The Patient Protection and Affordable Care Act of 2010 mandated nonprofit hospitals to complete community health needs assessments (CHNAs) every 3 years to identify priority health needs for the community they serve. The CHNA must include input from the community in the determination of health needs. Large variation exists across CHNAs on methods used in the integration of quantitative and qualitative data both in the determination and prioritization of health needs and those needs chosen by the hospital for community benefit funding. An important part of the CHNA is the prioritization of the needs identified, as it can influence hospital community benefit funding decisions. This article describes a method for clearly integrating qualitative and quantitative data in the CHNA process offering a best practice strategy for conducting CHNAs. The method uses an approach based on flexible, objective decision points that can be used to both generate a list of significant health needs and a prioritization of those needs based on community input, influencing funding priorities of the hospital. The method provides a standard approach useful across multiple hospital CHNAs in both rural and urban settings, and in collaborative-based CHNAs (local public health departments and hospitals) as well.

Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience.

Many coastal communities throughout the world are threatened by local (or near-field) tsunamis that could inundate low-lying areas in a matter of minutes after generation. Although the hazard and sustainability literature often frames vulnerability conceptually as a multidimensional issue involving exposure, sensitivity, and resilience to a hazard, assessments often focus on one element or do not recognize the hazard context. We introduce an analytical framework for describing variations in population vulnerability to tsunami hazards that integrates (i) geospatial approaches to identify the number and characteristics of people in hazard zones, (ii) anisotropic path distance models to estimate evacuation travel times to safety, and (iii) cluster analysis to classify communities with similar vulnerability. We demonstrate this approach by classifying 49 incorporated cities, 7 tribal reservations, and 17 counties from northern California to northern Washington that are directly threatened by tsunami waves associated with a Cascadia subduction zone earthquake. Results suggest three primary community groups: (i) relatively low numbers of exposed populations with varied demographic sensitivities, (ii) high numbers of exposed populations but sufficient time to evacuate before wave arrival, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. Results can be used to enhance general hazard-awareness efforts with targeted interventions, such as education and outreach tailored to local demographics, evacuation training, and/or vertical evacuation refuges.

Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions.

Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches.

Most community health needs assessments (CHNAs) are unilateral in nature and fail to include a community-based participatory research (CBPR) approach, limiting them in their scope. Nonprofit hospitals are required to conduct CHNAs every 3 years to determine where community prevention dollars should be spent. In 2010, a CBPR CHNA approach was conducted with four hospital systems in Northern California. Merging concepts from organization development, the approach included (a) goal determination, (b) use of a guiding framework, (c) creation of a container in which to interact, (d) established feedback loops, and (e) intentional trust-building exercises. The approach was to build lasting relationships between hospital systems that would extend beyond the CHNA. Results using this approach revealed that members representing all four hospital systems (a) began to meet regularly after the CHNA was completed, (b) increased collaboration with other community organizations, (c) expanded their level of intraorganization partnerships, (d) enjoyed the process, (e) felt that their professional knowledge expanded, and (f) felt connected professionally and personally with other hospital representatives. As a result, other joint projects are underway. The results of this study indicate that using CBPR to design a CHNA can build sustained collaborative relationships between study participants that continue.

Pedestrian evacuation modeling for tsunami hazards typically focuses on current land-cover conditions and population distributions. To examine how post-disaster redevelopment may influence the evacuation potential of at-risk populations to future threats, we modeled pedestrian travel times to safety in Seward, Alaska, based on conditions before the 1964 Good Friday earthquake and tsunami disaster and on modern conditions. Anisotropic, path distance modeling is conducted to estimate travel times to safety during the 1964 event and in modern Seward, and results are merged with various population data, including the location and number of residents, employees, public venues, and dependent care facilities. Results suggest that modeled travel time estimates conform well to the fatality patterns of the 1964 event and that evacuation travel times have increased in modern Seward due to the relocation and expansion of port and harbor facilities after the disaster. The majority of individuals threatened by tsunamis today in Seward are employee, customer, and tourist populations, rather than residents in their homes. Modern evacuation travel times to safety for the majority of the region are less than wave arrival times for future tectonic tsunamis but greater than arrival times for landslide-related tsunamis. Evacuation travel times will likely be higher in the winter time, when the presence of snow may constrain evacuations to roads.

Most community health needs assessments (CHNAs) are unilateral in nature and fail to include a community-based participatory research (CBPR) approach, limiting them in their scope. Nonprofit hospitals are required to conduct CHNAs every 3 years to determine where community prevention dollars should be spent. In 2010, a CBPR CHNA approach was conducted with four hospital systems in Northern California. Merging concepts from organization development, the approach included (a) goal determination, (b) use of a guiding framework, (c) creation of a container in which to interact, (d) established feedback loops, and (e) intentional trust-building exercises. The approach was to build lasting relationships between hospital systems that would extend beyond the CHNA. Results using this approach revealed that members representing all four hospital systems (a) began to meet regularly after the CHNA was completed, (b) increased collaboration with other community organizations, (c) expanded their level of intraorganization partnerships, (d) enjoyed the process, (e) felt that their professional knowledge expanded, and (f) felt connected professionally and personally with other hospital representatives. As a result, other joint projects are underway. The results of this study indicate that using CBPR to design a CHNA can build sustained collaborative relationships between study participants that continue.

Efforts to characterize population exposure to near-field tsunami threats typically focus on quantifying the number and type of people in tsunami-hazard zones. To develop and prioritize effective risk-reduction strategies, emergency managers also need information on the potential for successful evacuations and how this evacuation potential varies among communities. To improve efforts to properly characterize and differentiate near-field tsunami threats among multiple communities, we assess community variations in population exposure to tsunamis as a function of pedestrian travel time to safety. We focus our efforts on the multiple coastal communities in Grays Harbor and Pacific Counties (State of Washington, USA), where a substantial resident and visitor population is threatened by near-field tsunamis related to a potential Cascadia subduction zone earthquake. Anisotropic, path distance modeling is conducted to estimate travel times to safety, and results are merged with various population data, including residents, employees, public venues, and dependent-care facilities. Results suggest that there is substantial variability among communities in the number of people that may have insufficient time to evacuate. Successful evacuations may be possible in some communities assuming slow walking speeds, are plausible in others if travel speeds are increased, and are unlikely in another set of communities given the large distances and short time horizon. Emergency managers can use these results to prioritize the location and determine the most appropriate type of tsunami risk-reduction strategies, such as education and training in areas where evacuations are plausible and vertical-evacuation structures in areas where they are not.

Recent disasters highlight the threat that tsunamis pose to coastal communities. When developing tsunami-education efforts and vertical-evacuation strategies, emergency managers need to understand how much time it could take for a coastal population to reach higher ground before tsunami waves arrive. To improve efforts to model pedestrian evacuations from tsunamis, we examine the sensitivity of least-cost-distance models to variations in modeling approaches, data resolutions, and travel-rate assumptions. We base our observations on the assumption that an anisotropic approach that uses path-distance algorithms and accounts for variations in land cover and directionality in slope is the most realistic of an actual evacuation landscape. We focus our efforts on the Long Beach Peninsula in Washington (USA), where a substantial residential and tourist population is threatened by near-field tsunamis related to a potential Cascadia subduction zone earthquake. Results indicate thousands of people are located in areas where evacuations to higher ground will be difficult before arrival of the first tsunami wave. Deviations from anisotropic modeling assumptions substantially influence the amount of time likely needed to reach higher ground. Across the entire study, changes in resolution of elevation data has a greater impact on calculated travel times than changes in land-cover resolution. In particular areas, land-cover resolution had a substantial impact when travel-inhibiting waterways were not reflected in small-scale data. Changes in travel-speed parameters had a substantial impact also, suggesting the importance of public-health campaigns as a tsunami risk-reduction strategy.

This paper examines the spatial linkage between social vulnerability and estimated earthquake losses for differing levels of event magnitude. Charleston, South Carolina was selected as the sample urban setting for the study. Earthquake losses (debris generated and direct economic costs) were modeled using the HAZUS-MH software package. Social vulnerability, those characteristics of groups that increase the likelihood of losses or decrease the recovery ability, was modeled using the Social Vulnerability Index (SoVI). Modeled earthquake losses were higher in the urbanized core surrounding the Charleston peninsula and expanded outward, especially east and west of the peninsula along the coast. Physical parameters (peak ground acceleration and distance from the epicenter) were more significant in predicting impacts than social vulnerability. However, in examining the relative impact of earthquake losses accounting for wealth (dollar losses per average income as the dependent variable), we found social vulnerability is a significant predictor, suggesting that those areas with higher levels of social vulnerability experience a greater relative impact and may therefore face more obstacles in post-event recovery than areas with lower social vulnerability.

This article examines the potential geographic inequities between major hazard events and U.S. presidential disaster declarations at the county level from 1965 through 2004. The previous literature suggests that the disaster declaration process is highly politicized and not necessarily based on need. We hypothesize that there is a spatial inequity between the receipt of disaster declarations and the distribution of major hazard events. The results indicate that the geographic distribution of disaster declarations is not totally explained by the spatial pattern of major hazard events. In some locales, state experience in submitting disaster requests and achieving success translates into more disaster declarations (holding everything else constant), providing further evidence of the political nature of the process.

The Social Vulnerability Index (SoVI), created by Cutter et al. (2003) , examined the spatial patterns of social vulnerability to natural hazards at the county level in the United States in order to describe and understand the social burdens of risk. The purpose of this article is to examine the sensitivity of quantitative features underlying the SoVI approach to changes in its construction, the scale at which it is applied, the set of variables used, and to various geographic contexts. First, the SoVI was calculated for multiple aggregation levels in the State of South Carolina and with a subset of the original variables to determine the impact of scalar and variable changes on index construction. Second, to test the sensitivity of the algorithm to changes in construction, and to determine if that sensitivity was constant in various geographic contexts, census data were collected at a submetropolitan level for three study sites: Charleston, SC; Los Angeles, CA; and New Orleans, LA. Fifty‐four unique variations of the SoVI were calculated for each study area and evaluated using factorial analysis. These results were then compared across study areas to evaluate the impact of changing geographic context. While decreases in the scale of aggregation were found to result in decreases in the variance explained by principal components analysis (PCA), and in increases in the variance of the resulting index values, the subjective interpretations yielded from the SoVI remained fairly stable. The algorithm's sensitivity to certain changes in index construction differed somewhat among the study areas. Understanding the impacts of changes in index construction and scale are crucial in increasing user confidence in metrics designed to represent the extremely complex phenomenon of social vulnerability.

Hazards are taught with the belief that knowing something about their occurrence might help us avoid their consequences. The integrative nature of hazards - physical and social systems bound together - is attractive to the student and the instructor alike. Answering why we teach hazards is fairly straightforward. A more pressing question at present is this: how should we teach about hazards? To a large degree, attention towards how we teach hazards in a K-12 environment has been sparse. In this paper we explore the challenges faced when introducing hazards geography in a pre-collegiate setting. Following a review of the status of teaching hazards and the use of geographic information systems as an instructional aid, we outline a hazards course taught successfully for middle school students and discuss implementation obstacles for the traditional classroom.

As cities continue to increase in size, population diversity, and complexity their vulnerability to future disasters will increase as well. This paper explores the variability in vulnerability to natural hazards among the 132 urban areas using three indices of vulnerability: social, built environment, and hazard impact. The paper then examines the relative levels of vulnerability compared to federal UASI funding. The paper demonstrates that vulnerability manifests itself as a place-based regional phenomenon, with the most vulnerable cities located in the eastern half of the U.S. The relative importance of the underlying correlates changes from city to city across the United States with social vulnerability assuming greater importance in the South and Southwest, and built environment vulnerability showing regional primacy as the driving indicator among Northeastern and Midwestern cities. Based on this empirical analysis, New Orleans was the most vulnerable urban area in the U.S. yet received only one percent of the preparedness resources awarded by the federal government.

The 2005 Atlantic hurricane season was the most active season on record and produced 3 category five storms, namely Hurricane Katrina, Hurricane Rita and Hurricane Wilma. The article explores the impact these storms had on the Gulf Coast of the USA. It highlights the effect that Hurricane Katrina had on the structure of New Orleans and also on the people who stayed in the city. Those who stayed were deemed to be the socially vulnerable, and issues of race, ethnicity and poverty were raised. Hurricane Katrina brought national awareness to the deficiencies in preparedness and response to disasters, especially in urban areas. The reconstruction of the area, the rebuilding of peoples' lives and the impact of demographic change are also explored in the article.