scholarly journals The role of the social vulnerability index in personal protective equipment shortages, number of cases, and associated mortality during the coronavirus disease 2019 (COVID-19) pandemic in Michigan skilled nursing facilities

2020 ◽  
pp. 1-4
Author(s):  
Jennifer J. LeRose ◽  
Courtney Merlo ◽  
Phong Duong ◽  
Kelsi Harden ◽  
Rebecca Rush ◽  
...  
Keyword(s):  
Personal Protective Equipment ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Mortality Rates ◽  
Skilled Nursing Facilities ◽  
Protective Equipment ◽  
Nursing Facilities ◽  
Social Vulnerability Index ◽  
Skilled Nursing ◽  
The Social

Abstract The Social Vulnerability Index (SVI) is used to stratify community need for support during disasters. We evaluated relationships between the SVI and personal protective equipment shortages, COVID-19 caseload, and mortality rates in skilled nursing facilities (SNFs). In SVI quartile 4, personal protective equipment shortages were 2.3 times those in SNFs in quartile 1; COVID-19 case loads were 1.6 times those of SNFs in quartile 1; and mortality rates in were 1.9 times those of SNFs in SVI quartile 1.

scholarly journals ASSESSMENT OF SOCIAL VULNERABILITY TO THE IMPACT OF FLOOD HAZARD: A CASE STUDY OF KOPILI RIVER BASIN, ASSAM, INDIA

2018 ◽  
Vol XLII-5 ◽  
pp. 455-460
Author(s):  
S. V. Shiva Prasad Sharma ◽  
P. S. Roy ◽  
V. Chakravarthi
Keyword(s):  
Social Vulnerability ◽  
Flood Hazard ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
The Social ◽  
Vulnerability Indicators ◽  
Multi Temporal ◽  
The Impact ◽  
Vulnerable Zones

<p><strong>Abstract.</strong> In the present study, an attempt is made to understand the impact on Social Vulnerability of the Kopili basin due to various severities of flood hazard. The flood hazard is generated using multi-temporal historical satellite based analysis and integration of annual flood inundation layers. The census of India data of 2001 and 2011 is spatially joined with village database to study the impact at village level. Using 5 Census variables from both Census 2001 &amp;amp; 2011 as vulnerability indicators, the Social Vulnerability Index (SVI) is derived and classified into various vulnerable zones namely Low, Moderate and High Vulnerable zones. The findings of the study show that the number of villages falling in Low and High Vulnerable zones had decreased during Census 2011 when compared to 2001 and a rise of 6% in villages falling in moderate vulnerable zones during 2011 is observed. The spatial database generated is useful to understand the impact of floods on the Social Vulnerability status of the basin and can be a useful input to further study the Physical, Economic and Environmental Vulnerabilities of the basin.</p>

scholarly journals The Social Vulnerability Index: Assessing Replicability in Predicting Mortality Over 27 Years

2019 ◽  
Vol 67 (6) ◽  
pp. 1305-1306 ◽  
Author(s):  
Camille Ouvrard ◽  
José Alberto Avila-Funes ◽  
Jean-François Dartigues ◽  
Hélène Amieva ◽  
Maturin Tabue-Teguo
Keyword(s):  
Social Vulnerability ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
The Social

scholarly journals Social Vulnerability in Patients with Multimorbidity: A Cross-Sectional Analysis

2019 ◽  
Vol 16 (7) ◽  
pp. 1244 ◽  
Author(s):  
Tu Nguyen ◽  
Patrice Ngangue ◽  
Tarek Bouhali ◽  
Bridget Ryan ◽  
Moira Stewart ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Social Vulnerability ◽  
Chronic Conditions ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Cross Sectional ◽  
Term Care ◽  
Cross Sectional Analysis ◽  
The Social ◽  
Sectional Analysis

Background: Social aspects play an important role in individual health and should be taken into consideration in the long-term care for people with multimorbidity. Purposes: To describe social vulnerability, to examine its correlation with the number of chronic conditions, and to investigate which chronic conditions were significantly associated with the most socially vulnerable state in patients with multimorbidity. Methods: Cross-sectional analysis from the baseline data of the Patient-Centred Innovations for Persons with Multimorbidity (PACEinMM) Study. Participants were patients attending primary healthcare settings in Quebec, Canada. A social vulnerability index was applied to identify social vulnerability level. The index value ranges from 0 to 1 (1 as the most vulnerable). Spearman’s rank correlation coefficient was calculated for the correlation between the social vulnerability index and the number of chronic conditions. Logistic regression was applied to investigate which chronic conditions were independently associated with the most socially vulnerable state. Results: There were 301 participants, mean age 61.0 ± 10.5, 53.2% female. The mean number of chronic health conditions was 5.01 ± 1.82, with the most common being hyperlipidemia (78.1%), hypertension (69.4%), and obesity (54.2%). The social vulnerability index had a median value of 0.13 (range 0.00–0.78). There was a positive correlation between the social vulnerability index and the number of chronic conditions (r = 0.24, p < 0.001). Obesity, depression/anxiety, and cardiovascular diseases were significantly associated with the most socially vulnerable patients with multimorbidity. Conclusions: There was a significant correlation between social vulnerability and the total number of chronic conditions, with depression/anxiety, obesity, and cardiovascular diseases being the most related to social vulnerability.

scholarly journals The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults

Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 24
Author(s):  
Natalia Sánchez-Garrido ◽  
Sara G. Aguilar-Navarro ◽  
José Alberto Ávila-Funes ◽  
Olga Theou ◽  
Melissa Andrew ◽  
...  
Keyword(s):  
Older Adults ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Adverse Outcomes ◽  
Social Vulnerability Index ◽  
Middle Aged ◽  
Logistic Regression Models ◽  
The Social ◽  
Aging Study ◽  
Different Populations

The social vulnerability index (SVI) independently predicts mortality and others adverse outcomes across different populations. There is no evidence that the SVI can predict adverse outcomes in individuals living in countries with high social vulnerability such as Latin America. The aim of this study was to analyze the association of the SVI with mortality and disability in Mexican middle-aged and older adults. This is a longitudinal study with a follow-up of 47 months, the Mexican Health and Aging Study, including people over the age of 40 years. A SVI was calculated using 42 items stratified in three categories low (<0.36), medium (0.36–0.47), and high (>0.47) vulnerability. We examined the association of SVI with three-year mortality and incident disability. Cox and logistic regression models were fitted to test these associations. We included 14,217 participants (58.4% women) with a mean age of 63.9 years (±SD 10.1). The mean SVI was of 0.42 (±SD 0.12). Mortality rate at three years was 6% (n = 809) and incident disability was 13.2% (n = 1367). SVI was independently associated with mortality, with a HR of 1.4 (95% CI 1.1–1.8, p < 0.001) for the highest category of the SVI compared to the lowest. Regarding disability, the OR was 1.3 (95% CI 1.1–1.5, p = 0.026) when comparing the highest and the lowest levels of the SVI. The SVI was independently associated with mortality and disability. Our findings support previous evidence on the SVI and builds on how this association persists even in those individuals with underlying contextual social vulnerability.

VULNERABILIDADE SOCIAL A INUNDAÇÕES DOS SETORES CENSITÁRIOS DO MUNICÍPIO DE PIRACURUCA (PI)

2019 ◽  
Vol 21 (2) ◽  
pp. 319-333
Author(s):  
Mayara Jordana De Castro Sousa ◽  
Francílio De Amorim Dos Santos
Keyword(s):  
Social Vulnerability ◽  
Vulnerability Index ◽  
Arithmetic Mean ◽  
Housing Conditions ◽  
Social Vulnerability Index ◽  
Simple Arithmetic ◽  
Census Tracts ◽  
The Social ◽  
Low Levels ◽  
Very High

O objetivo da pesquisa foi analisar a vulnerabilidade a inundação dos setores censitários no município de Piracuruca, norte do estado do Piauí. A metodologia apresentou natureza descritiva e empregou dados alfanuméricos relacionados aos setores censitários definidos pelo Instituto Brasileiro de Geografia e Estatística (IBGE). Desse modo, foram elencados 4 critérios para composição do Índice de Vulnerabilidade Social (IVS), a saber: Demografia; Educação; Renda; Condições habitacionais. Utilizou-se a média aritmética simples para cálculo do IVS, cujos valores dos dados foram convertidos para porcentuais e manuseados no SIG QGIS, versão 2.14, para efetivação da união entre a tabela do (arquivo vetorial e planilha eletrônica) e sua espacialização. Foram definidas 5 classes para o IVS, a saber: muito baixa (0,00 a 0,93), baixa (0,93 a 1,86), média (1,86 a 2,78), alta (2,78, a 3,71) e muito alta (3,71 a 4,64). Por meio do IVS afirma-se que os setores urbanos exibem maior vulnerabilidade a processos de inundações, pois dos 44 setores 25 deles estão situados na classe Média a Muito Alta. Logo, um maior adensamento populacional, baixos níveis de instrução e renda e condições inadequadas de habitação contribuem para exercer maior pressão sobre os recursos naturais e acentuar o processo de inundação.Palavras-chave: Desastre natural; Rio Piracuruca; Risco. ABSTRACTThe objective of the research was to analyze the vulnerability to flooding of the census tracts in the municipality of Piracuruca, in the northern part of the state of Piauí. The methodology was descriptive and used alphanumerical data related to the census tracts defined by the Instituto Brasileiro de Geografia e Estatística (IBGE). Thus, four criteria were included for the composition of the Social Vulnerability Index (SVI), namely: Demography; Education; Income; Housing conditions. We used the simple arithmetic mean to calculate the SVI, whose data values were converted to percentages and handled in the GIS QGIS, version 2.14, to effect the union between the table (vector file and spreadsheet) and its spatialization. Five classes were defined for IVS: very low (0.00 to 0.93), low (0.93 to 1.86), mean (1.86 to 2.78), high (2.78 to 3.71) and very high (3.71 to 4.64). Through the IVS, it is stated that the urban sectors are more vulnerable to flooding processes, because of the 44 sectors, 25 of them are located in the Medium to Very High class. Therefore, greater population density, low levels of education and income, and inadequate housing conditions contribute to putting more pressure on natural resources and accentuating the flooding process.Keywords: Natural disaster; Piracuruca River; Risk. RESUMENEl objetivo de la investigación fue analizar la vulnerabilidad a las inundaciones de las secciones censales en el municipio de Piracuruca, estado norteño de Piauí. La metodología fue descriptiva y empleó datos alfanuméricos relacionados con las secciones censales definidas por el Instituto Brasileño de Geografía y Estadística (IBGE). Por lo tanto, se enumeraron cuatro criterios para la composición del Índice de Vulnerabilidad Social (SIV), a saber: Demografía; Educación; Ingresos; Condiciones de vivienda. La media aritmética simple se utilizó para calcular el IVS, cuyos valores de datos se convirtieron en porcentajes y se manejaron en GIS QGIS, versión 2.14, para efectuar la unión entre la tabla (archivo vectorial y hoja de cálculo) y su espacialización. Se definieron cinco clases para IVS, a saber: muy baja (0.00 a 0.93), baja (0.93 a 1.86), media (1.86 a 2.78), alta (2.78 a 3.71) y muy alto (3.71 a 4.64). A través del IVS se afirma que los sectores urbanos son más vulnerables a los procesos de inundación, ya que de los 44 sectores, 25 de ellos están en la clase media a muy alta. Por lo tanto, mayores densidades de población, bajos niveles de educación e ingresos y condiciones inadecuadas de vivienda contribuyen a una mayor presión sobre los recursos naturales y acentúan el proceso de inundación.Keywords: Desastre Natural; Río Piracuruca; Riesgo.

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.

scholarly journals Response Time to Flood Events using a Social Vulnerability Index (ReTSVI)

2017 ◽  
Author(s):  
Alvaro Quezada-Hofflinger ◽  
Marcelo A. Somos-Valenzuela ◽  
Arturo Vallejos-Romero
Keyword(s):  
Response Time ◽  
Social Vulnerability ◽  
Vulnerability Index ◽  
Second Step ◽  
Demographic Information ◽  
Social Vulnerability Index ◽  
The Social ◽  
Hazard Zone ◽  
Severe Flood ◽  
Potential Case

Abstract. Current methods used to estimate people's evacuation times during a natural disaster assume that human responses across different social groups are similar. However, individuals respond differently based on their socioeconomic and demographic characteristics and previous knowledge. This article develops the Response Time by Social Vulnerability Index (ReTSVI), which is a methodology to estimate how human response time to evacuation warnings during a natural hazard is affected by considering characteristics related to both physical and social vulnerability. ReTSVI is a three-step methodology: first we calculate a population's evacuation curves considering social vulnerability level, certain demographic information and a model that describes an inundation hazard. Then, we use a mobilization model to generate evacuation maps per level of vulnerability and we also estimate the social vulnerability index for the area of study. In the third step, we combine the results from the second step to generate a map that indicates the percentage of people that could evacuate a hazard zone according to their social vulnerability level. Finally, we provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 minutes of the evacuation, the population that lives in neighborhoods with high social vulnerability evacuate 15 % and 22 % fewer people than the neighborhoods with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning and social vulnerability becomes less relevant after 30 minutes. Using a methodology such as ReTSVI allows first responders to identify areas where the same level of physical vulnerability affects distinct groups differently, providing them with a tool to quantify the differences in time to evacuate and where the resources before and during an evacuation should be preferentially allocated.

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