Social Vulnerability to Environmental Hazards

A leading challenge in measuring social vulnerability to hazards is for output metrics to better reflect the context in which vulnerability occurs. Through a meta-analysis of 67 flood disaster case studies (1997–2013), this paper profiles the leading drivers of social vulnerability to floods. The results identify demographic characteristics, socioeconomic status, and health as the leading empirical drivers of social vulnerability to damaging flood events. However, risk perception and coping capacity also featured prominently in the case studies, yet these factors tend to be poorly reflected in many social vulnerability indicators. The influence of social vulnerability drivers varied considerably by disaster stage and national setting, highlighting the importance of context in understanding social vulnerability precursors, processes, and outcomes. To help tailor quantitative indicators of social vulnerability to flood contexts, the article concludes with recommendations concerning temporal context, measurability, and indicator interrelationships.

Social vulnerability to floods: Review of case studies and implications for measurement

Social vulnerability indices have emerged over the past decade as quantitative measures of the social dimensions of natural hazards vulnerability. But how reliable are the index rankings? Validation of indices with external reference data has posed a persistent challenge in large part because social vulnerability is multidimensional and not directly observable. This article applies global sensitivity analyses to internally validate the methods used in the most common social vulnerability index designs: deductive, hierarchical, and inductive. Uncertainty analysis is performed to assess the robustness of index ranks when reasonable alternative index configurations are modeled. The hierarchical design was found to be the most accurate, while the inductive model was the most precise. Sensitivity analysis is employed to understand which decisions in the vulnerability index construction process have the greatest influence on the stability of output rankings. The deductive index ranks are found to be the most sensitive to the choice of transformation method, hierarchical models to the selection of weighting scheme, and inductive indices to the indicator set and scale of analysis. Specific recommendations for each stage of index construction are provided so that the next generation of social vulnerability indices can be developed with a greater degree of transparency, robustness, and reliability.

Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis

Objective A recent HIV outbreak in a rural network of persons who inject drugs (PWID) underscored the intersection of the expanding epidemics of opioid abuse, unsterile injection drug use (IDU), and associated increases in hepatitis C virus (HCV) infections. We sought to identify US communities potentially vulnerable to rapid spread of HIV, if introduced, and new or continuing high rates of HCV infections among PWID. Design We conducted a multistep analysis to identify indicator variables highly associated with IDU. We then used these indicator values to calculate vulnerability scores for each county to identify which were most vulnerable. Methods We used confirmed cases of acute HCV infection reported to the National Notifiable Disease Surveillance System, 2012-2013, as a proxy outcome for IDU, and 15 county-level indicators available nationally in Poisson regression models to identify indicators associated with higher county acute HCV infection rates. Using these indicators, we calculated composite index scores to rank each county's vulnerability. Results A parsimonious set of 6 indicators were associated with acute HCV infection rates (proxy for IDU): drug-overdose deaths, prescription opioid sales, per capita income, white, non-Hispanic race/ethnicity, unemployment, and buprenorphine prescribing potential by waiver. Based on these indicators, we identified 220 counties in 26 states within the 95th percentile of most vulnerable. Conclusions Our analysis highlights US counties potentially vulnerable to HIV and HCV infections among PWID in the context of the national opioid epidemic. State and local health departments will need to further explore vulnerability and target interventions to prevent transmission.

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County-Level Vulnerability Assessment for Rapid Dissemination of HIV or HCV Infections Among Persons Who Inject Drugs, United States.

The Impact of Social Vulnerability on COVID-19 in the U.S.: An Analysis of Spatially Varying Relationships.

Social vulnerability refers to the socioeconomic and demographic factors that affect the resilience of communities. Studies have shown that in disaster events the socially vulnerable are more likely to be adversely affected, i.e. they are less likely to recover and more likely to die. Effectively addressing social vulnerability decreases both human suffering and the economic loss related to providing social services and public assistance after a disaster. This paper describes the development of a social vulnerability index (SVI), from 15 census variables at the census tract level, for use in emergency management. It also examines the potential value of the SVI by exploring the impact of Hurricane Katrina on local populations.

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Edward W. Gregory

Papers

A Social Vulnerability Index for Disaster Management