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"Cutter, Susan L"
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Hurricane Katrina and the forgotten coast of Mississippi
\"Hurricane Katrina slammed into the Gulf Coast in August 2005 with devastating consequences. Almost all analyses of the disaster have been dedicated to the way the hurricane affected New Orleans. This volume examines the impact of Katrina on southern Mississippi. While communities along Mississippi's Gulf Coast shared the impact, their socioeconomic and demographic compositions varied widely, leading to different types and rates of recovery. This volume furthers our understanding of the pace of recovery and its geographic extent, and explores the role of inequalities in the recovery process and those antecedent conditions that could give rise to a \"recovery divide.\" It will be especially appealing to researchers and advanced students of natural disasters and policy makers dealing with disaster consequences and recovery\"-- Provided by publisher.
Book
The landscape of disaster resilience indicators in the USA
The landscape of disaster resilience indicators is littered with wide range of tools, scorecards, indices that purport to measure disaster resilience in some manner. This paper examines the existing qualitative and quantitative approaches to resilience assessment in order to delineate common concepts and variables. Twenty seven different resilience assessment tools, indices, and scorecards were examined. Four different parameters were used to distinguish between them—focus (on assets baseline conditions); spatial orientation (local to global), methodology (top down or bottom up), and domain area (characteristics to capacities). There is no dominant approach across these characteristics. In a more detailed procedure, fourteen empirically based case studies were examined that had actually implemented one of the aforementioned tools, indices, or scorecards to look for overlaps in both concepts measured and variables. The most common elements in all the assessment approaches can be divided into attributes and assets (economic, social, environmental, infrastructure) and capacities (social capital, community functions, connectivity, and planning). The greatest variable overlap in the case studies is with specific measures of social capital based on religious affiliation and civic organizations, and for health access (measured by the number of physicians). Based on the analysis a core set of attributes/assets, capacities, and proxy measures are presented as a path forward, recognizing that new data may be required to adequately measure many of the dimensions of community disaster resilience.
Journal Article
Resilience to What? Resilience for Whom?
The discourse on disaster resilience and vulnerability entails diverse research and policy communities each assigning different meanings to the concepts, which in turn influences their measurement and implementation in decision-making contexts. This invited contribution introduces a themed section with five independently submitted papers on the broad topic of vulnerability and resilience. The distinctive geographical focus on the historical development of vulnerability and resilience and their contemporary manifestations is illustrated by the five internationally focused case studies presented in the themed section.
Journal Article
Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina
As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1 st —September 5 th , 2020. We first describe the initial diffusion of the new confirmed cases per week across the state, which remained under 2,000 cases until Memorial Day weekend (epi week 23) then dramatically increased, peaking in mid-July (epi week 29), and slowly declining thereafter. Second, we found significant differences in cases and deaths between urban and rural counties, partially related to the timing of the number of confirmed cases and deaths and the implementation of state and local mitigations. Third, we found that the case rates and mortality rates positively correlated with pre-existing social vulnerability. There was also a negative correlation between mortality rates and county resilience patterns, as expected, suggesting that counties with higher levels of inherent resilience had fewer deaths per 100,000 population.
Journal Article
Temporal and Spatial Changes in Social Vulnerability to Natural Hazards
During the past four decades (1960-2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades.
Journal Article
Urban-Rural Differences in Disaster Resilience
The concept of disaster resilience has gained attention in political spheres and news outlets over the past few years, yet relatively few empirical measures of the concept exist. Furthermore, research into urban resilience has dwarfed our understanding of disaster resilience in rural places. This schism in what is known about the differences between urban and rural places becomes the topic of this article. Employing a suite of spatial and statistical techniques using an established measure of community resilience, the Baseline Resilience Indicators for Communities (BRIC), we focus on two key questions to better explain the resilience divide between urban and rural areas of the United States. Nonparametric rank analysis, analysis of variance, and logistic regression help describe the relationships between rurality and disaster resilience in contrast to resilience in urban areas. Pinpointing the driving factors, or characteristics, of resilience in rural America compared to metropolitan America, accomplished through binary logistic regression, revealed notable distinctions. Resilience in urban areas is primarily driven by economic capital, whereas community capital is the most important driver of disaster resilience in rural areas. Within rural areas there is considerable spatial variability in the components of disaster resilience. This suggests that attempts to enhance resilience cannot be approached using a one-size-fits-most strategy given the variability in the primary drivers of disaster resilience at county scales.
Journal Article
Leveraging Twitter to gauge evacuation compliance: Spatiotemporal analysis of Hurricane Matthew
Hurricane Matthew was the deadliest Atlantic storm since Katrina in 2005 and prompted one of the largest recent hurricane evacuations along the Southeastern coast of the United States. The storm and its projected landfall triggered a massive social media reaction. Using Twitter data, this paper examines the spatiotemporal variability in social media response and develops a novel approach to leverage geotagged tweets to assess the evacuation responses of residents. The approach involves the retrieval of tweets from the Twitter Stream, the creation and filtering of different datasets, and the statistical and spatial processing and treatment to extract, plot and map the results. As expected, peak Twitter response was reached during the pre-impact and preparedness phase, and decreased abruptly after the passage of the storm. A comparison between two time periods-pre-evacuation (October 2th-4th) and post-evacuation (October 7th-9th)-indicates that 54% of Twitter users moved away from the coast to a safer location, with observed differences by state on the timing of the evacuation. A specific sub-state analysis of South Carolina illustrated overall compliance with evacuation orders and detailed information on the timing of departure from the coast as well as the destination location. These findings advance the use of big data and citizen-as-sensor approaches for public safety issues, providing an effective and near real-time alternative for measuring compliance with evacuation orders.
Journal Article
Degree and direction of overlap between social vulnerability and community resilience measurements
An ongoing debate in academic and practitioner communities, centers on the measurement similarities and differences between social vulnerability and community resilience. More specifically, many see social vulnerability and community resilience measurements as conceptually and empirically the same. Only through a critical and comparative assessment can we ascertain the extent to which these measurement schemas empirically relate to one another. This paper uses two well-known indices—the social vulnerability index (SoVI) and the Baseline Resilience Indicators for Communities (BRIC) to address the topic. The paper employs spatio-temporal correlations to test for differences or divergence (negative associations) and similarities or convergence (positive associations), and the degree of overlap. These tests use continental U.S. counties, two timeframes (2010 and 2015), and two case study sub-regions (to identify changes in measurement associations going from national to regional scales given the place-based nature of each index). Geospatial analytics indicate a divergence with little overlap between SoVI and BRIC measurements, based on low negative correlation coefficients (around 30%) for both time periods. There is some spatial variability in measurement overlap, but less than 2% of counties show hot spot clustering of correlations of more than 50% in either year. The strongest overlap and divergence in both years occurs in few counties in California, Arizona, and Maine. The degree of overlap in measurements at the regional scale is greater in the Gulf Region (39%) than in the Southeast Atlantic region (21% in 2010; 28% in 2015) suggesting more homogeneity in Gulf Coast counties based on population and place characteristics. However, in both study areas SoVI and BRIC measurements are negatively associated. Given their inclusion in the National Risk Index, both social vulnerability and resilience metrics are needed to interpret the local community capacities in natural hazards risk planning, as a vulnerable community could be highly resilient or vice versa.
Journal Article
Measuring social vulnerability to natural hazards in the Yangtze River Delta region, China
Social vulnerability emphasizes the different burdens of disaster losses within and between places. Although China continuously experiences devastating natural disasters, there is a paucity of research specifically addressing the multidimensional nature of social vulnerability. This article presents an initial study on the social vulnerability of the Yangtze River Delta region in China. The goal is to replicate and test the applicability of the place-based Social Vulnerability Index (SoVI®) developed for the United States in a Chinese cultural context. Twenty-nine variables adapted from SoVI® were collected for each of the 134 analysis units in the study area. Using principal components analysis, six factors were identified from the variable set: employment and poverty, education, poor housing quality, minorities, family size, and housing size—factors similar to those identified for the United States. Factor scores were summed to get the final SoVI® scores and the most and least vulnerable study units were identified and mapped. The highest social vulnerability is concentrated in the southern portions of the study area—Jingning, Suichang, Yunhe, Lanxi, Pan’an, and Shengsi. The least socially vulnerable areas are concentrated southwest, west, and northwest of Shanghai. Limitations of replication are discussed along with policy-relevant suggestions for vulnerability reduction and risk mitigation in China.
Journal Article
Global risks: Pool knowledge to stem losses from disasters
Public awareness, rigorous risk research and aligned targets will help policy-makers to increase resilience against natural hazards, say Susan L. Cutter and colleagues.
Journal Article