Mathew C. Schmidtlein

A Sensitivity Analysis of the Social Vulnerability Index

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 algorithms 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.

Vulnerability of U.S. Cities to Environmental Hazards

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.

Anisotropic path modeling to assess pedestrian-evacuation potential from Cascadia-related tsunamis in the US Pacific Northwest

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.

Community variations in population exposure to near-field tsunami hazards as a function of pedestrian travel time to safety

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.

Disaster Declarations and Major Hazard Occurrences in the United States

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.

Community clusters of tsunami vulnerability in the US Pacific Northwest

Significance We present an analytical framework for understanding community-level vulnerability to tsunamis that integrates population exposure, demographic sensitivity, and evacuation potential.We identify three types of communities along the US Pacific Northwest coast that are directly threatened by tsunamis associated with a Cascadia subduction zone earthquake: (i) demographically diverse with low numbers of exposed people, (ii) high numbers of exposed populations but sufficient time to evacuate, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. This approach is a significant advance over current practice because traditional measures of social vulnerability do not relate population structure to specific hazard characteristics. Results help managers to develop risk reduction strategies that are tailored to local conditions and needs. 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.

Teaching Hazards Geography and Geographic Information Systems: A Middle School Level Experience

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.

Getting More for Your Money Designing Community Needs Assessments to Build Collaboration and Capacity in Hospital System Community Benefit Work

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.

Changes in population evacuation potential for tsunami hazards in Seward, Alaska, since the 1964 Good Friday earthquake

AbstractPedestrian 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.

Funding Priorities: Data-Driven Approach for Prioritizing Community Health Needs in Vulnerable Communities

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.