Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard types (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the "lessons learned" from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to academic disciplines at the detriment to the advancement of the field of risk communications research writ large. We tested this hypothesis by evaluating the disciplinarity of 5,078 published articles containing risk and crisis communication keywords using a combination of simple descriptive statistics, natural language processing, and hierarchical clustering. Finding that the risk communication research is siloed according to disciplinary lexicons, we present our findings as a call for convergence amongst our risk and crisis communication scholars to bridge across our silos. In so doing, we will increase our ability to affect transformative change in the efficacy of our risk and crises messages across myriad hazard types - from cyclones to cybersecurity.

Emergency managers (EMs) need nuanced data that contextualize the local-scale risks and impacts posed by major storm events (e.g. hurricanes and nor'easters). Traditional tools available to EMs, such as weather forecasts or storm surge predictions, do not provide actionable data regarding specific local concerns, such as access by emergency vehicles and potential communication disruptions. However, new storm models now have sufficient resolution to make informed emergency management at the local scale. This paper presents a Participatory Action Research (PAR) approach to capture critical infrastructure managers concerns about hurricanes and nor'easters in Providence, Rhode Island (USA). Using these data collection approach, concerns can be integrated into numerical storm models and used in emergency management to flag potential consequences in real time during the advance of a storm. This paper presents the methodology and results from a pilot project conducted for emergency managers and highlights implications for practice and future academic research.

All regions of the US experience disasters which result in a number of negative public health consequences. Some populations have higher levels of social vulnerability and, thus, are more likely to experience negative impacts of disasters including emotional distress, loss of property, illness, and death. To mitigate the impact of disasters on at-risk populations, emergency managers must be aware of the social vulnerabilities within their community. This paper describes a qualitative study which aimed to understand how emergency managers identify social vulnerabilities, also referred to as at-risk populations, in their populations and barriers and facilitators to current approaches. Findings suggest that although public health tools have been developed to aid emergency managers in identifying at-risk populations, they are not being used consistently. Emergency managers requested more information on the availability of tools as well as guidance on how to increase ability to identify at-risk populations.

Each of the nuclear power plants in the US is encircled by an Emergency Planning Zone (EPZ). Within each EPZ, government officials, utility professionals, emergency managers, and public health practitioners collectively conduct extensive planning, exercises, and outreach to better protect their communities in the event of a nuclear accident. Our objective was to conduct a cross-sectional study of off-site public health preparedness within EPZs to better understand the dynamics of nuclear preparedness and uncover lessons for all-hazards preparedness.