Social Vulnerability Index: Barbados – A Case Study

2020 ◽  
Vol 48 (5) ◽  
pp. 505-526
Author(s):  
Janice Cumberbatch ◽  
Crystal Drakes ◽  
Tara Mackey ◽  
Mohammad Nagdee ◽  
Jehroum Wood ◽  
...  
Keyword(s):  
Social Vulnerability ◽  
Vulnerability Index ◽  
Social Vulnerability Index

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 QUANTITATIVE ASSESSMENT OF SOCIAL VULNERABILITY FOR LANDSLIDE DISASTER RISK REDUCTION USING GIS APPROACH (CASE STUDY: CILACAP REGENCY, PROVINCE OF CENTRAL JAVA, INDONESIA)

2018 ◽  
Vol XLII-4 ◽  
pp. 703-709
Author(s):  
A. P. Wijaya ◽  
J.-H. Hong
Keyword(s):  
Social Vulnerability ◽  
Vulnerability Index ◽  
Spatial Diversity ◽  
Disaster Risk ◽  
Social Vulnerability Index ◽  
Internal Factors ◽  
Central Java ◽  
National Disaster ◽  
Quantitative Assessments

<p><strong>Abstract.</strong> Social vulnerability is an important aspect in determining the level of disaster risk in a region. Social vulnerability index (SoVI) is influenced by several supporting factors, such as age, gender, health, education, etc. When different sets of parameters are considered, the SoVI analyzed results are likely to be also different from one to another. In this paper, we will discuss the quantitative assessments of SoVI based on two different models. The first model, proposed by Frigerio et al. (2016), is used to analyze the spatial diversity of social vulnerability due to seismic hazards in Italy. The second model is based on the regulations of the head of the National Disaster Management Agency (BNPB) No. 2 of 2012. GIS is used to present and compare the results of the two selected models. In additive impact factor on the SoVI is also done. The result is that there are regions that belong to the same class on both models such as Pemalang, there are regions that enter in different classes on both models such as Cilacap. The result also shows the model of Frigerio et al. (2016) is more representative than the BNPB model (2012) by additionally considering the education and unemployment factors in determining the SoVI, while the BNPB model (2012) only includes internal factors such as age, gender. By considering education and unemployment factors, we get more detailed conditions about society from social vulnerability.</p>

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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