scholarly journals Cumulative Environmental Vulnerability Assessment in the Area of Influence of the Pecém Port Industrial Complex (Ceará, Brazil): A Spatial Analysis

2021 ◽  
Vol 18 (5) ◽  
pp. 2404
Author(s):  
Norberto Santos-Junior ◽  
Jose Ueleres Braga ◽  
Elvira Maria Godinho de Seixas Maciel
Keyword(s):  
Vulnerability Assessment ◽  
Risk Index ◽  
Vulnerability Index ◽  
Metropolitan Region ◽  
Industrial Complex ◽  
Health Index ◽  
Social Vulnerability Index ◽  
Environmental Vulnerability ◽  
Choropleth Maps ◽  
Area Of Influence

The municipalities of Caucaia and São Gonçalo do Amarante are located in the metropolitan region of Fortaleza (CE) and are home to the Pecém Port Industrial Complex (PPIC). We know that economic development is not necessarily related to improvements in the quality of life of the population. Furthermore, the bonuses and burdens of this particular installation can occur unevenly. This study aimed to assess the cumulative environmental vulnerability of these municipalities. We used the cumulative environmental vulnerability assessment methodology to assess the population’s degree of vulnerability, considering census sectors as a spatial unit. This approach combines three indices: environmental risk index, social vulnerability index, and health index. Finally, we calculated the arithmetic mean of each indicator in each census sector. We built choropleth maps to assess the spatial distribution of environmental vulnerability. We found that many maps demonstrated high cumulative environmental vulnerability census sectors around the PPIC, while the Caucaia, located downtown, exhibited a substantial majority of the low cumulative environmental vulnerability census sectors. The district of Guararu, in Caucaia, was notable for having proportionally more census sectors with high health index values. Environmental vulnerability was heterogeneously distributed, and the most impoverished areas are also the most vulnerable.

scholarly journals The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts

2021 ◽  
Vol 8 ◽  
Author(s):  
Erin N. Biggs ◽  
Patrick M. Maloney ◽  
Ariane L. Rung ◽  
Edward S. Peters ◽  
William T. Robinson
Keyword(s):  
Population Density ◽  
Social Vulnerability ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Census Tracts ◽  
Control And Prevention ◽  
Choropleth Maps ◽  
The Relationship

Objective: To examine the association between the Centers for Disease Control and Prevention (CDC)'s Social Vulnerability Index (SVI) and COVID-19 incidence among Louisiana census tracts.Methods: An ecological study comparing the CDC SVI and census tract-level COVID-19 case counts was conducted. Choropleth maps were used to identify census tracts with high levels of both social vulnerability and COVID-19 incidence. Negative binomial regression with random intercepts was used to compare the relationship between overall CDC SVI percentile and its four sub-themes and COVID-19 incidence, adjusting for population density.Results: In a crude stratified analysis, all four CDC SVI sub-themes were significantly associated with COVID-19 incidence. Census tracts with higher levels of social vulnerability were associated with higher COVID-19 incidence after adjusting for population density (adjusted RR: 1.52, 95% CI: 1.41-1.65).Conclusions: The results of this study indicate that increased social vulnerability is linked with COVID-19 incidence. Additional resources should be allocated to areas of increased social disadvantage to reduce the incidence of COVID-19 in vulnerable populations.

scholarly journals Social Vulnerability Assessment for Flood Risk Analysis

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 558 ◽  
Author(s):  
Laura Tascón-González ◽  
Montserrat Ferrer-Julià ◽  
Maurici Ruiz ◽  
Eduardo García-Meléndez
Keyword(s):  
Vulnerability Assessment ◽  
Flood Risk ◽  
Social Vulnerability ◽  
Large Scale ◽  
Vulnerability Index ◽  
Social Vulnerability Index ◽  
Coping Capacity ◽  
High Exposure ◽  
Public Data ◽  
Social Vulnerability Assessment

This paper proposes a methodology for the analysis of social vulnerability to floods based on the integration and weighting of a range of exposure and resistance (coping capacity) indicators. It focuses on the selection and characteristics of each proposed indicator and the integration procedure based on the analytic hierarchy process (AHP) on a large scale. The majority of data used for the calculation of the indicators comes from open public data sources, which allows the replicability of the method in any area where the same data are available. To demonstrate the feasibility of the method, a study case is presented. The flood social vulnerability assessment focuses on the municipality of Ponferrada (Spain), a medium-sized town that has high exposure to floods due to potential breakage of the dam located upstream. A detailed mapping of the social vulnerability index is generated at the urban parcel scale, which shows an affected population of 34,941 inhabitants. The capability of working with such detailed units of analysis for an entire medium-sized town provides a valuable tool to support flood risk planning and management.

scholarly journals Urban Vulnerability Assessment for Pandemic Surveillance—The COVID-19 Case in Bogotá, Colombia

2021 ◽  
Vol 13 (6) ◽  
pp. 3402
Author(s):  
Jeisson Prieto ◽  
Rafael Malagón ◽  
Jonatan Gomez ◽  
Elizabeth León
Keyword(s):  
Vulnerability Assessment ◽  
Disease Transmission ◽  
Urban Areas ◽  
A Priori ◽  
Vulnerability Index ◽  
Past Century ◽  
Vulnerability Factors ◽  
Early Assessment ◽  
Global Citizens ◽  
Urban Vulnerability

A pandemic devastates the lives of global citizens and causes significant economic, social, and political disruption. Evidence suggests that the likelihood of pandemics has increased over the past century because of increased global travel and integration, urbanization, and changes in land use with a profound affectation of society–nature metabolism. Further, evidence concerning the urban character of the pandemic has underlined the role of cities in disease transmission. An early assessment of the severity of infection and transmissibility can help quantify the pandemic potential and prioritize surveillance to control highly vulnerable urban areas in pandemics. In this paper, an Urban Vulnerability Assessment (UVA) methodology is proposed. UVA investigates various vulnerability factors related to pandemics to assess the vulnerability in urban areas. A vulnerability index is constructed by the aggregation of multiple vulnerability factors computed on each urban area (i.e., urban density, poverty index, informal labor, transmission routes). This methodology is useful in a-priori evaluation and development of policies and programs aimed at reducing disaster risk (DRR) at different scales (i.e., addressing urban vulnerability at national, regional, and provincial scales), under diverse scenarios of resources scarcity (i.e., short and long-term actions), and for different audiences (i.e., the general public, policy-makers, international organizations). The applicability of UVA is shown by the identification of high vulnerable areas based on publicly available data where surveillance should be prioritized in the COVID-19 pandemic in Bogotá, Colombia.

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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