Social Vulnerability Assessment Research Articles

Integrated assessment of geophysical and social vulnerability to natural hazards in North-East Region, Romania

The multidisciplinary approach outlined in this paper aims to assess the correlation between geophysical and social vulnerability for disaster risk reduction. To achieve this, two multi-criteria methods based on Geographic Information Systems (GIS) techniques have been integrated to assess the risk to natural hazards in the North-East Development Region. The Analytical Hierarchy Process (AHP) was utilized to conduct a comprehensive hazard analysis, including floods, landslides, and earthquakes. The Principal Component Analysis (PCA) method was applied to examine the spatial distribution of social vulnerability at the Local Administrative Unit (LAU level), utilizing 24 variables to generate 6 principal components. Based on these results a Regional Risk Index (RRI) was developed using the bivariate method, combining the multi-hazard distribution with social vulnerability. The results showed that the north-eastern part of the region presents the highest risk, encompassing 10.68% of administrative units. These results can contribute to the design of risk reduction programs and policies.

A Dynamic Spatiotemporal Understanding of Changes in Social Vulnerability to Wildfires at Local Scale

Research on wildfires and social vulnerability has gained significant importance due to the increasing frequency and severity of wildfires around the world. This study investigates the dynamic changes in social vulnerability to wildfires over a decade in Idaho, USA, utilizing GIS-based tools and a quasi-experimental design. We assess the evolving nature of social vulnerability at a local scale, emphasizing both spatial and temporal dynamics. Initially, we identified social vulnerability trends in relation to varying levels of wildfire risk. The research then employs propensity score matching to contrast areas affected by wildfires in 2012 with similar non-affected regions, thereby quantifying the short-term shifts in social vulnerability post-wildfires. The results indicate that regions with a high wildfire risk may display elevated vulnerability, characterized by an increase in unemployment rates and a reduction in high-income households. These findings tentatively demonstrate the compounded effect of wildfires on already vulnerable populations, highlighting the critical need for targeted interventions. Ultimately, this study underscores the importance of integrating dynamic social vulnerability assessments into wildfire management and planning, aiming to enhance community resilience and equitable resource distribution in the face of escalating wildfire threats.

Assessment of Physical, Social, and Economic Vulnerability to Landslides Disaster in the Karangsambung Karangbolong National Geopark, Indonesia.

Abstract The Karangsambung-Karangbolong National Geopark (GNKK) is administratively located in Kebumen Regency, Central Java Province, Indonesia. The GNKK area has an area of 543,599 km2 which includes 12 sub-districts with 117 villages. The morphology of the GNKK area consists of hills, valleys, and plains to the coast. The morphology of hills and mountains is an area that is prone to landslides. Assessment of physical, social, and economic vulnerability needs to be carried out so that disaster risk analysis and mitigation can be carried out in the future. The aims of this study are 1. To determine the spatial distribution of physical, social, and economic vulnerabilities in the Karangsambung Karangbolong National Geopark Area, 2. To analyze the physical, social, and economic vulnerability to landslides in the Karangsambung Karangbolong National Geopark Area. Assessment of physical, social, and economic vulnerability using the Spatial Multi-Criteria Evaluation (SMCE) method. The results of the main study of the GNKK area have high, moderate, and low classes of physical, social, and economic vulnerability to landslides. However, most GNKK areas are classified as moderate. The community’s social conditions in each village significantly affect the areas prone to frequent landslides. The strategy for disaster mitigation by a landslide is increasing human resources for disaster knowledge with disaster mitigation training and using infrastructures such as installing landslide-prone signs and trigger lines.

The association between social vulnerability and geriatric assessment impairments among older adults with gastrointestinal cancers-The CARE Registry.

Older adults comprise the majority of patients with gastrointestinal (GI) cancer. Geriatric assessments (GAs) are recommended for older adults with cancer in part to detect aging-related impairments (e.g., frailty) associated with early mortality. Social factors like social vulnerability may also influence aging-related impairments. However, the association between social vulnerability and aging outcomes among older adults with cancer is understudied. The authors included 908 older adults aged 60 years and older who were recently diagnosed with GI cancer undergoing GA at their first prechemotherapy visit to the University of Alabama at Birmingham oncology clinic. The primary exposure of interest was the social vulnerability index (SVI). Outcomes were frailty (frail vs. robust/prefrail) and total number of GA impairments (range, 0-13). The authors examined the association between SVI and outcomes using Poisson regression with robust variance estimation and generalized estimating equations. The median age at GA was 69 years (interquartile range, 64-75 years), 58.2% of patients were male, 22.6% were non-Hispanic Black, 29.1% had colorectal cancer, 28.2% had pancreatic cancer, and 70.3% had stage III/IV disease. Adjusting for age, sex, cancer type, and disease stage, each decile increase in the SVI was associated with an 8% higher prevalence of frailty (prevalence ratio, 1.08; 95% confidence interval, 1.05-1.11) and a 4% higher average count of total GA impairments (risk ratio, 1.04; 95% confidence interval, 1.02-1.06). The results were attenuated after further adjustment for race and education. Greater social vulnerability was associated with a higher prevalence of frailty and an increasing average number of GA impairments among older adults with GI cancers before systemic treatment. Intervening on social vulnerability may be a target for improving the risk of frailty and GA impairments, but associations of race and education should be further evaluated.

GIS-based Social Vulnerability Integration for Robust Flood Response, Disease Prevention and Community Resilience in Chennai Metropolitan Area post-Cyclone Michaung

The present study outlines a comprehensive strategy for flood response, disease prevention and long-term community resilience in the aftermath of a recent Cyclone Michaung, with the proximity of landfall near Chennai and the increased likelihood of flooding in the CMA. Drawing insights from an existing social vulnerability map, the study addresses the unique challenges posed by flooding and aims to mitigate the heightened risk of waterborne and vector-borne diseases. Objectives encompass assessing social vulnerability, formulating a targeted flood response strategy, implementing healthcare interventions for disease prevention, strengthening information dissemination and advocating for long-term resilience planning. The methodology involves reviewing the existing vulnerability map, identifying vulnerable communities, integrating flood impact data and developing a comprehensive response plan. The study utilizes GIS and Remote Sensing technologies for monitoring and assessing the results. Key findings from the social vulnerability assessment inform prioritized intervention areas for both flood response and disease prevention. The discussion interprets results in the context of strategy effectiveness, emphasizing the significance of a nuanced and inclusive approach. This manuscript serves as a guide for stakeholders in implementing a holistic strategy that addresses immediate concerns, prevents disease outbreaks and fosters long-term community resilience.

Social vulnerability assessment under different extreme precipitation scenarios: A case study in Henan Province, China.

Extreme precipitation usually cause grievous losses&casualties, which varies greatly under different scenarios. This paper took Henan province as an example, it innovatively constructed three different extreme precipitation scenarios and built indicators system of social vulnerability from exposure, sensitivity and resilience based on MOVE framework. Social Vulnerability Indexs(SoVI) were then calculated by mathematical models under three different reoccurrence intervals. The results show that SoVI was low in the west and high in the north. High SoVI areas expanded to the middle and south as recurrence intervals increased. SoVI in each area of Henan province increased along with the recurrence intervals at different growth rates. The larger the recurrence interval was, the faster the SoVI increased. The results indicate SoVI is greatly affected by disaster levels, which need to be incorporated into social vulnerability. This study provides not only a new thought for social vulnerability assessment, but also a reference for the policymakers to formulate related risk management policies.

Enhancing social vulnerability assessment with energy resilience: A comprehensive study of the Netherlands

A comprehensive vulnerability assessment is a scientific basis for the realization of the United Nations' sustainable development goals. Energy resilience plays a crucial role in mitigating social vulnerability due to disaster shocks. Often, energy infrastructure and services collapse after disasters. The recent Russia-Ukraine war has exacerbated Europe's energy crisis and social vulnerabilities, making it even more urgent to add energy resilience to vulnerability assessments. This paper takes the Netherlands as the study area for vulnerability assessment, constructs a new social vulnerability indicator (SVI) system supplemented with the energy element, and compares that with the traditional energy indicator system.The results indicate that: 1) The introduction of energy indicators fills the gap of traditional SVI assessment. 2) Energy indicators reveal regional and spatial differences in potential social vulnerability in the Netherlands. 3) Energy-inclusive SVI demonstrates that uneven urbanization exacerbates risks and inequalities for vulnerable groups, with potential impacts on social vulnerability. Sustainable urban development requires the search for a recognized and coordinated approach to managing vulnerability across regions. The complementarity of energy indicators offers opportunities to provide a more comprehensive assessment of spatial patterns of social vulnerability, identify potentially vulnerable areas, enhance urban disaster resilience, and achieve sustainable urban development.

The Vulnerability Assessment of Flash Floods Disaster in the Upper Cisadane Watershed

Flash floods is a sudden flood disaster that can be triggered by several factors, one of which is the landslides that occur in river basins. In Bogor Regency, there are fourteen sub-districts located in the Upper Cisadane watershed area that are prone to flash flood disaster. This study aims to determine social, economic, physical and environmental vulnerability assessment of the community in the Upper Cisadane watershed area based on the modification assessment from PERKA BNPB No. 12 Tahun 2012. According to the vulnerability index, the Upper Cisadane watershed has high and very high classes of flash floods vulnerability. Sub-districts with high vulnerability index class are Nanggung, Pamijahan, West Bogor, South Bogor, Central Bogor, East Bogor, Cibungbulang, Cigudeg, Leuwisadeng, and Sukajaya, meanwhile, sub-districts with very high vulnerability index are Caringin, Ciampea, Ciawi, Cigombong, Cijeruk, Ciomas, Dramaga, Kemang, Leuwiliang, Megamendung, Rancabungur, Rumpin, Tamansari, and Tenjolaya.

Identifying vulnerable populations in urban society: a case study in a flood-prone district of Wuhan, China

Abstract. In the context of unprecedented extreme weather and climatic events, the internal structural factors of society play a decisive role in determining the extent to which human beings are affected by disasters and their ability to respond to them. In the past few decades, rapid urbanization in developing countries, such as China, has greatly increased social vulnerability. This process has generated uneven living conditions and created many vulnerable groups, including urban poverty, migrants, and socially and geographically marginalized groups. These groups face difficulties in living conditions, education, livelihood stability, and more. This study sets up indicators from a micro-perspective: three indicators of exposure, four indicators of sensitivity, and eight indicators of adaptive capacity. Based on this evaluation index system, this study conducted a social vulnerability assessment of the population in Hongshan District, Wuhan, China, through individual questionnaire surveys. K-means cluster analysis was used to determine high, medium, and low levels of social vulnerability, which were used to compare different community types and identify vulnerable groups. The results showed close interrelationships between different types of communities in terms of physical and built environments as well as varying levels of social vulnerability to disasters. The high-vulnerability group accounted for 12.9 % of the 599 samples, the medium-vulnerability group accounted for 48.4 %, and the low-vulnerability group accounted for 38.7 %. The higher-vulnerability groups exhibited characteristics such as low education, poor health, low annual income, unstable work, and insufficient social security. Quantitative understanding of the degree of dissimilarity in social vulnerability among different communities and populations is significant in reducing social vulnerability and disaster risk specifically and effectively.

Seasonal rockfall risk analysis in a touristic island: Application to the Tramuntana Range (Mallorca, Spain)

Rockfalls are an ever-present possibility in the mountainous context of the Tramuntana Region (Mallorca, Spain). Recent events have shown the high potential for direct and indirect impact on the safety of people and economic activities, lasting for weeks or even months. In the present study, we start from a probabilistic assessment of the rockfall hazard (spatial propensity and temporal recurrence), based on a detailed historical record of occurrences and rockfall modelling, which is subsequently superimposed on three exposure scenarios and on a social vulnerability assessment. Exposure considers the floating population at three seasons of the year, given the area's high tourist aptitude. Vulnerability considers on the one hand the intrinsic characteristics of individuals and, on the other, the characteristics of the surrounding territory that act to facilitate emergency operations, mitigate the immediate impact and enhance rapid recovery. Due to the characteristics of the island and the spatial distribution of tourism, the results show that the highest density of rockfall trajectories potentially affect areas of high exposure, whose access by emergency services is complex. Not being, in general, the areas of highest individual criticality, those areas have in most situations low support capability installed or nearby.The results constitute a useful tool for emergency and risk management planning in multiple sectors linked to risk governance. Despite the high geographic detail of the analysis, these studies do not replace exposure and vulnerability analysis at the building level, for which the contribution of georeferenced Census data is fundamental.

Social vulnerability and climate risk assessment for agricultural communities in the United States

Floods and droughts significantly affect agricultural activities and pose a threat to food security by subsequently reducing agricultural production. The impact of flood events is distributed disproportionately among agricultural communities based on their socio-economic fabric. Understanding climate-related hazards is critical for planning mitigation measures to secure vulnerable communities. This study introduces a holistic approach for evaluating the combined risks associated with drought and flood hazards for agricultural communities in the United States. It accomplishes this by merging social vulnerability indicators with data on drought and flood exposure, enabling the identification of the most susceptible agricultural communities. The research seeks to offer valuable insights into the vulnerability of agricultural communities across the United States. It fills a vital research gap by conducting a comprehensive nationwide assessment of social vulnerability, considering expected annual losses related to both flood and drought hazards, and amalgamating social vulnerability with these expected annual losses. The analyses were conducted by adapting datasets and methodologies that are developed by federal institutions such as FEMA, USACE, and USDA. The study identified the 30 most socially vulnerable counties and assessed their exposure to drought and flooding, finding that Mendocino, Sonoma, Humboldt, El Dorado, Fresno, and Kern counties in California had the highest drought exposure and expected annual losses, with Humboldt (CA) and Montgomery (TX) having the highest combined risk. The study estimated over $1 billion in crop damage, with California experiencing the greatest losses, primarily affecting a diverse range of crops, while the Midwest was primarily impacted in terms of major crop types. The findings of this study can serve as supportive information for policymakers to better understand climate risks in agricultural communities and identify where risk mitigation activities should be allocated.

Application of geospatial tools in the assessment of Flood hazard impact on social vulnerability of Malda district, West Bengal, India

Social vulnerability assessment is a dynamic process, which varies from place to place. In the present study, the social vulnerability index (SVI) of Malda district has been prepared because of several impacts of flood inundation. The flood inundation layer has been generated using multi-temporal remote sensing data. The flood inundation layer is prepared from real-time Synthetic Aperture Radar (SAR) data. For social vulnerability assessment, the most efficient indicators are household composition, age & sex composition, and underprivileged population (SC& ST). Economic and educational data has been collected from the Census of India Handbook 2011. All these data are combined with the district's village database on the GIS platform. The weightage overlay analysis method is applied to generate the social vulnerability index of the study area, where the multi-influencing factor (MIF) technique has been used for determining the influencing factors. The social vulnerability index has categories into Very High (4%), High (37%), Moderate (32%) and Low (27%). The social vulnerability index is being further intersected with the flood inundation layer to build a database for the most vulnerable area of this district. It has been observed that 70 villages are in Very High zones, 662 villages are in High, 578 villages are in Moderate and 479 villages are in Low zones. This study will help the disaster manager and stakeholders about the vulnerable situation of the study area and also depict the importance of geospatial techniques in disaster management.

Modes of climate mobility under sea-level rise

Exposure to sea-level rise (SLR) and flooding will make some areas uninhabitable, and the increased demand for housing in safer areas may cause displacement through economic pressures. Anticipating such direct and indirect impacts of SLR is important for equitable adaptation policies. Here we build upon recent advances in flood exposure modeling and social vulnerability assessment to demonstrate a framework for estimating the direct and indirect impacts of SLR on mobility. Using two spatially distributed indicators of vulnerability and exposure, four specific modes of climate mobility are characterized: (1) minimally exposed to SLR (Stable), (2) directly exposed to SLR with capacity to relocate (Migrating), (3) indirectly exposed to SLR through economic pressures (Displaced), and (4) directly exposed to SLR without capacity to relocate (Trapped). We explore these dynamics within Miami-Dade County, USA, a metropolitan region with substantial social inequality and SLR exposure. Social vulnerability is estimated by cluster analysis using 13 social indicators at the census tract scale. Exposure is estimated under increasing SLR using a 1.5 m resolution compound flood hazard model accounting for inundation from high tides and rising groundwater and flooding from extreme precipitation and storm surge. Social vulnerability and exposure are intersected at the scale of residential buildings where exposed population is estimated by dasymetric methods. Under 1 m SLR, 56% of residents in areas of low flood hazard may experience displacement, whereas 26% of the population risks being trapped (19%) in or migrating (7%) from areas of high flood hazard, and concerns of depopulation and fiscal stress increase within at least 9 municipalities where 50% or more of their total population is exposed to flooding. As SLR increases from 1 to 2 m, the dominant flood driver shifts from precipitation to inundation, with population exposed to inundation rising from 2.8% to 54.7%. Understanding shifting geographies of flood risks and the potential for different modes of climate mobility can enable adaptation planning across household-to-regional scales.

Assessing social vulnerability to flood hazards: A case study of Sarawak's divisions

Social vulnerability assessment to flood hazard depends upon multiple factors that can vary across the different indicators. However, there is limited knowledge on specific indicators suitable for assessing social vulnerability on Sarawak. This study systematically analyzed important components of vulnerability and mapped them by weight for the 12 different divisions. Indices focusing on components of the two different dimensions of vulnerability (physical exposure and resistances) were identified based on the literature. Data on these different indices were then collected through relevant government agencies. Components of vulnerability dimensions were assessed and significantly contributing components were identified by Principal Component Analysis (PCA). An entropy method was used to weight the dimensions of vulnerability for the different divisions. Vulnerability was estimated based on the Iyengar and Sudarshan methodology and the data were used to produce a vulnerability map based on a proposed Social Vulnerability Index (SVI). The results indicated that divisions of Kuching, Miri, Sibu and Bintulu were more vulnerable (score over than 0.81) than those in other divisions. Greater vulnerability was mainly due to high exposure to extreme events and less adaptive capacity of resistance, which can affect agricultural production negatively, in combination with high population density in communities. The map clearly shows which areas are more susceptible, indicating that the government's adaptation measures should vary depending on the available resources, urgency, and means of survival needed to achieve resilience against climate change.

Impact of social vulnerability assessment on flood risk management processes in the urban environment in Annaba province


 
 
 Considering that flood risk is one of the greatest natural hazards threatening human beings, the standard approach of flood risk management is mostly based on structural mea- sures giving less importance to uncertainty as a main factor. The robustness leads frequently to failures in the structural measures as a factor of uncertainty, in addition to other factors like changes in hazard comportment. The current study represents an evaluation of flood policy in Annaba city, how decision-makers deal with this issue, and how to reduce exposure and susceptibility factors. The evaluation is based on the study of flood risk components, hazard amount, vulnerability degree and people’s perception of flood risk. The study also assesses how people handle flood risk and their capability to cope with extreme events. A survey method was used to assess the potential risks as it involves analyzing different flood risk aspects by conducting a survey through questioning local residents. We can state that exposure is highly affected by the number and density of the population characterized by the high probability of human and material losses in the study area. On the other hand, the vulnerability operates on a smaller scale that increases the capacity of flood risk to affect humans and other components of the environment. This study affirms that the uncertainty in hazard determination forecasting and misevaluation of social vulnerability leads inevitably to devastating consequences in the case of an exceptional event. Moreover, the behaviour of citizens during and after disaster phases can have a key role in flood risk management. Taking into consideration complexities related to social behaviour enhances the outcome of scenarios that lead consequently to more realistic forecasting. These findings concluded that the risk has always existed, i.e., the notion of «zero risk» never exists by natural laws. Knowing that risk management is the only way to deal with such issues, we highlight the importance of urban governance that integrates all actors without exclusion, based on a partnership aimed at obtaining optimal results. The essential principle of this mode of management is the reduction of economic and human losses.
 
 

Assessment and analysis of social vulnerability to island seismic disasters

More than 11,000 islands in China are located at the intersection of the Circum-Pacific and Eurasian seismic belts. The current research on the Social Vulnerability of Seismic Disasters (SVSD) mainly focuses on inland area, which has limited applicability for islands field. This paper set China island counties as the research object. We established a comprehensive index system to express islands' unique SVSD characteristics, consisting of 27 indicators in three aspects: exposure, sensitivity, and coping capacity. Afterwards, taking China island counties as the research object, Principal Component Analysis (PCA) and Pearson correlation analysis were used to screen the indicators, and the CRITIC and entropy weight methods were used to assign weights. Then the Social Vulnerability Index (SoVI) was calculated to express the islands' SVSD, which is further discussed to get the spatial distribution and possible causes. The assessment method established in this paper could be a reference for quantitative analysis of the islands’ SVSD. This research is fundamental for the implementation of island seismic disaster prevention, mitigation planning, and sustainable development.

Case study in Poland: Understanding spatial diversity of social vulnerability to natural hazards based on local level assessments within the European Union

Social vulnerability is an element of disaster risk theory and reduction, a tool to understand and improve risk mitigation. The paper focusses on social vulnerability to multi-hazards within the EU on Central and Southern Europe but not including physical factors; within Poland, this quantification type is as yet unavailable. Based on the knowledge and social vulnerability estimations in selected countries within the European Union and the US, it shows the Social Vulnerability to Natural Hazards index to unify these approaches.One case study in Poland, which included careful study of the national database, revealed the problems of collecting useful data in order to study social vulnerability within municipalities. But it also indicated a useful variable when placing a social vulnerability assessment. The paper shows maps within the most vulnerable municipalities in Poland by percentage share, with 41.8% urban and 41.46% urban-rural municipalities showing the highest value of social vulnerability based on this comprehensive index. It also indicates the need to take locally better-targeted and diverse policy and actions for risk reduction using social vulnerability in the type of municipality.Such a richness of approaches with a simultaneous diversity of used variables could be due to a lack of any homogeneous data collected for municipalities within EU states. So we suggest there is a need to build a unified database in Europe in order to estimate social vulnerability in municipalities. It is a basic requirement when it comes to comparing disaster risk reduction progress and effectiveness in the EU.

Evaluation and formation mechanism of rural social vulnerability under natural hazard: A case study of the eastern Qinghai-Tibetan Plateau, China

Global environmental change has posed serious threats and challenges to human survival and sustainable development, especially for mountainous communities with fragile ecological environments, weak infrastructure, and underdeveloped economic development. Reducing rural social vulnerability has become an important way to promote global rural revitalization and achieve the United Nations Sustainable Development Goals. However, current research has mostly focused on social vulnerability assessment, with few revealing its formation mechanism. Based on the collected survey data of 240 households, this paper selected Zhouqu county as a case, which located in the eastern edge of the Qinghai-Tibet Plateau, and constructed theoretical framework and hypothesis model of social vulnerability from three dimensions: exposure, sensitivity, and adaptability. On the basis of analyzing the characteristics of social vulnerability, we used structural equation model to further explore its formation mechanism. The result shows that the mean value of social vulnerability index of farmers under natural hazards is 0.442, and nearly 30% of the surveyed farmers have high social vulnerability. There are significant differences in social vulnerability among households in different communities, different economic levels and different livelihood styles. Natural hazards have a double-edged sword effect on the rural social system. They can not only directly aggravate social vulnerability by weakening household natural capital, physical capital, financial capital and psychological capital, but also indirectly stimulate the vitality of social capital, integrate human capital and social resource to reduce social vulnerability. Finally, we put forward effective countermeasures to reduce the rural social vulnerability. Our study aimed to providing theoretical reference for developing countries to formulate risk management policies and disaster prevention and mitigation planning in mountain areas.

Constructing a social vulnerability index for flooding: insights from a municipality in Sweden

Floods disproportionately affect disadvantaged groups. Social vulnerability assessments are the first step in designing just and equitable flood risk reduction strategies. In Sweden, earlier social vulnerability indices apply top-down approaches. In this paper, we develop and apply a combined bottom-up and top-down approach to assess social vulnerability to flooding at a sub-municipal level in Sweden. We tested an indicator-based climate risk and vulnerability framework, more specifically the impact chain method suggested by the Vulnerability Sourcebook. We involved stakeholders using various participatory methods in three workshops, interviews, and informal exchanges to identify variables and indicators for social vulnerability. The Indicators were aggregated into a composite social vulnerability index using exploratory factor analysis. We thereafter mapped the social vulnerability index scores to uncover spatial injustices. We found that the proposed social vulnerability index captures municipal nuances better than national-level approaches. Our findings indicate an uneven spatial distribution of social vulnerability that mimics the overall patterns of income segregation found in the municipality. Many areas that score low in social vulnerability endure high exposure to floods. The social vulnerability index can support municipalities in designing just and equitable interventions toward flood risk reduction by serving as an input to policymaking, investment strategies, and civil protection.

Social vulnerability assessment for an industrial city in Natech accidents: A Bayesian network approach

ABSTRACT China is a large industrial country where tropical meteorological disasters occur frequently. Therefore, natural-technological (Natech) risk cannot be ignored. Assessing the social vulnerability of an industrial city prone to tropical meteorological disaster-induced Natechs is urgent. To analyze the social vulnerability of such cities, we propose a Bayesian network (BN)-based method to model the social vulnerability framework. Natech is characterised by high-consequence and low-probability. The industrial cities in Southeast China are selected as a case study. The Monte Carlo method simulates the data generated in industrial cities suffering from tropical disaster-induced Natechs, and the conditional probability tables of BN descendant nodes are obtained by the expert scoring method. After sensitivity analysis, we conclude that the ‘catastrophic index of tropical cyclones,’ ‘population density,’ and ‘prevention capacity’ have important impacts on social vulnerability. Human traits, the social environment, and the economy play important roles in social vulnerability assessments. Therefore, reducing the catastrophic index of tropical cyclones and population density and strengthening prevention capacity management measures are necessary. Some suggestions obtained after sensitivity analysis can assist governments in improving disaster prevention and mitigation abilities and formulating urban planning policies for sustainable development. Highlights Industry city’s vulnerability analysis for Natural-technological (Natech) accidents A social vulnerability assessment framework for sustainable development A Bayesian network combined with the Monte Carlo simulation data and expert judgment Risk management for high-consequence and low-probability events