Measurement, mechanistic and geospatial models of public health hazard vulnerability and jurisdictional risk

County and state public health departments are increasingly conducting hazard vulnerability and jurisdictional risk (HVJR) assessments as part of their public health emergency planning. These assessments involve the measurement of hazards (exposure), environmental, physical, social and health vulnerabilities (susceptibility), and community resources available to counter the disaster impact (resilience). We undertook a quantitative analysis to validate measurement and mechanistic models of HVJR using geographical information system (GIS) mapping and multivariate statistical techniques. GIS mapping was used to develop the hypothetical mechanistic model by visually examining the variability and patterns associated with county-level demographic, social, economic, hazards and resource data. Map layers were created that maximized the separation of geographical areas and these results were later used to select the most parsimonious measurement and mechanistic models for further testing and evaluation. We utilized public access data and Esri Community Analyst online software to perform a visualization analysis using GIS mapping and to hypothesize the causal pathways linking exposure and vulnerability to hazard impact. Conclusions: The most widely used HVJR models involve hundreds of probability estimates and individual item ratings that are then combined into a simple linear equation typically without testing or validating the latent variable constructs of exposure, vulnerability and resilience at the measurement level, and the causal pathways at the structural level. GIS mapping and multivariate methods can be used to confirm and validate measurement and mechanistic models of HVJR to increase the accuracy and predictive validity of these models and to optimize public health preparedness planning.