scholarly journals Exploratory Bivariate and Multivariate Geovisualizations of a Social Vulnerability Index

2020 ◽  
Author(s):  
Georgianna Strode ◽  
Victor Mesev ◽  
Susanne Bleisch ◽  
Kathryn Ziewitz ◽  
Fennis Reed ◽  
...  
Keyword(s):  
Social Vulnerability ◽  
Visual Analytics ◽  
Vulnerability Index ◽  
The United States ◽  
Public Health Research ◽  
Household Composition ◽  
Vulnerable Groups ◽  
Social Vulnerability Index ◽  
National Agency ◽  
Emergency Responders

In the United States, the Centers for Disease Control and Prevention (CDC) is the national agency that conducts and supports public health research and practice. Among the CDC’s many achievements is the development of a social vulnerability index (SVI) to aid planners and emergency responders when identifying vulnerable segments of the population, especially during natural hazard events. The index includes an overall social vulnerability ranking as well as four individual themes: socioeconomic, household composition & disability, ethnicity & language, and housing & transportation. This makes the SVI dataset multivariate, but it is typically viewed via maps that show one theme at a time. This paper explores a suite of cartographic techniques that can represent the SVI beyond the univariate view. Specifically, we recommend three techniques: (1) bivariate mapping to illustrate overall vulnerability and population density, (2) multivariate mapping using cartographic glyphs to disaggregate levels of the four vulnerability themes, and (3) visual analytics using Euler diagrams to depict overlap between the vulnerability themes. The CDC’s SVI, and by extension, vulnerability indices in other countries, can be viewed in a variety of cartographic forms that illustrate the location of vulnerable groups of society. Viewing data from various perspectives can facilitate the understanding and analysis of the growing amount and complexity of data.

scholarly journals Applying the Social Vulnerability Index as a Leading Indicator to Protect Fire-Based Emergency Medical Service Responders’ Health

2021 ◽  
Vol 18 (15) ◽  
pp. 8049
Author(s):  
Emily J. Haas ◽  
Alexa Furek ◽  
Megan Casey ◽  
Katherine N. Yoon ◽  
Susan M. Moore
Keyword(s):  
Emergency Response ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Fire Service ◽  
Household Composition ◽  
Fire Departments ◽  
Social Vulnerability Index ◽  
Response Planning ◽  
Leading Indicator ◽  
Increased Risk

During emergencies, areas with higher social vulnerability experience an increased risk for negative health outcomes. However, research has not extrapolated this concept to understand how the workers who respond to these areas may be affected. Researchers from the National Institute for Occupational Safety and Health (NIOSH) merged approximately 160,000 emergency response calls received from three fire departments during the COVID-19 pandemic with the CDC’s publicly available Social Vulnerability Index (SVI) to examine the utility of SVI as a leading indicator of occupational health and safety risks. Multiple regressions, binomial logit models, and relative weights analyses were used to answer the research questions. Researchers found that higher social vulnerability on household composition, minority/language, and housing/transportation increase the risk of first responders’ exposure to SARS-CoV-2. Higher socioeconomic, household, and minority vulnerability were significantly associated with response calls that required emergency treatment and transport in comparison to fire-related or other calls that are also managed by fire departments. These results have implications for more strategic emergency response planning during the COVID-19 pandemic, as well as improving Total Worker Health® and future of work initiatives at the worker and workplace levels within the fire service industry.

scholarly journals Modeling the COVID-19 Vaccination Dynamics in the United States: An Estimation of Coverage Velocity and Carrying Capacity Based on Socio-demographic Vulnerability Indices in California

2021 ◽  
Author(s):  
Alexander Bruckhaus ◽  
Aidin Abedi ◽  
Sana Salehi ◽  
Trevor A Pickering ◽  
Yujia Zhang ◽  
...  
Keyword(s):  
Vaccine Coverage ◽  
Vulnerability Index ◽  
The United States ◽  
Household Composition ◽  
Social Vulnerability Index ◽  
Vaccination Rates ◽  
Group Methods ◽  
The Social ◽  
Data Points ◽  
Maximum Proportion

Introduction: Coronavirus disease 2019 (COVID-19) disparities among vulnerable populations are a paramount concern that extends to COVID-19 vaccine administration. We aim to better characterize the scope of vaccine inequity in California by comparing the Social Vulnerability Index (SVI) of California counties and respective vaccination rates, modeling the growth rate and anticipated maximum proportion of individuals vaccinated by SVI group. Methods: Overall SVI, its four themes, and 9228 data points of daily vaccination numbers across all 58 California counties were used to model, overall and by theme, growth velocity of proportion of population vaccinated and the expected maximum proportion of individuals (at least 1 dose of Pfizer-BioNTech, Moderna, or Johnson & Johnson/Janssen) that will be vaccinated for each theme. Results: Overall high vulnerability counties in California have lower vaccine coverage velocity compared to low and moderate vulnerability counties. The largest disparity in coverage velocity between low and highly vulnerable counties was observed in Theme 3 (minority status & language). However, our model showed that highly vulnerable counties based on Theme 3 are expected to eventually achieve a higher proportion of vaccinated individuals compared to low vulnerable counterparts if current trajectories continue. Counties in the overall low vulnerability category are estimated to achieve a higher proportion of vaccinated individuals when compared to high and moderate vulnerable counties, assuming current trajectories. The largest disparity in asymptotic proportion vaccinated between high and low vulnerable counties was observed in Theme 2 (household composition & disability). Conclusion: This study provides insight into the problem of COVID-19 vaccine disparity across California which can be used to help promote equity during the current pandemic as well as guide the allocation of future vaccines such as COVID-19 booster shots.

Can the Social Vulnerability Index Be Used for More Than Emergency Preparedness? An Examination Using Youth Physical Fitness Data

2016 ◽  
Vol 13 (2) ◽  
pp. 121-130 ◽  
Author(s):  
Jennifer L. Gay ◽  
Sara W. Robb ◽  
Kelsey M. Benson ◽  
Alice White
Keyword(s):  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass ◽  
Emergency Preparedness ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Household Composition ◽  
Minority Status ◽  
Social Vulnerability Index ◽  
The Social

Background:The Social Vulnerability Index (SVI), a publicly available dataset, is used in emergency preparedness to identify communities in greatest need of resources. The SVI includes multiple socioeconomic, demographic, and geographic indicators that also are associated with physical fitness and physical activity. This study examined the utility of using the SVI to explain variation in youth fitness, including aerobic capacity and body mass index.Methods:FITNESSGRAM data from 2,126 Georgia schools were matched at the census tract level with SVI themes of socioeconomic, household composition, minority status and language, and housing and transportation. Multivariate multiple regression models were used to test whether SVI factors explained fitness outcomes, controlling for grade level (ie, elementary, middle, high school) and stratified by gender.Results:SVI themes explained the most variation in aerobic fitness and body mass index for both boys and girls (R2 values 11.5% to 26.6%). Socioeconomic, Minority Status and Language, and Housing and Transportation themes were salient predictors of fitness outcomes.Conclusions:Youth fitness in Georgia was related to socioeconomic, demographic, and geographic themes. The SVI may be a useful needs assessment tool for health officials and researchers examining multilevel influences on health behaviors or identifying communities for prevention efforts.

Abstract 16562: Association of County-Level Social Vulnerability Index and Cardiovascular Disease in the United States, 1999-2018

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Quentin R Youmans ◽  
Megan E McCabe ◽  
Clyde W Yancy ◽  
Lucia Petito ◽  
Kiarri N Kershaw ◽  
...  
Keyword(s):  
United States ◽  
Cardiovascular Disease ◽  
Social Vulnerability ◽  
Cardiovascular Health ◽  
Vulnerability Index ◽  
The United States ◽  
County Level ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
Cvd Mortality

Introduction: Social determinants of health are multi-dimensional and span various interrelated domains. In order to inform community-engaged clinical and policy efforts, we sought to examine the association between a national social vulnerability index (SVI) and age-adjusted mortality rate (AAMR) of CVD. Hypothesis: Higher county-level SVI or greater vulnerability will be associated with higher AAMR of CVD between 1999-2018 in the United States. Methods: In this serial, cross-sectional analysis, we queried CDC WONDER for age-adjusted mortality rates (AAMRs) per 100,000 population for cardiovascular disease (I00-78) at the county-level between 1999-2018. We quantified the association of county-level SVI and CVD AAMR using Spearman correlation coefficients and examined trends in CVD AAMR stratified by median SVI at the county-level. Finally, we performed geospatial county-level analysis stratified by combined median SVI and CVD AAMR (high/high, high/low, low/high, and low/low). Results: We included data from 2766 counties (representing 95% of counties in the US) with median SVI 0.53 (IQR 0.28, 0.76). Overall SVI and the household and socioeconomic subcomponents were strongly correlated with 2018 CVD AAMR (0.47, 0.50, and 0.56, respectively with p<0.001 for all). CVD mortality declined between 1999-2011 and was stagnant between 2011-2018 with similar patterns in high and low SVI counties (FIGURE). Counties with high SVI and CVD AAMR were clustered in the South and Midwest (n=977, 35%). Conclusion: County-level social vulnerability is associated with higher CVD mortality. High SVI and CVD AAMR coexist in more than 1 in 3 US counties and have persisted over the past 2 decades. Identifying counties that are disproportionately vulnerable may inform targeted and community-based strategies to equitably improve cardiovascular health across the country.

scholarly journals Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February–June 2020, Massachusetts

2021 ◽  
pp. 003335492110367
Author(s):  
Scott Troppy ◽  
Grete E. Wilt ◽  
Ari Whiteman ◽  
Elaine Hallisey ◽  
Molly Crockett ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Social Vulnerability ◽  
Limited English Proficiency ◽  
Vulnerability Index ◽  
The United States ◽  
Social Vulnerability Index ◽  
Public Health Action ◽  
Infected People ◽  
Molecular Tests ◽  
Negative Results

Objectives Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. Methods We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran’s I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. Results Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. Conclusion Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

Abstract P133: Geospatial Mapping of Prehospital Delay in Acute Ischemic Stroke and Association With Social Vulnerability

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Amar Dhand ◽  
Amber Nieves ◽  
Molly Jarman ◽  
Regan Bergmark ◽  
Robert Semco ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Social Vulnerability ◽  
Arrival Time ◽  
Census Data ◽  
The United States ◽  
Household Composition ◽  
Social Vulnerability Index ◽  
Major Barrier ◽  
Prehospital Delay ◽  
Geospatial Mapping

Introduction: Prehospital delay, defined as the delay between symptom discovery and hospital arrival, remains a major barrier to timely acute stroke treatments. Delay is worse in socially vulnerable populations. A geospatial map of prehospital delay may identify high-risk areas and highlight the role of community social vulnerability in delay. We hypothesized that a community’s social vulnerability would be associated with delay. Methods: We analyzed national Get With The Guidelines ischemic stroke data between 2015 and 2017. We calculated the median arrival time (symptom discovery-to-door times) for each Zip Code Tabulation Area (ZCTA), and created geospatial map using ArcGIS. The primary exposure variable was the Center for Disease Control’s Social Vulnerability Index (SVI), and its 4 subcomponents. The SVI is a composite metric of community vulnerability using U.S. Census data (0, least vulnerable to 1, most vulnerable). To account for clustering within ZCTAs, we performed a multilevel linear regression of community-level SVI and patient-level prehospital delay. Results: During the study period, 149,774 patients had an ischemic stroke in 16,949 ZCTAs. Across patients, the median time of arrival was 140 mins, IQR was 60-459 mins, and range was 1-1439 mins. Arrival by 2h occurred in 46% of patients. Multilevel regression showed a strong positive association between the SVI and prehospital delay, evident in the maps (Figure). For every 10% increase in the SVI, the arrival time increased by 38 minutes [CI, 30 - 47] (p<0.001). Considering the 4 SVI subcomponents, delay was most strongly associated with socioeconomic status, household composition, and housing/transportation, but not minority status/language. Conclusion: Using geospatial mapping of prehospital delay across the United States, we show that community SVI is strongly associated with delayed ischemic stroke arrival. These maps help identify communities to target for stroke preparedness campaigns.

scholarly journals Assessment of Social Vulnerability to Floods in the Floodplain of Northern Italy

2017 ◽  
Vol 9 (4) ◽  
pp. 717-737 ◽  
Author(s):  
G. Roder ◽  
G. Sofia ◽  
Z. Wu ◽  
P. Tarolli
Keyword(s):  
Social Vulnerability ◽  
Flood Hazard ◽  
Vulnerability Index ◽  
Northern Italy ◽  
Vulnerable Groups ◽  
Management Approach ◽  
Elevated Concentration ◽  
Social Risk ◽  
Social Vulnerability Index ◽  
Spatial Detection

Abstract Practices for reducing the impacts of floods are becoming more and more advanced, centered on communities and reaching out to vulnerable populations. Vulnerable individuals are characterized by social and economic attributes and by societal dynamics rooted in each community. These indicators can magnify the negative impacts of disasters together with the capacity of each individual to cope with these events. The Social Vulnerability Index (SoVI) provides an empirical basis to compare social differences in various spatial scenarios and for specific environmental hazards. This research shows the application of the SoVI to the floodplain of northern Italy, based on the use of 15 census variables. The chosen study area is of particular interest for the high occurrence of flood events coupled with a high level of human activity, landscape transformations, and an elevated concentration of assets and people. The analysis identified a positive spatial autocorrelation across the floodplain that translates into the spatial detection of vulnerable groups, those that are likely to suffer the most from floods. In a second stage, the output of the index was superimposed on the flood hazard map of the study area to analyze the resulting risk. The Piemonte and Veneto regions contain the main areas prone to flood “social” risk, highlighting the need for a cohesive management approach at all levels to recognize local capacities and increase communication, awareness, and preparedness to mitigate the undesirable effects of such events.

scholarly journals Assessment of Social Vulnerability to Wildfire in Missouri, United States of America

2019 ◽  
Vol 12 (4) ◽  
pp. 76
Author(s):  
Omolola Victoria Akinola ◽  
Jimmy Adegoke ◽  
Temi Emmanuel Ologunorisa
Keyword(s):  
United States ◽  
Low Income ◽  
Social Vulnerability ◽  
Rating Scale ◽  
Biodiversity Loss ◽  
Vulnerability Index ◽  
The United States ◽  
Social Vulnerability Index ◽  
Wildfire Risk ◽  
Property Loss

Wildfire is a major environmental hazard causing property damage and destruction including biodiversity loss in the United States. In order to reduce property loss and destruction arising from wildfire, this study assessed and identified social vulnerability to wildfire in Missouri using the American Community Survey data on social and demographic variables for the state of Missouri and social vulnerability index (S0VI). The study divided Missouri into five geopolitical zones from which ten counties were randomly selected for this study. The selected counties formed the basis on which fourteen social and demographic indicators were identified and assessed using Bogardi, Birkmann and Cadona conceptual framework. The result of the analysis shows that S0VI estimated for the five geopolitical zones of Missouri is moderate with a rating scale of 1.42 &ndash; 1.71. Education, income and marital status have a rating scale of 2.0 - 3.0 attributed for the high value of Social Vulnerability to wildfire. Race / ethnicity, language spoken, employment and percentage of house units that are mobile homes had a low S0VI value of 1.0 thereby contributing positively to resilience to wildfire risk. The study observes that government involvement in wildfire risk reduction is quite impressive and should still be intensified. The policy implication of this study is that education and income are key variables that contribute to high wildfire risk in Missouri. The need for government to formulate a policy on environmental education of the populace especially for people of low income and education become imperative. This will go a long way in reducing damage and property loss arising from wildfire.

Social Vulnerability and Access of Local Medical Care During Hurricane Harvey: A Spatial Analysis

2021 ◽  
pp. 1-9
Author(s):  
David S. Rickless ◽  
Grete E. Wilt ◽  
J. Danielle Sharpe ◽  
Noelle Molinari ◽  
William Stephens ◽  
...  
Keyword(s):  
Medical Care ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Emergency Department Visits ◽  
Household Composition ◽  
Social Vulnerability Index ◽  
Socioeconomic Vulnerability ◽  
Control And Prevention ◽  
Impact Area ◽  
Education And Employment

Abstract Objectives: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW). This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. Methods: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. Results: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. Conclusions: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.

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