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 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 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 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.

scholarly journals Revising Ncei’s Climate Extremes Index And The Cdc’s Social Vulnerability Index To Analyze Climate Extremes Vulnerability Across The United States

2020 ◽  
pp. 1-42
Author(s):  
Emily L. Pauline ◽  
John A. Knox ◽  
Lynne Seymour ◽  
Andrew J. Grundstein
Keyword(s):  
United States ◽  
Social Vulnerability ◽  
Demographic Data ◽  
Climate Extremes ◽  
Vulnerability Index ◽  
The United States ◽  
Social Vulnerability Index ◽  
Social Demographic

CapsuleWhere are climate extremes happening? This information is urgently needed. We combine this information with social demographic data to create an index identifying U.S. locations vulnerable to climate extremes.

scholarly journals Social Vulnerability across the Great Lakes Basin: A County-Level Comparative and Spatial Analysis

2021 ◽  
Vol 13 (13) ◽  
pp. 7274
Author(s):  
Joshua T. Fergen ◽  
Ryan D. Bergstrom
Keyword(s):  
Great Lakes ◽  
Spatial Patterns ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Great Lakes Basin ◽  
Empirical Examination ◽  
Regional Patterns ◽  
Urban Rural ◽  
Social Vulnerabilities

Social vulnerability refers to how social positions affect the ability to access resources during a disaster or disturbance, but there is limited empirical examination of its spatial patterns in the Great Lakes Basin (GLB) region of North America. In this study, we map four themes of social vulnerability for the GLB by using the Center for Disease Control’s Social Vulnerability Index (CDC SVI) for every county in the basin and compare mean scores for each sub-basin to assess inter-basin differences. Additionally, we map LISA results to identify clusters of high and low social vulnerability along with the outliers across the region. Results show the spatial patterns depend on the social vulnerability theme selected, with some overlapping clusters of high vulnerability existing in Northern and Central Michigan, and clusters of low vulnerability in Eastern Wisconsin along with outliers across the basins. Differences in these patterns also indicate the existence of an urban–rural dimension to the variance in social vulnerabilities measured in this study. Understanding regional patterns of social vulnerability help identify the most vulnerable people, and this paper presents a framework for policymakers and researchers to address the unique social vulnerabilities across heterogeneous regions.

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 Effectiveness of mass treatment of Schistosoma mansoni infection in socially vulnerable areas of a state in northeastern Brazil, 2011–2014

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Flávia Silvestre Outtes Wanderley ◽  
Ulisses Montarroyos ◽  
Cristine Bonfim ◽  
Carolina Cunha-Correia
Keyword(s):  
Schistosoma Mansoni ◽  
Correspondence Analysis ◽  
Social Vulnerability ◽  
Multiple Correspondence Analysis ◽  
Vulnerability Index ◽  
Two Dimensions ◽  
Northeastern Brazil ◽  
Mass Treatment ◽  
Social Vulnerability Index ◽  
Treatment Information

Abstract Background To assess the effectiveness of mass treatment of Schistosoma mansoni infection in socially vulnerable endemic areas in northeastern Brazil. Method An ecological study was conducted, in which 118 localities in 30 municipalities in the state of Pernambuco were screened before 2011 and in 2014 (after mass treatment). Information on the endemic baseline index, mass treatment coverage, socio-environmental conditions and social vulnerability index were used in the multiple correspondence analysis. One hundred fourteen thousand nine hundred eighty-seven people in 118 locations were examined. Results The first two dimensions of the multiple correspondence analysis represented 55.3% of the variability between locations. The human capital component of the social vulnerability index showed an association with the baseline endemicity index. There was a significant reduction in positivity for schistosomes. For two rounds, for every extra 1% of initial endemicity index, the fixed effect of 13.62% increased by 0.0003%, achieving at most 15.94%. Conclusions The mass treatment intervention helped to reduce transmission of schistosomiasis in areas of high endemicity. Thus, it can be recommended that application of mass treatment should be accompanied by other control actions, such as basic sanitation, monitoring of intermediate vectors and case surveillance.

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