The article by Lloyd-Smith et al. explores the impact of individual variation in infectiousness on disease emergence and outbreak dynamics. They introduce the concept of the "individual reproductive number" ($r$), which represents the expected number of secondary cases caused by a single infected individual, and use this to model superspreading events (SSEs). The authors analyze contact tracing data from eight directly transmitted diseases to show that the distribution of $r$ is often highly skewed, with a small proportion of highly infectious individuals contributing significantly to transmission. They compare models that assume homogeneous transmission with those that account for individual variation, finding that the latter better explain observed transmission patterns. The study highlights that disease extinction is more likely and outbreaks are rarer but more explosive when individual variation is considered. Additionally, they propose a rigorous definition for SSEs and a method to predict their frequency. The findings suggest that individual-specific control measures are more effective than population-wide measures, emphasizing the need to identify predictive correlates of higher infectiousness. The research has broad implications for emerging disease epidemiology and control strategies.The article by Lloyd-Smith et al. explores the impact of individual variation in infectiousness on disease emergence and outbreak dynamics. They introduce the concept of the "individual reproductive number" ($r$), which represents the expected number of secondary cases caused by a single infected individual, and use this to model superspreading events (SSEs). The authors analyze contact tracing data from eight directly transmitted diseases to show that the distribution of $r$ is often highly skewed, with a small proportion of highly infectious individuals contributing significantly to transmission. They compare models that assume homogeneous transmission with those that account for individual variation, finding that the latter better explain observed transmission patterns. The study highlights that disease extinction is more likely and outbreaks are rarer but more explosive when individual variation is considered. Additionally, they propose a rigorous definition for SSEs and a method to predict their frequency. The findings suggest that individual-specific control measures are more effective than population-wide measures, emphasizing the need to identify predictive correlates of higher infectiousness. The research has broad implications for emerging disease epidemiology and control strategies.