Social Vulnerability Assessment Research Articles

Spatial Industrial Accident Exposure and Social Vulnerability Assessment of Hazardous Material Sites, Chemical Parks, and Nuclear Power Plants in Germany

Industrial accidents have shown that many people can be affected, such as in Seveso, Italy, in 1976. Industrial accidents in nuclear power plants have also led to fatalities and evacuations. To better guide preparedness against and mitigation of industrial accidents, an assessment is necessary to evaluate hazard exposure and the type of potentially vulnerable social groups that need to be taken into account. This study conducted a spatial assessment of three types of industrial facilities in Germany: facilities registered under the Seveso Directive, chemical parks, and nuclear power plants. The method consisted of a spatial assessment using a Geographic Information System of exposure around hazardous sites registered under the Seveso Directive in Germany and of census data to analyze social vulnerability. Hazards analyzed included industrial accidents and earthquakes. The results revealed that most industrial sites are in urban areas and that population density, the numbers of foreigners, and smaller housing unit sizes are higher in close proximity to these sites. The buffer zones analyzed in circles between 1 and 40 km show a decreasing vulnerability with more distance. This can guide emergency management planners and other stakeholders to better prepare for major accidents and better devise disaster risk reduction strategies specifically for different social groups.

Landslide susceptibility and risk analysis in Benighat Rural Municipality, Dhading, Nepal

The complex geology and undulating terrain made Nepal vulnerable to natural disasters like landslides. Benighat-Rorang Rural Municipality (RM), in the Dhading district of Nepal's Bagmati province, has experienced several minor to massive landslides that have harmed both nature and civilization. This study examines the factors influencing landslides in the Benighat-Rorang RM by analyzing soil structure, geology, land cover, geomorphology (primarily slopes and aspects), fault lines, drainage density, weather data, and road density to generate a comprehensive Landslide Susceptibility Mapping (LSM). The LSM will help in identifying landslide-prone zones (high to low), which will, in turn, enable stakeholders to implement appropriate mitigation measures across the landslide-induced rural municipality. The current study intends to create Landslide susceptibility zonation mapping within and around the studied area by applying the AHP method while taking into account the optimal set of geo-environmental parameters to identify regions at risk of future landslides. Elevation, Slope, Aspect, Drainage, Geology, Soil Classes, Fault Line, Lineaments, Land-cover, Road Networks, Population, and climatic parameters (Rainfall, Temperature, Relative Humidity, Surface Pressure, and Wind Speed) are among the fourteen geo-environmental elements used for this research. Using the field verification approach, the results of this procedure have been validated, which can be observed in an estimated success rate curve. Meteorological factors, such as temperature, rainfall, relative humidity, surface pressure, and wind speed, have been examined regarding landslide susceptibility. Thus, an integrated assessment of landslide susceptibility was applied to the area to identify inhabited areas vulnerable to or at risk of landslides. Furthermore, the placement of public amenities throughout the research zone was considered while conducting the social vulnerability risk analysis. Finally, landslide susceptibility zonation, climatic factors influencing landslide susceptibility, and social vulnerability assessment results of the study area have been combined to generate a risk map identifying landslide-prone municipal facilities and vulnerable communities. This study will help in building resilient landslide communities through effective spatial urban planning that incorporates regional risks induced by landslides with infrastructure development and management strategies.

Assessment of Social Vulnerability in Pediatric Head and Neck Cancer Care and Prognosis in the United States

Prior investigations in social determinants of health (SDoH) in pediatric head and neck cancer (HNC) have only considered a narrow scope of HNCs, SDoH, and geography while lacking inquiry into the interrelational association of SDoH with disparities in clinical pediatric HNC. To evaluate the association of SDoH with disparities in HNC among children and adolescents and to assess which specific aspects of SDoH are most associated with disparities in dynamic and regional sociodemographic contexts. This retrospective cohort study included data about patients (aged ≤19 years) with pediatric HNC who were diagnosed from 1975 to 2017 from the Surveillance, Epidemiology, and End Results Program (SEER) database. Data were analyzed from October 2021 to October 2022. Overall social vulnerability and its subcomponent contributions from 15 SDoH variables, grouped into socioeconomic status (SES; poverty, unemployment, income level, and high school diploma status), minority and language status (ML; minoritized racial and ethnic group and proficiency with English), household composition (HH; household members aged ≥65 and ≤17 years, disability status, single-parent status), and housing and transportation (HT; multiunit structure, mobile homes, crowding, no vehicle, group quarters). These were ranked and scored across all US counties. Regression trends were performed in continuous measures of surveillance and survival period and in discrete measures of advanced staging and surgery receipt. A total of 37 043 patients (20 729 [55.9%] aged 10-19 years; 18 603 [50.2%] male patients; 22 430 [60.6%] White patients) with 30 different HNCs in SEER had significant relative decreases in the surveillance period, ranging from 23.9% for malignant melanomas (mean [SD] duration, lowest vs highest vulnerability: 170 [128] months to 129 [88] months) to 41.9% for non-Hodgkin lymphomas (mean [SD] duration, lowest vs highest vulnerability: 216 [142] months vs 127 [94] months). SES followed by ML and HT vulnerabilities were associated with these overall trends per relative-difference magnitudes (eg, SES for ependymomas and choroid plexus tumors: mean [SD] duration, lowest vs highest vulnerability: 114 [113] months vs 86 [84] months; P < .001). Differences in mean survival time were observed with increasing social vulnerability, ranging from 11.3% for ependymomas and choroid plexus tumors (mean [SD] survival, lowest vs highest vulnerability: 46 [46] months to 41 [48] months; P = .43) to 61.4% for gliomas not otherwise specified (NOS) (mean [SD] survival, lowest vs highest vulnerability: 44 [84] months to 17 [28] months; P < .001), with ML vulnerability followed by SES, HH, and HT being significantly associated with decreased survival (eg, ML for gliomas NOS: mean [SD] survival, lowest vs highest vulnerability: 42 [84] months vs 19 [35] months; P < .001). Increased odds of advanced staging with non-Hodgkin lymphoma (OR, 1.21; 95% CI, 1.02-1.45) and retinoblastomas (OR, 1.31; 95% CI, 1.14-1.50) and decreased odds of surgery receipt for melanomas (OR, 0.79; 95% CI, 0.69-0.91) and rhabdomyosarcomas (OR, 0.90; 95% CI, 0.83-0.98) were associated with increasing overall social vulnerability. In this cohort study of patients with pediatric HNC, significant decreases in receipt of care and survival time were observed with increasing SDoH vulnerability.

An Integrated PCA–AHP Method to Assess Urban Social Vulnerability to Sea Level Rise Risks in Tampa, Florida

Coastal flooding risks are increasing with the rise of sea level due to global climate change. Such risk presents different groups of residents with diverse vulnerability. Using a coastal city as the study area, this study quantitatively and qualitatively examines social vulnerability across different communities at risk of sea level rising. This study develops a novel social vulnerability assessment method that integrates principal component analysis (PCA) and analytical hierarchical process (AHP), inputting the advantages of each into factor analysis for social vulnerability quantification. Twenty-four socioeconomic factors are first grouped into four different themes. PCA is then performed to identify major components within each theme. We apply AHP to generate the weighting scheme for each theme. Therefore, the AHP-derived weights to those PCA components according to each theme are used to obtain an overall social vulnerability index. The thematic map of PCA–AHP SVI showed that minority communities with low income, mobile home, and unemployed populations aggregated in the East Tampa shore (over 69% of the total minority), compared with the West Tampa (31% of the total minority). Our findings provide insightful spatial information of the social vulnerability index (SVI) that allows decision makers to make optimal efforts to mitigate damages and unexpected impacts on different communities, especially those marginalized minorities due to sea level rising risks.

Assessment of social vulnerability to forest fire and hazardous facilities in Germany

In recent years, Germany has seen an increase in forest fires, and many fires have occurred in military training areas that are difficult to access for firefighting. While casualties are still low and mostly restricted to firefighting personnel, settlements are also increasingly threatened. Increasing impacts from extreme events due to climate change will likely increase the ignition and spread of fires. More people are being affected by fires, and in need of external help to evacuate and cope with the resulting damages and losses. Forest fires also threaten military training site, with additional risks created by the presence of ammunition depots.Despite this hazard scenario, Germany so far lacks an overview of the spatial occurrence of forest fires and the related risk. This study develops a spatial exposure and social vulnerability assessment of settlements to forest fires in Germany. The results reveal that social vulnerability is an important variable in determining which settlements are potentially exposed to fire. Areas exposed to fire risk are characterised by having a higher proportion of women, a higher-than-average age, a higher number of young people under 18 years, a higher number of persons over 65 years and foreigners than the national average. Furthermore, exposed communities are characterised by higher rates of unoccupied housing units and lower living space per dwelling, as well as living in areas with high population densities within forested areas. The results can help to improve emergency management and spatial planning to prevent the development of fire risk areas.

Evaluation of Frailty Measures and Short-term Outcomes After Lung Transplantation

Frailty, measured as a single construct, is associated variably with poor outcomes before and after lung transplantation. The usefulness of a comprehensive frailty assessment before transplantation is unknown. How are multiple frailty constructs, including phenotypic and cumulative deficit models, muscle mass, exercise tolerance, and social vulnerabilities, measured before transplantation, associated with short-term outcomes after lung transplantation? We conducted a retrospective cohort study of 515 lung recipients who underwent frailty assessments before transplantation, including the short physical performance battery (SPPB), transplant-specific frailty index (FI), 6-min walk distance (6MWD), thoracic sarcopenia, and social vulnerability indexes. We tested the association between frailty measures before transplantation and outcomes after transplantation using logistic regression to model 1-year survival and zero-inflated negative binomial regression to model hospital-free days (HFDs) in the first 90days after transplantation. Adjustment covariates included age, sex, native lung disease, transplantation type, lung allocation score, BMI, and primary graft dysfunction. Before transplantation, 51.3%of patients were frail by FI (FI≥ 0.25) and no patients were frail by SPPB. In multivariate adjusted models that also included FI, SPPB, and 6MWD, greater frailty by FI, but not SPPB, was associated with fewer HFDs (-0.006 per 0.01 unit worsening; 95%CI, -0.01 to -0.002 per 0.01 unit worsening) among discharged patients. Greater SPPB deficits were associated with decreased odds of 1-year survival (OR, 0.51 per 1 unit worsening; 95%CI, 0.28-0.93 per 1 unit worsening). Correlation among frailty measurements overall was poor. No association was found between thoracic sarcopenia, 6MWD, or social vulnerability assessments and short-term outcomes after lung transplantation. Both phenotypic and cumulative deficit models measured before transplantation are associated with short-term outcomes after lung transplantation. Cumulative deficit measures of frailty may be more relevant in the first 90days after transplantation, whereas phenotypic frailty may have a stronger association with 1-year survival.

GIS based urban social vulnerability assessment for liquefaction susceptible areas: a case study for greater Chennai, India

BackgroundThe areas prone to geological hazards such as liquefaction need special attention with respect to social vulnerability. Though liquefaction by itself may not result in damage, it may trigger a series of ground failures such as ground oscillation, lateral spread, loss of bearing strength, etc., which cause heavy damage. Globally, during the past few decades liquefaction hazard analysis has become one of the important criteria in seismic risk analysis and mitigation management, especially for urban areas. Greater Chennai is one of the million-plus population cities in India. The city also felt earthquakes/tremors in the past history.MethodThe present study aims to assess the social vulnerability of the population density of the Greater Chennai area due to liquefaction susceptibility using GIS technology. The liquefaction susceptibility map (hazard) for the Greater Chennai was prepared by integration of geological and geomorphological parameters and analyzed over socioeconomic parameters (exposure) using an integration of GIS and AHP.ResultsThe result showed that around 53% of Greater Chennai’s households and population are very much exposed to liquefaction hazard.ConclusionsThis study can be used as a base level study for decision-making during land use planning as well as disaster mitigation planning.

Assessment of Social Vulnerability of Older Adults in Zahedan to Natural Disasters in 2023

Assessment of Social Vulnerability of Older Adults in Zahedan to Natural Disasters in 2023

Social vulnerability analysis at municipal level: Case study of the province of Chlef, Algeria

This paper explores the empirical assessment of social vulnerability in the Algerian context using the Social Vulnerability Index (SoVI). The SoVI is applied at the municipal level in the province of Chlef. The assessment aims to map the geographical variability of social vulnerability for the 35 municipalities of the study area. While following the original SoVI methodology, some adjustments were made to the variables to adapt them to the context. Principal Component Analysis (PCA) was performed on a set of 40 selected variables resulting in six vulnerability factors. After as-signing a sign (negative, positive, or absolute) to each factor, they were summed to calculate the overall SoVI score. The resulting maps highlight the most vulnerable municipalities in the province, and their interpretation was aided by geographical maps depicting the natural and human characteristics of the territory.

Multicriteria seismic hazard and social vulnerability assessment in the Puerto Vallarta metropolitan area, Mexico: toward a comprehensive seismic risk analysis

Multicriteria seismic hazard and social vulnerability assessment in the Puerto Vallarta metropolitan area, Mexico: toward a comprehensive seismic risk analysis

Seismic risk assessment for the North Eastern Region of India by integrating seismic hazard and social vulnerability

ABSTRACT The present study aims at conducting a comprehensive seismic risk assessment for the North Eastern Region of India at regional and sub-regional levels by integrating probabilistic seismic hazard and social vulnerability assessments. Bedrock-level peak ground acceleration varied from 0.14 to 0.69g for the return period of 475 years. Using PCA, the social vulnerability index (SVI) was generated considering district-level socioeconomic indicators. Built environment quality, illiteracy, access to amenities, dependent population, and employment opportunities contributed tohigh SVI. Most vulnerable districts were concentrated in the Brahmaputrafloodplains, Tripura fold belt, and Imphal valley. At the regional level,significant parts of Assam, Meghalaya, Arunachal Pradesh, and Tripura lie inmoderate to very high-risk zones. At the sub-regional level, Nagaland accountsfor the highest proportion of areas in high to very high-risk zones. The findings will aid site-specific resilient infrastructure design, disaster risk reduction, and effective resource allocation for the risk-prone areas.

A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

Social vulnerability, as one of the risk components, partially explains the magnitude of the impacts observed after a disaster. In this study, a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal, at the civil parish level, for three census frames. The first challenging step consisted of the selection of meaningful and consistent variables over time. Data were normalized using the Adjusted Mazziotta-Pareto Index (AMPI) to obtain comparable adimensional-normalized values. A joint principal component analysis (PCA) was applied, resulting in a robust set of variables, interpretable from the point of view of their self-grouping around vulnerability drivers. A separate PCA for each census was also conducted, which proved to be useful in analyzing changes in the composition and type of drivers, although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011. A general improvement in social vulnerability was observed for Portugal. The two main drivers are the economic condition (PC1), and aging and depopulation (PC2). The remaining drivers highlighted are uprooting and internal mobility, and daily commuting. Census data proved their value in the territorial, social, and demographic characterization of the country, to support medium- and long-term disaster risk reduction measures.

Social vulnerability assessment to flood hazard in Souss basin, Morocco

The concept of vulnerability is now embedded into multiple disaster-related disciplinary theories and is currently incorporated in various ways concerning disaster risk management. The Souss basin has witnessed many intensive extreme flooding events during the last two decades because it is located in a semi-arid to arid climate. The area is quite vulnerable, and negative impacts have gotten increasingly alarming. The susceptibility to this risk is accentuated not only by the shorter intense rainfall but also by the rapid population growth, uncontrolled land use, anthropogenic actions, and recent environmental fluctuations. These factors affect both the potential hazards and general vulnerability. In this study and given the current context, we developed a methodology to assess social vulnerability towards flooding in the area based on 26 socioeconomic indicators from the database of the Last general census of population and housing (GPHC) in 2014. These indicators aim to describe the spatial variability of the Social Vulnerability Index (SoVI) using principal component analysis (CPA) and GIS. Thus, the SoVI, with values ranging from 0 to 4, is a powerful tool for better quantifying social vulnerability and highlighting the potential impact on urban and rural communities. The result shows that few urban areas have a low average vulnerability index (1.76–2.33) while most rural areas have a higher average of SoVI ranging from 3.56 to 4 in this area. Therefore, it will serve as a basis for evacuation plans to anticipate and prevent flooding risks. This statement indicates that social-economic indicators enhancement is advisable in this area.

Imagining and assessing future risks: A dynamic scenario‐based social vulnerability analysis framework for disaster planning and response

AbstractWhile social vulnerability assessments should play a crucial part in disaster management, there is a lack of assessment tools that retain sensitivity to the situation‐specific dynamics of vulnerabilities emerging in particular hazard scenarios. We developed a novel scenario‐based vulnerability assessment framework together with practitioners in crisis management and assessed the suitability of its components in three past crises and their scenario‐based derivations: a large‐scale power outage, the COVID‐19 pandemic, and a cyber‐attack. Rather than deterministically concluding about vulnerability based on prefixed factors, the framework guides relevant stakeholders to systematically think through categories of vulnerability pertinent to a scenario. We used a table‐top exercise, interviews, and focus groups to demonstrate how the framework broadens the crisis managers’ understanding of the scope of factors that may cause vulnerability, the related sources of information and enables to identify individuals burdened by certain vulnerability mixes. The new framework could be applied to different types of crises to enhance preparedness, demand‐driven relief and rescue during critical events.

Coastal vulnerability modelling and social vulnerability assessment under anthropogenic impacts

Coastal regions are highly vulnerable to the impacts of human activities, land cover change, sea level rise (SLR), and climate extremes. In this study, we attempt to address this issue by simulating the spatial interactions among natural hazards, ever-increasing human activities, and social vulnerability in the south coast of the Bohai Sea, China. It is found that the activities occurring on land, especially within coastal environments, such as agricultural pond and ports, and those in the ocean (tide and residual current) both impose disaster risks on the marine environment. In 2020, 25.2% of the total study area is highly vulnerable, which is 21% larger than that in 1997. The socially vulnerable areas are mainly distributed in the southeast coast of the Laizhou Bay. These areas should be strengthened to reduce and prevent the storm surge and flood disasters. Ultimately, we emphasize the urgent needs to implement effective policy measures for reducing tomorrow’s risks from natural hazards.

Landslide susceptibility, social vulnerability, and risk assessment in Kumaun Himalaya, Uttarakhand, India

Landslide susceptibility, social vulnerability, and risk assessment in Kumaun Himalaya, Uttarakhand, India

Social vulnerability assessment of landslide disaster based on improved TOPSIS method: Case study of eleven small towns in China

• Constructing evaluation index system of social vulnerability of small towns in China. • Exploring the spatial differences of social vulnerability landslide disaster areas. • Risk perception and social structure are the two key factors of social vulnerability in landslide disaster areas. • It provides a case and method reference for structural and non-structural disaster prevention & mitigation.a. There are few studies on the social vulnerability of small towns in landslide disaster areas. The occurrence of geological disasters will directly threaten the local socioeconomic growth, it is particularly important to identify vulnerable areas and populations by using the social vulnerability index system. Eleven small towns of landslide areas after Wenchuan earthquake were taken as examples, based on 863 questionnaires and statistical data, this study established a new comprehensive evaluation index system of social vulnerability evaluation in landslide areas, and conducted quantitative evaluation by using the improved TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) model, the social vulnerability index was adopted to compare, classify and rank the social vulnerability levels in townships. The empirical results indicate that the social vulnerability showed the characteristics of regional heterogeneity, most towns showed a high or medium level of social vulnerability. Only Yingxiu showed a low level of social vulnerability, Shuimo presented the highest evaluation score of social vulnerability in eleven towns, the inter-group difference between these two towns is 0.286. Risk perception is an important factor affecting social vulnerability in landslide areas, involving disaster awareness, disaster cognitive approach, and community publicity. Additionally, social structure is another key factor affecting these areas based on the scores of the top three areas with the highest social vulnerability, including disaster prevention facilities, residents' income, and infrastructure accessibility. The index system can evaluate the social vulnerability scientifically in landslide areas, it can be used for urban disaster management and socioeconomic development in geological disaster areas.

Assessment of social vulnerability to groundwater pollution using K-means cluster analysis.

It is possible to assess the harm that society suffers as a consequence of groundwater contamination in aquifers. Indexing methodologies are commonly applied to assess the social vulnerability to polluted aquifers. However, they assign weighting and rating values to the different factors involved, which makes them very subjective. This research aims to assess the social vulnerability to groundwater pollution taking into account three factors: the uses of groundwater resources, the exposed population, and the socio-economic losses. In order to eliminate the subjectivity of current indexing methodologies, this work uses a K-means cluster analysis for the assessment of social vulnerability. With this method, a social vulnerability map can be produced with greater objectivity. The proposed methodology is applied to an aquifer located in central Spain, an area with significant agricultural development. Low population density and unproductive zones result in low social vulnerability in most of the area. However, high social vulnerability is observed in the southern sector due to agricultural development, which leads to higher socio-economic variables and demand for groundwater resources. Similarly, high social vulnerability is observed in the northeast, mainly influenced by the groundwater use and the exposed population. These results show that social vulnerability in most of the study area is not very significant for assessing the risk of groundwater contamination, because the damage to the social, environmental, or economic sector is low. However, in the south and northeast of the study area, pesticides and fertilizers should be used with caution, as they significantly increase the risk of groundwater contamination. The K-means clustering method proved to be an objective and reliable option for assessing social vulnerability to groundwater pollution in aquifers.

Urban community perception on social vulnerability to disaster: the case of Bukit Antarabangsa, Malaysia

This article aims to determine the perception of urban communities living in Bukit Antarabangsa regarding the issue of social vulnerability (SV) to landslide and landslide-related disasters. Bukit Antarabangsa is widely known as one of the highly urbanized areas near the metropolitan of Kuala Lumpur which are highly susceptible to landslides. Few communities which currently under the SeDAR project (i.e., a join-community-based disaster risk reduction/CBDRR program between Selangor State Disaster Management Centre – JICA – Local NGO: SlopeWatch Bukit Antarabangsa) were selected as a case study. Focus Group Discussion (FGD) and household surveys were conducted during Conditional Movement Order (CMCO) on March 27th 2021 and April 11th 2021 to gather relevant information on the researched topic. The questionnaire for the survey was formulated based on the proposed detailed list of SV components, indicators, sub-indicators and weightage which was derived from a review of the literature and internal consultation among disaster experts. The data analysis process in this study served to achieve the objective of social and economic vulnerability assessment in general based on the usage of sub-indicators to point out the score value and level of performance of each sub-indicator based on the survey of local stakeholders. Results from data analysis were translated into spatial context through the production of an SV map of the study area. In summary, the integrated approach to the assessment of SV involving data analysis and mapping/spatial representation has offered some valuable insights towards strengthening local community resilient to disaster and should be considered for inclusion into the establishment of a long-term community-based disaster risk reduction (CBDRR) planning and assessment, and in formulating DRR strategies at local and/or municipal context.

Assessment of social vulnerability of landslides in the Darjeeling district using MCDA-based GIS techniques

The consequences or the result of any disaster or hazard's impact on society or nature is considered a vulnerability. In terms of landslide hazards, it causes many losses to the community such as the death of people, damage to property and damage to nature. Social vulnerability is measured with different scales depending on the area of the occurrence. In this study, a social vulnerability was conducted to identify the socially vulnerable zones such as people and property. The study was conducted in the Darjeeling district, West Bengal (26027” N to 27013” N latitudes and 87059” E to 88053” E longitudes). The main objective of this study is to find out the area under vulnerable zones. With the help of the GIS platform and Data available from the DDMA handbook and Census 2011, the social vulnerable map was created. In this study, Analytic Hierarchy Process (AHP)17 was applied to determine the weighted values of each factor i.e. Population Distribution, Literacy Rate, Non-working population etc. All the parameters were put into Arc GIS based on each parameter’s weighted values and the final output of social vulnerability was prepared. The result showed that 26% area comes under high vulnerable zones and 4% are in very high vulnerable zones. The southern part of the district comes under high to very high vulnerable zones due to the high population density and high settlement density.