “Probably about 10% of cases lead to 80% of the spread,” Kucharski says.