Abstract: Federal, State, and local decision makers and public health officials must prepare and exercise complex plans to contend with a variety of possible mass casualty events, such as pandemic influenza. Through the provision of quick look tools (QLTs) focused on mass casualty events, such planning can be done with higher accuracy and more realism through the combination of interactive simulation and visualization in these tools. If an event happens, the QLTs can then be employed to rapidly assess and execute alternative mitigation strategies, and thereby minimize casualties. This can be achieved by conducting numerous “what-if” assessments prior to any event in order to assess potential health impacts (e.g., number of sick individuals), required community resources (e.g., vaccinations and hospital beds), and optimal mitigative decision strategies (e.g., school closures) during the course of a pandemic. In this presentation, we overview and demonstrate a pandemic influenza QLT, discuss some of the modeling methods and construct and visual analytic components and interface, and outline additional development concepts. These include the incorporation of a user selectable infectious disease palette, simultaneous visualization of decision alternatives, additional resource elements associated with emergency response (e.g., first responders and medical professionals), and provisions for other potential disaster events.

Abstract: Crisis management efforts in the United States public health sector aim to prepare and protect the life of an individual, family or group against a health-related event. These efforts span governmental, nongovernmental and private sectors. The need for coordination between these organizations has never been more apparent. A solution will depend heavily on standardized communication protocols using information and communication technology (ICT). Numerous initiatives are currently addressing the needs of our nation with respect to homeland security and public health, yet remain in the early stages for the nongovernmental sector. The emphasis of our research is at the local level where the governmental sector extends to the nongovernmental sector (NGO), particularly community outreach. Our analysis of the local community suggests focusing on the management of communication during public health crises to better understand the complexities and variations presented in these communities. Leveraging experiences from media-technology literature findings and emergency-response efforts, we seek to identify a framework and tools to enable effective communication for those public health practitioners who serve as front-line responders to public health crises. The major contributions of this research will be to extend the use of information systems and mobile technology to the local United States public health communities to increase effective communication between organizations, while providing a state of readiness for homeland security related events.

Abstract: This paper depicts the real-time sensemaking of experts as they worked to combat the first emerging disease of the 21st century: Severe Acute Respiratory Syndrome (SARS). Newspaper data was analysed from the 2003 SARS crisis, with a Canadian perspective, to follow the process of solving the puzzle of this emerging disease. Retrospective sensemaking is a process that is triggered by the unexpected, which leads to actors gathering information (taking action) in order to consider possible interpretations for the unexpected event. Disease outbreaks serve as sensemaking triggers, and actors engage in retrospective sensemaking to find out the factors involved in how the outbreak happened. Prospective sensemaking (future-oriented) is employed when actors work together to plan how to combat the disease. The newspaper data demonstrate that retrospective and prospective sensemaking are tethered: to make plans to combat a disease, actors first require a collectively agreed upon understanding from which they can generate possibilities for a crisis response. This paper contributes to the field by providing concepts for long-duration crisis sensemaking, as the bulk of organisational research focuses on acute crises such as wildfires, or earthquakes.

Abstract: The STATPack is a telemedicine consultation and emergency response system which was developed to increase statewide laboratory responsiveness to public health emergencies. Although several emergency response management information systems have been created for diagnostic laboratories at the national level, most states in the U.S. do not have the capability to share critical public health microbiology laboratory information at local levels, especially in rural communities. This paper offers a description and preliminary assessment of the STATPack as it is being deployed by the Nebraska Public Health Laboratory and should be recognized as research in-progress. Initial experiences with this emergency response system have been encouraging.

Abstract: The Interactive Media Laboratory at Dartmouth Medical School produces computer games and multimedia programs for public health preparedness. With Department of Homeland Security funding, the IML is developing the Virtual Terrorism Response Academy, which uses game technology to prepare first responders for rescue efforts in which hazardous materials may be involved. This paper looks at the history of the “Virtual Clinic” concept and the original rationale for creating what Max Boisot calls “epistemology space.” It also offers an account of the VRTA designers' responses to potential criticism from learning specialists in game studies who object that the game is too didactic and discourages trial-and-error by restraining the learner in the narrative conceit of a “simulation of a simulation.”.

Abstract: The COVID-19 pandemic has generated unprecedented, devastating impacts across the United States. However, some communities have disproportionately endured adverse health outcomes and socioeconomic injuries. Ascertaining the factors driving these inequities is crucial to determining how policy could mitigate the impacts of future public health crises. We have established research-driven metrics, aggregated as the Community Vulnerability Index (CVI), that quantify vulnerability to public health and economic impacts of COVID-19. We performed two analyses to better understand similarities between communities in terms of the vulnerabilities represented by the metrics. We performed an unsupervised k-means clustering analysis to understand whether communities can be grouped together based on their levels of negative social and health indicators. Our goal for this analysis is to determine whether attributes of the constructed clusters reveal areas of opportunity for potential policy impacts and future disaster response efforts. We also analyzed similarities between communities across time using time-sensitive clustering analysis to discover whether historical community vulnerabilities were persistent in the years preceding the pandemic and to better understand the historical factors associated with disparate COVID-19 impacts. In particular, we highlight where communities should invest based on their historical health and socioeconomic patterns and related COVID impacts. Through extensive interpretation of our findings, we uncover how health policy can advance equity and improve community resilience.