In this paper, a dynamic and stochastic notion of public transport network vulnerability is developed. While previous studies have considered only the network topology, the granular nature of services requires a more refined model for supply and demand interactions in order to evaluate the impacts of disruptions. We extend the measures of betweenness centrality (often used to identify potentially important links) and link importance to a dynamic-stochastic setting from the perspectives of both operators and passengers. We also formalize the value of real-time information (RTI) provision for reducing disruption impacts. The developed measures are applied in a case study for the high-frequency public transport network of Stockholm, Sweden. The importance ranking of the links varies depending on the RTI provision scheme. The results suggest that betweenness centrality (passenger/vehicle flows) may not be a good indicator of link importance. The results of the case study reveal that while service disruptions have negative effects and RTI may have significant positive influence, counter examples also exist due to secondary spillover effects.