Socioeconomic Vulnerability Index Research Articles

Is the coastal vulnerability index a suitable index? Review and proposal of alternative indices for coastal vulnerability to sea level rise

The Coastal Vulnerability Index (CVI) has been widely applied around the world. This study provides a review of the suitability of the variables and mathematical expression of the CVI and proposes a new Integrated Coastal Vulnerability Index (ICVI), comparing both indices for 4 study areas in the southern Caribbean. The ICVI assesses vulnerability to sea level rise by integrating the Environmental Vulnerability Index (EVI) and the Socioeconomic Vulnerability Index (SVI). Regarding the variables that constitute the indices, it is noted that the CVI includes vulnerability and hazard variables and therefore it should be considered a risk index rather than a vulnerability index. The EVI includes geomorphological vulnerability variables, like the CVI, but also ecological ones. Regarding the mathematical expression, the use of the arithmetic mean versus the formula proposed for the CVI is discussed based on the comparison of the results obtained for EVI and SVI in the 4 study areas. In addition, the use of absolute (between 0 and 1) or relative (based on percentiles) limits in these indices, and the use of weights or not, are also discussed. The conclusion is that the use of relative thresholds necessarily forces the identification of very low to very high vulnerability zones for any study, and the use of weights on the variables increases the subjectivity of the assessment, all of which impedes the comparability of the index at a global level. Therefore, the ICVI, with the formula based on the arithmetic mean, with absolute limits between 0 and 1 and without variable weightings, is preferable to the CVI for use at the global level.

Analysing district-level climate vulnerability pattern in Madhya Pradesh, India, based on agricultural and socio-economic indicators.

Indian agriculture transitioned from a food deficit sector to a food surplus following the Green Revolution. However, the continued progress of Indian agriculture has been hampered by climate change. This research explores the district-wise vulnerability in Madhya Pradesh, India, to climate change by assessing the composite vulnerability index using the agricultural vulnerability index (AVI) and socio-economic vulnerability index (SEVI). The study seeks to understand how agricultural and socio-economic factors lead to variations in vulnerability across districts and influence targeted adaptation and mitigation strategies. The trend analysis results present declining rainfall and inclining temperature from 1951 to 2021 in Madhya Pradesh, directly affecting the agricultural sector and human livelihood. The composite vulnerability index (CVI) results revealed that districts with low values (< 0.394), such as Burhanpur and Balaghat, demonstrate reduced susceptibility due to limited cultivation, low reliance on rainfall, lower drought susceptibility, and decreased population density. Districts such as Panna and Bhopal show moderate vulnerability (0.394-0.423), with lower fallow land, reduced rainfed agriculture, and socio-economic vulnerability. Extensive agriculture and marginalised workers' presence influence high vulnerability (0.423 to 0.456) in districts such as Tikamgarh and Indore. Districts like Barwani and Jhabua have the highest CVI values (> 0.456), indicating substantial susceptibility to climate impacts. The cluster analysis validates the results of the vulnerability index. The findings highlight the urgent need for tailored adaptation strategies to address the diverse agricultural and socio-economic indicators creating vulnerability in Madhya Pradesh. The study helps understand regional vulnerability patterns and provides evidence-based policy approaches for resilience to climate change effects.

The dilution effect of healthy lifestyles on the risk of cognitive function attributed to socioeconomic status among Chinese older adults: A national wide prospective cohort study.

Lower socioeconomic status (SES) is a risk factor for poor cognitive function, while a healthy lifestyle is associated with better cognitive function. We examined the complex relationship between SES and a healthy lifestyle and cognitive function among older Chinese adults. We used a national prospective cohort of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008-18, aged 65 years and older with normal cognition at baseline. Participants were categorised into the favourable group if they had four to six healthy lifestyle factors and the unfavourable group for zero to three factors. SES was classified as higher and lower by assessing the socioeconomic vulnerability index (SEVI) with six components. Cognitive function was measured using the Mini-Mental State Examination (MMSE) scores and the standardised Z-scores. We applied the linear mixed effects and time-dependent Cox regression models to explore associations and further stratified the analysis by healthy lifestyles. A total of 6851 participants were included (the mean age was 80.87, 43.44% had a favourable lifestyle, and 49.29% had higher SES). Over the 10-year follow-up period, SES status and lifestyle profiles significantly affected the decline in the standardised Z-scores (P < 0.05). The higher SES group with favourable lifestyles exhibited a slower cognitive decline than those with lower SES (by 0.031 points per year, P < 0.05). The association was not observed in those in the unfavourable group (0.010 points per year, P > 0.05). During a follow-up, 25.06% of participants developed cognitive impairment (MMSE<18). We also observed a significant interaction between SES and healthy lifestyles (P < 0.05), with the corresponding associations of SES being more pronounced among participants with unfavourable lifestyles (hazard ratio (HR) = 0.821; 95% confidence interval (CI) = 0.701-0.960) than those with favourable lifestyles (HR = 1.006; 95% CI = 0.844-1.200). A healthy lifestyle may attenuate the adverse impacts of lower SES on cognitive function among older adults. This study might provide important information for protecting cognitive function, especially in low- and middle-income countries.

Association Between Social Vulnerability Index and Hospital Readmission Following Gunshot Injuries

IntroductionNo association regarding classification of social vulnerability and outcomes of patients with gunshot injury have been described. Our goal was to assess whether the socioeconomic vulnerability index (SVI), is associated with an increased risk of hospital readmission following gunshot wounds. MethodsWe conducted an exploratory retrospective cohort study on Massachusetts patients with trauma following gunshot wounds from January 1, 2012 to December 31, 2020 using the institutional trauma registry. We estimated the association between high social vulnerability (defined by the Centers for Disease Control and Prevention as ≥90th percentile) and incidence of all-cause readmission at 30, 60, and 90 d (overall and stratified over sex, race, and age groups). Estimates from unadjusted log-binomial regression were reported using relative risks (RRs) and 95% confidence intervals. Time-to-event (readmission) was assessed using Kaplan-Meier plots. ResultsA total of 386 patients were included for analysis: 211 (55%) with SVI <0.90 and 175 (45%) with SVI ≥0.90. The mean (standard deviation) age was 29 (13) y, with majority being male (89%). There was no strong risk of readmission associated with SVI ≥0.90; the interval with the greatest risk was at 60 d (RR = 1.34; 95% confidence interval [0.73, 2.45]). Among stratified analyses, the strongest associations were observed when restricting to young adults (aged 18-35) with RRs of 2.49, 2.62, and 2.45 for 30, 60, and 90 d readmission, respectively. ConclusionsOverall, high SVI was not associated with all-cause readmission; however, subanalyses suggest an association among young adults. Future research should explore SVI as a tool for identifying patients with trauma at risk for readmission.

Estimation of the Coastal Vulnerability Index Using Multi-Criteria Decision Making: The Coastal Social–Ecological System of Rachgoun, Western Algeria

This research deals with spatial vulnerability in the coastal area of Rachgoun (Algeria), on the southern shore of the Mediterranean Sea. Over the past two decades, the coastal area of Rachgoun has been suffering from a large amount of pressure due to accelerated socioeconomic development, urbanization, tourism, fishing, and agriculture. The main objective of this study is to visualize the coastal vulnerability of Rachgoun using multi-criteria decision making (MCDM). A multidisciplinary approach that integrates geological, physical, and socioeconomic vulnerability was adopted. The selected parameters for the study include lithology, elevation, slope, shoreline change, significant wave height, population density, tourist density, land use/land cover (LULC), road network density, proximity to coast, distance from river, people’s awareness, and designated conservation areas and cultural heritage. Data from AlSat-2 Satellite imagery, aerial photography, topographic maps, and field surveys were processed. Spatial modeling was conducted through the MCDM approach and geographic information systems (GIS) to develop two sub-indices: the natural vulnerability index (CVIN) and the socioeconomic vulnerability index (CVIS). The combination of the two sub-indices allowed us to deduce the integrated coastal vulnerability index (ICVI). The outcomes present a coastal vulnerability map with a spatial resolution of 10 m of the identified problematic area. This map can guide decision-makers in implementing an effective integrated coastal zone management (ICZM) strategy.

Climate change threat on socio-economic condition of agroforestry managers: A vulnerability study in eastern Himalayan state of Mizoram, Northeast India

In recent years, the increase in transition from shifting cultivation to permanent agroforestry (AF) plantations such as oil palm, Areca nut etc. in Mizoram, Northeast India has made the present study all the more essential with regard to social, economic and ecological perspective. Four most prominent AFSs i.e., Parkia based AFS (PAFS), Areca based AFS (AAFS), Oil palm based AFS (OAFS) and Borrasus based AFS (BAFS) were selected for the vulnerability assessment in the tribal state of Mizoram, North-East India (NEI). The association between AF managers and their physical and social surroundings was extensively integrated and analysed to assess the Socio-economic Vulnerability Index (SeVI). This vulnerability assessment involved data normalization, factor analysis, weight assignment, and finally index calculation. 10% household from each of the six villages were sampled to identify the target AFSs following which 78 indicators under 15 domain groups and 3 dimensions were perceived to be apt for this study. AF managers practicing BAFS (0.65) was found to be most vulnerable to climate change followed by OAFS (0.63), AAFS (0.57) and PAFS (0.43). For the dimensions of vulnerability BAFS scored maximum (0.98) for adaptive capacity and OAFS for sensitivity (0.49) and exposure (0.48). While the most vulnerable among domains were: “demographic” for adaptive capacity, “AF function” for sensitivity and “impact on crop varieties” for exposure. Although the IPCC considered AF as an important for climate change, to bridge the gap by adapting new measures for the managers is needed to make them socio-economically less vulnerable henceforth.

How vulnerable are Wular Lake fishing communities compared to non‐fishing communities in rural Kashmir? Insights and interventions for development

AbstractWular Lake, one of the largest wetlands in Asia (13,000 ha in Kashmir Valley) is a biodiversity‐rich Ramsar site supporting nearly 32,000 rural people involved in harvesting fish, water chestnuts, lotus stems and fodder. With 2914 active fishers, Wular Lake contributes 54% of Kashmir's total fish catch. Large‐scale land‐use changes and global warming have resulted in siltation, reduced lake area and alterations in the water flow regime, threatening lake ecology and human livelihoods. A novel census‐based multi‐criteria Socio‐Economic Vulnerability Index (SEVI) was used to assess the vulnerability status of 23 fishing and 115 non‐fishing adjacent villages. All the fishing villages exhibited ‘low’ (0.21–0.40) vulnerability levels, except Kunas village (0.42). Interestingly, no significant differences could be found in vulnerability levels between fishing (23) and non‐fishing (115) villages, although the former exhibited relatively higher social sensitivity. A graphical decision matrix based on sensitivity and adaptive capacity scores provided a snapshot of vulnerability status for each village. Using SEVI scores, drivers (i.e., key indicators responsible for high sensitivity &amp; low adaptive capacity) were identified and corresponding village‐specific development interventions are suggested with Kunas as an illustrative case village. Improving education levels, strengthening community and rural infrastructure, and expanding livelihood options were key short‐term strategies for improving resilience in Kashmir's Wular region.

Comparing socioeconomic vulnerability index and land cover indices: Application of fuzzy TOPSIS model and geographic information system

Vulnerability Assessment (VA) has numerous management implications, particularly for locating the most vulnerable areas affected by land cover degradation. This study aims to assess and compare the relationship between socioeconomic vulnerability (SEV) and land cover indices (LCIs) in summer rangelands (Natanz county) and winter rangelands (Aran-V-Bidgol county) in Isfahan Province, Iran. To assess the socioeconomic vulnerability index (SEVI), a survey was conducted. Based on the SEVI, summer and winter rangelands were classified and mapped using a combination of fuzzy TOPSIS model and geographic information system (GIS) techniques. Field research was conducted to estimate LCIs, including plant cover, plant yield, litter (dead biomass), sand and gravel, bare soil, and forage production. Finally, the correlations between SEVI and LCIs were verified, and the SEV of winter rangelands and summer rangelands was examined. Results showed the rangelands of Chah Robat, Bidhend, and Tar were the most vulnerable summer rangelands, while the rangelands of Chah Zard, Cheshmeh Sefid, and Kandeh Matin were the most vulnerable winter rangelands. Findings further revealed more LCIs, including total ground cover, the yield of shrubs, and total yield had a significant relationship with SEVI in summer rangelands compared to winter rangelands (yield of annual forbs and total yield). Moreover, there was a significant difference between SEVI, determined by the fuzzy TOPSIS model, in summer and winter rangelands. It can be concluded that while the fuzzy TOPSIS model and GIS can be used to gain a better understanding of VA, the type of rangeland has an impact on how well these techniques can assess the SEV of rangelands.

Methodological framework for territorial planning of urban areas: Analysis of socio-economic vulnerability and risk associated with flash flood hazards

• Risk analysis from a socio-natural viewpoint optimizes territorial planning. • Flash flood characteristics were verified during fieldwork. • The Flash flood risk index includes the behavior of the process. • The socioeconomic vulnerability index integrates aspects of the people affected. • Risk index identifies attention priority areas for strengthening local strategies.

Socioeconomic vulnerability and public water arsenic concentrations across the US

Inorganic arsenic is a known human carcinogen and is routinely detected in US community water systems (CWSs). Inequalities in CWS arsenic exist across broad sociodemographic subgroups. Our objective was to evaluate the county-level association between socioeconomic vulnerability and CWS arsenic concentrations across the US. We evaluated previously developed, population-weighted CWS arsenic concentrations (2006–2011) and three socioeconomic domains (the proportion of adults with a high school diploma, median household income, and the Centers for Disease Control and Prevention's overall socioeconomic vulnerability score) for 2,604 conterminous US counties. We used spatial lag models and evaluated the adjusted geometric mean ratio (GMR) of CWS arsenic concentrations per higher socioeconomic domain score corresponding to the interquartile range, and also evaluated flexible quadratic spline models. We also stratified by region and by United States Department of Agriculture Rural-Urban Continuum Codes to assess potential effect measure modification by region and rurality. Associations between socioeconomic vulnerability and CWS arsenic were modified by region and rurality and specific to socioeconomic domain. The fully adjusted GMR (95% CIs) of CWS arsenic per interquartile range higher proportion of adults with a high school education was 0.83 (0.71, 0.98) in the Southwest (corresponding to 17% lower arsenic with higher education), 0.82 (0.71, 0.94) in the Eastern Midwest (18% lower), and 0.65 (0.31, 1.36) in New England (35% lower). Associations between median household income and CWS arsenic were largely null. Higher overall socioeconomic vulnerability was significantly associated with lower CWS arsenic, but only in counties in the Central Midwest and those with total populations less than 20,000. Findings may reflect regional/local differences in both socioeconomic/socio-cultural context and public drinking water regulatory efforts. Across the US, individual domains of socioeconomic vulnerability (especially educational attainment) are more strongly associated with inequalities in CWS arsenic than the complex overall socioeconomic vulnerability index.

Socioeconomic and Environmental Vulnerability Index in the Brazilian Amazon: The Case of the Carajás Railroad

This article assesses the socioeconomic and environmental vulnerability of the 28 municipalities of the Carajás Railroad territory, located in Pará and Maranhão states, Brazilian Amazon. We constructed a Socioeconomic and Environmental Vulnerability Index (IVSEA) applying the Principal Component Analysis (PCA) on a set of indicators built using 1991, 2000, and 2010 censuses data. In this vulnerability analysis at the levels, we also used the Social Progress Index (SPI) of 2014 and 2018, spanning approximately 30 years. Moreover, we analyzed the spatially-weighted percentage changes of surrounding municipalities’ IVSEA and SPI across the censuses and over the 2014-2018 period, respectively. We found that municipalities on the Maranhão's side of the railroad (e.g., Monção and Anajatuba) are more vulnerable than those on the Pará’s. São Luís (Maranhão) and Parauapebas (Pará) are the least vulnerable in the territory. There is a high spatial correlation between the municipalities with their clusters occurring according to the degree of vulnerability. Consistent with the literature, a challenge to improve effectiveness and efficiency in interventions by companies, policymakers, and other stakeholders to reduce vulnerabilities and build resilient and more sustainable regions remains.

Mapping urban socio-economic vulnerability related to heat risk: A grid-based assessment framework by combing the geospatial big data

Heat-related risk due to climate change increases the socio-economic vulnerability in the metropolitan area worldwide. Although many studies have conducted on heat associated vulnerability assessment at various scales, a holistic grid-based framework with the available, multi-source geospatial data remains undetermined. This paper describes an effective method for assessing the socio-economic vulnerability related to heat risk at gird scale by using census data, remote sensing and point of interest (POI) data. The integrated Socio-Economic Vulnerability Index (SEVI) is constructed by considering three dimensions of the demographic vulnerability (DVI), economic vulnerability (EVI) and infrastructure vulnerability (IVI) based on Sensitivity-Exposure-Adaptive capacity framework. A total number of 4807 grids in Hangzhou city of China is involved in the vulnerability analysis. The Monte Carlo method is subsequently employed to quantify the sensitivity of assessing result. Further, we examine the regional spatial heterogeneity and clustering of vulnerability in urban area. The results reveal that all vulnerability index (DVI, EVI, IVI, and SEVI) demonstrate a similar spatial pattern, and the high vulnerability grids are concentrated in urban center. Sensitivity analysis exhibit that the vegetation coverage and availability of medical resources are the key influencing factors that cause a greater variability in SEVI values. In the context of urban grid management, this study contributes new method on identifying the spatial heterogeneity of vulnerability associated with heat stress, which can provide more targeted spatial information to decision makers for optimizing local urban heat vulnerability management strategies.

A Place-based Approach to Assess the Vulnerability of Communities to Urban Floods: Case of Nagpur, India

Amongst all disasters, flood is the most incessant disaster influencing a noteworthy number of individuals all around the world. The developing countries have been profoundly affected by the calamities, due to excessive loss of lives and assets. The city of Nagpur in Maharashtra, India, is prone to water related disasters. In addition, the uncontrolled development has worsened the floods events. The existing physical infrastructure and social attributes have made the population vulnerable to urban floods. The study focuses on conducting a micro-scale i.e., community vulnerability assessment by identifying the drivers of vulnerability. A questionnaire based on the socio-economic and infrastructure characteristics was formulated and a primary survey was conducted. The study involved application of principal component analysis by means of python programming to develop socio-economic and physical infrastructure indices. The analysis enabled component wise and index wise visualization of low vulnerable to high vulnerable zones in Nagpur using Geographic Information System (GIS). The goodness-of-fit for socio-economic and physical infrastructure vulnerability index show R2 value as 0.7219 and 0.7058 respectively, suggesting the models to be substantial. This robust vulnerability framework can gauge the real conditions of the population thereby assist in developing policies and strategies to reduce the impact of urban floods.

Brazil's health system functionality amidst of the COVID-19 pandemic: An analysis of resilience

BackgroundAs of December 31, 2020, Brazil had the second-highest burden of COVID-19 worldwide. Given the absence of federal government coordination, it was up to the local governments to maintain healthcare provision for non-COVID health issues. In this descriptive study, we aimed to discuss the SUS functionality and resilience, describing the impact of the pandemic on non-COVID health services delivery while considering the regional inequalities of the allocation of financing health system, health infrastructure and health workforce.MethodsWe used input-output framework based on the World Health Organization (WHO) Health System Building Blocks to estimate health system functionality and resilience. An ecological assessment was designed to calculated mean relative changes to compare the first year of the pandemic in Brazil with the previous one. All data used in this study were anonymized and made available by the Brazilian Ministry of Health. Input indicators were categorized in health system financing (federal funding received as well as expenditure of both state and city governments), health system's infrastructure (hospital beds) and health workforce (healthcare workers positions). Output indicators were categorized into nine different groups of service delivery procedures. To explore the relationship between the variation in procedures with socioeconomic conditions, we used the Socioeconomic Vulnerability Index (SVI).FindingsState governments had a 38·6% increase in federal transfers, while municipal governments had a 33·9% increase. The increase of ICU beds reached its peak in the third quarter of 2020, averaging 72·1% by the end of the year. The country also saw an increase in jobs for registered nurses (13·6%), nurse assistants (8·5%), physiotherapists (7·9%), and medical doctors (4·9%). All procedures underwent expressive reduction: Screenings (−42·6%); Diagnostic procedures (−28·9%); Physician appointments (−42·5%); Low and medium complexity surgeries (−59·7%); High complexity surgeries (−27·9%); Transplants (−44·7%); Treatments and clinical procedures due to injuries of external causes (−19·1%); Irrepressible procedures (−8·5%); and Childbirths (−12·6%). The most significant drop in procedures happened in the first quarter of the pandemic, followed by progressive increase; most regions had not yet recovered by the end of 2020. State-level changes in numbers of procedures point towards a negative trend with SVI.InterpretationThe Brazilian Government did not consider that socioeconomically vulnerable states were at a higher risk of being impacted by the overburden of the health system caused by the COVID-19, which resulted in poorer health system functionality for those vulnerable states. The lack of proper planning to improve health system resilience resulted in the decrease of a quarter of the amount of healthcare procedures increasing the already existing health disparities in the country.FundingMCTIC/CNPQ/FNDCT/MS/SCTIE/DECIT No 07/2020.

Households’ Socioeconomic Vulnerability Assessment Due to COVID-19 Outbreak: A Web-Based Survey in Bangladesh

Aim: COVID-19, which can be considered a disastrous event, has created not only a public health emergency but also a major socio-economic crisis in Bangladesh. This study, therefore, aimed to assess households’ socioeconomic vulnerability due to the COVID-19 outbreak in the country. Methods: A quantitative cross-sectional survey was performed among 404 households from different districts in Bangladesh. The socioeconomic vulnerability index (SeVI) was developed using data collected from participants via an online-based self-reported questionnaire that included demographic, social, economic, and physical characteristics as well as exposure to COVID-19. Results: The socioeconomic vulnerability index (SeVI) was calculated as an index score of 0.405 where social, economic, and COVID-19 exposure were reported to be the more impactful components of adaptive capacity, sensitivity, and exposure, respectively. Furthermore, the economic options for households were greatly limited by the consequences of the COVID-19 pandemic. Practical implications: This study may help to identify the socioeconomic issues that resulted from the COVID-19 outbreak in the country and instruct the policymakers and corresponding authorities on which areas to emphasize for policy implementation so that households become socially and economically less susceptible to the COVID-19 outbreak as well as related infectious diseases and disastrous events in the upcoming years. Conclusion: This study found socioeconomic vulnerability among Bangladeshi households. The corresponding authorities should adopt policy initiatives to minimize the socioeconomic vulnerability due to the COVID-19 outbreak in the country.

Socioeconomic Vulnerability Index and Obesity among Korean Adults

Examining the socioeconomic vulnerability–obesity relationship is a different approach than comparing obesity rates according to the socioeconomic level. This study explored the socioeconomic vulnerability–obesity relationship among Korean adults. This secondary analysis used data from the Korea National Health and Nutrition Examination Survey, which were collected nationwide from participants aged 30–64 years. Seven socioeconomic indicators (education level, residential area, personal income level, household income level, food insecurity, house ownership, and national basic livelihood security beneficiary status) were used to create the socioeconomic vulnerability index. The prevalence of obesity was higher in the lowest socioeconomic vulnerability index quartile than in the highest socioeconomic vulnerability index quartile (odds ratio = 1.31; 95% confidence interval = 1.13–1.52) after adjusting for gender. When developing future interventions for the prevention and management of obesity, health care providers and researchers need to consider the differences in socioeconomic vulnerability index in adults.

Mapping integrated vulnerability of coastal agricultural livelihood to climate change in Bangladesh: Implications for spatial adaptation planning

Understanding the spatial variation of agricultural livelihood vulnerability to climate change is crucial for developing adaptation strategies in the future, something that has only been seldom done so far in developing economies like Bangladesh. To this end, we developed an integrated vulnerability index (IVI) based on the IPCC framework for analyzing and mapping the vulnerability of agricultural livelihoods in coastal Bangladesh. The IVI was calculated as a function of three components: exposure, sensitivity, and adaptive capacity. We used 45 indicators from nationally comparable and reliable datasets to conduct the research. Besides, a socio-economic livelihood vulnerability index (SELVI) was developed on the basis of sensitivity and adaptive capacity indicators and displayed in a scatter diagram in order to identify the socio-economically more vulnerable districts of coastal Bangladesh. A circumplex chart was used to disaggregate the normalized indices of sensitivity and adaptive capacity components, allowing the researcher to discover the factors that cause and mitigate the vulnerability. Using the IVI information, a vulnerability map was created that revealed that Patuakhali, Noakhali, Bhola, and Barguna districts in the exposed central coastal region were the topmost vulnerable districts, reflecting the fact that the agricultural livelihoods of 7.3 million people were highly vulnerable to the effects of climate change. The geographical diversity in salt intrusion, river-bank erosion, dependence ratio, crop yield, literacy, the density of physicians in the hospital, disaster-resistant houses, shelter facilities, and irrigated farming areas contributed to the diverse coastal agricultural livelihood vulnerability.

Socioeconomic Disparities in Severe Acute Respiratory Syndrome Coronavirus 2 Serological Testing and Positivity in New York City.

BackgroundWe characterized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody test prevalence and positive test prevalence across New York City (NYC) in order to investigate disparities in testing outcomes by race and socioeconomic status (SES).MethodsSerologic data were downloaded from the NYC Coronavirus data repository (August 2020–December 2020). Area-level characteristics for NYC neighborhoods were downloaded from United States census data and a socioeconomic vulnerability index was created. Spatial generalized linear mixed models were performed to examine the association between SES and antibody testing and positivity.ResultsThe proportion of Hispanic population (posterior median, 0.001 [95% credible interval, 0.0003–0.002]), healthcare workers (0.003 [0.0001–0.006]), essential workers (0.003 [0.001–0.005]), age ≥65 years (0.003 [0.00002–0.006]), and high SES (SES quartile 3 vs 1: 0.034 [0.003–0.062]) were positively associated with antibody tests per 100000 residents. The White proportion (–0.002 [–0.003 to –0.001]), SES index (quartile 3 vs 1, –0.068 [–0.115 to –0.017]; quartile 4 vs 1, –0.077 [–0.134 to –0.018]) and age ≥65 years (–0.005 [–0.009 to –0.002]) were inversely associated with positive test prevalence (%), whereas the Hispanic (0.004 [0.002–0.006]) and essential worker (0.008 [0.003–0.012]) proportions had positive coefficients.ConclusionsDisparities in serologic testing and seropositivity exist on SES and race/ethnicity across NYC, indicative of excess coronavirus disease burden in vulnerable and marginalized populations.

Assessment of the Socioeconomic Vulnerability to Seismic Hazards in the National Capital Region of India Using Factor Analysis

The seismicity of the National Capital Region (NCR) of India increased significantly over the last decade. Communities in the NCR face significant exposure to damaging seismic events, and the seismic risk arises not only from the region’s proximity to the Himalayan mountains, but also from the socioeconomic vulnerabilities in its communities and the current capacities of different localities to respond to and recover from any unforeseen large seismic event. GIS-based spatial distribution of exposure to seismic hazards (SH) can help decision-makers and authorities identify locations with populations at high seismic risk, and to prepare risk-mitigation plans. Socioeconomic vulnerability (SeV) studies serve as a basis for quantifying qualitative measures. For this purpose, in the present study, the hazard of place (HoP) model is used to assess SeV to seismic hazards in the NCR. Social indicators like age, gender, literacy, family size, built environment, etc., comprising a total of 36 variables, are used to assess a socioeconomic vulnerability index (SeVI) based on factor and principal component (PCA) analyses. Based on PCA, 20 variables were retained and grouped into four factors: socioeconomic status, employment status, building typology, and family size. Ground-motion parameters, estimated from probabilistic seismic hazard assessment, are integrated with the socioeconomic vulnerability index to quantify exposure to seismic hazards. The spatial distributions in the produced socioeconomic-vulnerability index and seismic–hazard–exposure maps highlight the critical areas. The results reveal that areas of low literacy, high unemployment, and poor housing condition show moderate-to-high vulnerability. The south-eastern region of the study area is assessed as a high-risk zone by an integrated SeV–SH risk matrix. The results of this study emphasize the importance of the socioeconomic vulnerability component of disaster risk–reduction programs, from a holistic perspective, for the areas with high seismicity.

Multi-scale comparison of urban socio-economic vulnerability in the Washington, DC metropolitan region resulting from compound flooding

The co-occurrence of different flood types (i.e. compound floods), such as coastal storms, riverine flow, and urban pluvial runoff, can cause severe damage to urban areas. Like many U.S. metropolitan regions along the coast, the Washington, DC metropolitan area, where increasing precipitation rates and sea-level rise have been observed, is vulnerable to the impacts from such events. This study aims to evaluate urban socio-economic vulnerability in the Washington, DC Metropolitan Region resulting from compound flooding at multiple scales. The socioeconomic damages from riverine flood and storm surges, which is defined as exposure index, were combined with the Socio-Economic Vulnerability Index (SOVI) in order to detect vulnerable populations to compound flood events at a range of scales (tract, group, and block). The highest damage was found on the banks of the Potomac River in the compound flood scenario. A high-precipitation scenario was also performed, leading to severe damages in locations with denser infrastructures, such as DC. The multi-scale comparison suggested that block scale analysis is more sensitive to vulnerability and flood damages compared to coarser scales, i.e., group and tract. The distribution of the risk was found significantly dependent on both the type of the compound flood event and the scale of the analysis. From a flood management perspective, coarser scale assessments can mislead efforts as it is not able to highlight specific locations with substantial vulnerable populations. The method presented in this study can potentially aid decision-makers to identify the vulnerable populations to compound floods in large coastal metropolitan areas.