Multidimensional Vulnerability Research Articles

Multi Dimensional Relative Vulnerability Assessment of Santhal Pargana, Jharkhand, India

The concept of vulnerability is multifaceted, encompassing a range of socio-economic, environmental, and climatic elements that necessitate comprehensive analysis to fully grasp its implications for affected populations. The study employs a Fuzzy-AHP methodology to conduct a multi-dimensional relative vulnerability (Meteorological, Agricultural and Socio-economic) assessment in Santhal Pargana, located in Jharkhand. Notably, rainfall data from 1900 to 2020 revealed a downward trend. The findings of study indicate that Sahibganj exhibits the lowest vulnerability, while the Godda faces the highest risk. To validate the model's accuracy, we calculated the Area Under Curve (AUC), which yielded a value of 84.3, demonstrating the robustness of our assessment approach.

Understanding and monitoring vulnerability during pregnancy at population-level

Abstract Background Detecting and addressing vulnerability during pregnancy is important to optimize the first thousands days of children’s lives and prevent health inequities. We aimed to gain insight into vulnerability during pregnancy and determine the best data to predict vulnerability. Methods In the Netherlands, two studies were done using nationwide routinely collected data and self-reported Public Health Monitor-data. The first study utilized all data to identify classes of vulnerability among 4172 pregnant women through Latent Class Analysis. The second study predicted multidimensional vulnerability at population-level using solely routinely collected data first, and step-by-step incorporating self-reported data. Random Forest (RF) analysis was employed, and model performance was assessed using Area Under the Curve (AUC) and F1-measure. Results Five vulnerability-classes were found: ‘healthy and socioeconomically stable’, ‘high care utilization’, ‘socioeconomic vulnerability’, ‘psychosocial vulnerability’, and ‘multidimensional vulnerability’. Women in the ‘multidimensional vulnerability’-class shared multiple risk factors across domains and lacked protective factors. They more often had adverse outcomes such as premature birth. In the next study, the initial RF-model achieved an AUC of 0.98 in distinguishing multidimensional vulnerability, with an F1-measure of 0.70. Adding self-reported data improved model performance. Strong predictors were self-reported health, socioeconomic characteristics and healthcare utilization. Conclusions Several vulnerability classes can be distinguished among pregnant women. The co-existence of risk factors and lack of protective factors leads to more adverse outcomes. Effective public health strategies should include both medical and social care and support. Next, it seems possible to predict multidimensional vulnerability using data that is readily available, providing a foundation for longitudinal monitoring and policy formulation. Key messages • Considering the combination of both social risk and protective factors related to vulnerability during pregnancy is necessary. • Routinely collected data could provide insight in the prevalence, geographical distribution and trends in multidimensional vulnerability during pregnancy at population-level.

Multi-hazard, multidimensional disaster risk validation in selangor’s three urban districts, Malaysia

Considering the increasing impact of natural hazard-related disasters in Malaysia, understanding and evaluating integrated disaster risk must consider multi-hazard and multidimensional vulnerability at the local level, particularly in developing industrial nations like Malaysia. Therefore, this study proposes an improved methodology for conducting an integrated disaster risk assessment index (IDRI) mapping to measure disaster risk within local administrative boundaries in Malaysia. In this study, multi-hazard spatial overlapping combined two common hazards in Malaysia, which are floods and landslides. This study used multidimensional vulnerability, which encompasses six dimensions, 16 subdimensions, and 54 indicators. Researchers applied this approach in three urban districts of Selangor, Malaysia: Sepang, Kuala Langat, and Hulu Langat, which are located within the Langat River catchment and consist of 17 subdistricts. Overall, 32.9% of the total study area was found to be at risk, with 4.3% in the very high-risk area. In comparison with the latest flood events in 2021, the IDRI components were highly correlated with disaster impact. In conclusion, the contribution of this study provides a novel perspective on disaster risk assessment by addressing several types of hazards and multidimensional vulnerability, as compared to the previous methodology focusing on a single hazard and a physical vulnerability factor.

Assessing energy vulnerability in Colombia using a multidimensional index

Energy vulnerability studies are conducted to identify and address the multidimensional causes of energy problems of a territory. Colombia faces substantial energy challenges, including sustained excess demand, slow supply expansion, rising tariffs, flow intermittency and power instability. It is a tropical developing country undergoing an energy transition and characterized by significant cultural, geographical, and demographic diversity. This article assesses the energy vulnerability of Colombia's 32 departments and its capital district through a Multidimensional Energy Vulnerability Index (MEVI). The MEVI is a measure ranging from 0 to 1 that evaluates energy vulnerability through 12 indicators across four dimensions: social, environmental, technical, and economic. To construct the index, a multivariate analysis using Cronbach's Alpha was conducted, and the min-max normalization method was employed. Additionally, a specific weighting system of the dimensions accompanied by an additive aggregation function was utilized to synthesize the various indicators into a unified index. Furthermore, a sensitivity analysis was performed to assess the robustness of the index, incorporating variations in key inputs such as the weighting scheme and data processing methods. The mean energy vulnerability score was 0.6, indicating that the departments of Colombia do not have extreme energy vulnerability. The territories with the highest energy vulnerability include the Departments of Vaupés, Guainía, Vichada, and Amazonas. In these cases, effective government policy is necessary to provide more energy security, which requires improvements across nearly all indicators involved in the calculation of the index. A discussion on the policies that could be implemented is presented in the document.

Vulnerability assessment and evolution analysis of Beijing's Urban Rail Transit Network

With the development of urban rail transit system, the complexity of the network intensifies, and its vulnerability shifts correspondingly. Understanding the characteristics and evolution of network vulnerability, as well as identifying developmental patterns, enables more scientific network planning. Current researches on network vulnerability predominantly focus on the static vulnerability assessment of existing networks, with limited studies on vulnerability evolution. This paper divides the topological evolution of the Beijing Urban Rail Transit Network (BURTN) from 2000 to 2020 into Formation and Improvement stages using the K-means++ method. By constructing a multidimensional vulnerability assessment model that considers node degree uniformity, network efficiency, and connectivity, the vulnerability evolution characteristics and patterns of BURTN are explored in cases of both Single-station failures and Multi-station consecutive failures (including random and intentional failures). Furthermore, the evolutionary relationship between network vulnerability and network structure is explored using the Ridge regression model. Calculations reveal that in the case of Single-station failures, during the Formation stage, the proportion of highly vulnerable stations (HVS) and the impact of each station failure on network performance decrease significantly, by 69.36 % and 67.67 %, respectively. During the Improvement stage, the proportion of HVS decreases significantly, while the impact of each station failure on network performance decreases slightly, by 79.10 % and 37.04 %, respectively. In the case of Multi-station consecutive failures, during the Formation stage, the network’s ability to cope with both random and intentional failures decreases, with the percentage of network nodes removed at the collapse state decreasing by 24.95 % and 11.12 %, respectively. During the Improvement stage, the network’s ability to cope with random failures remains stable, while its ability to cope with intentional failures decreases. This study helps to understand vulnerability from an evolutionary perspective and provides practical strategies for reducing vulnerability.

Adapting to Adversity: Unraveling the nexus between vulnerability and well-being in coastal Bangladesh

As climate change intensifies multi-dimensional vulnerabilities in coastal Bangladesh, understanding its impact on household well-being becomes crucial. This study empirically investigates how climatic extreme event-triggered (super-cyclone Amphan) vulnerabilities affect at-risk households' well-being in the Southwestern coastal zone. Deploying a systematic random sampling procedure, we collected data from 747 households using a structured questionnaire from seven disaster-affected Unions (i.e., sub-districts) from three districts, namely Khulna, Satkhira, and Bagerhat. The findings reveal that diverse demographic, socioeconomic, sociopolitical, disaster-preparedness, environmental, and locational factors influence multi-dimensional vulnerabilities in the study areas. Notably, these vulnerabilities significantly affected post-cyclone well-being, measured by consumption expenditure. Acquaintances with local political leaders (OR = 6.028, p < 0.05), participation in disaster-preparedness training (OR = 2.63, p < 0.01), and timely evacuation decisions (OR = 2.57, p < 0.01) emerged as key determinants of better household well-being following cyclone-disaster. Intriguingly, households with stronger political connections exhibited higher participation in disaster-preparedness training (z = 4.60, p < 0.000) and evacuation rates to safe havens (Chi2(1) = 5.14, p < 0.02). The study proposes three policy recommendations based on these empirical insights, paving the way for enhanced resilience and adaptive capacity in coastal Bangladesh communities facing the challenges of climate change.

Beyond Multidimensional Vulnerability Approach: A Triple Network Notion for Urban Cohesion in At-Risk Neighborhoods of Jaen’s Historic Center

Today’s cities need more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of a diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabric. This study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and the formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Paternalistic state care and the dynamic of COVID-19 pandemic governance in Jakarta's rented social housing

The COVID-19 pandemic has reignited debates on care, exposing the vital role of social reproduction despite its ongoing devaluation. Recent studies underscore the urban marginal's multidimensional vulnerabilities during the pandemic, coupled with inadequate state support and excessive policing amid their disproportionate engagements in low-paying care work essential to the city.This study extends the literature by exploring the discourse of care amid the pandemic in Jakarta's rented social housing (rusunawa), Indonesia. As a state-owned settlement hosting displaced residents from informal settlements, rusunawa represents a new form of urban marginality. Based on an ethnography of three rusunawa between 2019 and 2021, I argue that paternalism defines the state's vision and operation of rusunawa. By portraying the residents as vulnerable yet ignorant, the state justifies the combination of disciplines and supports in ‘caring’ for them.The continued paternalistic care during the pandemic, with an intensification of disciplines and assistance, ameliorated the residents' antagonism against the state. Yet, access to state relief programs still hinged upon the residents' invocation of vulnerabilities and personal connection with rusunawa management. Lastly, I demonstrate the residents' intractable desire for a state that embodies a powerful yet nurturing parent, shaping their assessment of the quality of state care.

The relevance of development policies to confront crisis situations: World Bank’s early response to Covid-19

Evaluating the relevance of development policies is a complex task as many different dimensions must be considered. By focusing on one particular, quantifiable aspect of relevance, this study proposes a new method for generating data-driven evidence that can be used both for assessing the relevance of international development policies ex post, and for guiding decisions about future strategic priorities. For this purpose, relevance is defined as the match between (i) the types and scopes of support provided and (ii) the types and scopes of support most needed in a given context, according to measurable indicators (proxies). The latter is operationalized using a multidimensional vulnerability score constructed based on a set of empirical indicators commonly argued to proxy vulnerability to shocks. Comparing the vulnerability score with the sector-specific allocation of support yields two empirical measures of relevance, one at the country level and one at the sector level within each country. The proposed method is then applied to evaluate the relevance of the World Bank Group’s early response to Covid-19 across 133 countries. At the same time, many of the modeling insights are more broadly applicable and may also be useful in informing evaluations of development policies beyond the specific application considered here.

Unpacking the energy crisis impact with a multidimensional vulnerability index: A granular analysis of the Spanish case

Unpacking the energy crisis impact with a multidimensional vulnerability index: A granular analysis of the Spanish case

Beyond residential segregation: Mapping Chilean social housing project residents’ vulnerability

Residential segregation is an important challenge in Latin America, particularly since its effects on quality of life and access to urban opportunities are increasingly urgent on the public agenda. Segregation has not only arisen in the region due to the market, but also directly due to the State, which has promoted it through creating social housing along urban peripheries, far from job opportunities and urban equipment. This has increased conditions of vulnerability, although such conditions are not homogenously distributed in the territory. The present article proposes a multidimensional vulnerability index for social housing project residents, which apart from the socioeconomic indicator used in official measurements also applies two special indicators: (1) spatial mismatch from employment centers, and (2) an indicator for accessibility to public services and equipment. Unlike the commonly used one-dimensional indicator, the proposed index produces clearer discrimination of the vulnerability levels faced by social housing residents, allowing for better public policy design and improved public resource focusing.

Compounding impacts of COVID-19, cyclone and price crash on vanilla farmers' food security and natural resource use.

The intersection of the COVID-19 pandemic with other crises can amplify vulnerabilities and push communities further into poverty. In low-income countries, the dual impacts of COVID-19 and extreme weather events, along with multidimensional poverty and structural vulnerabilities in agriculture can decimate farmer livelihoods. This study aims to understand the effects of individual and compounding crises (COVID-19, cyclones, and vanilla price collapse) on smallholder vanilla farmers and local coping strategies in Madagascar, one of the world's largest vanilla producers and poorest countries. We used semi-structured and scenario-based interviews across two case study villages with contrasting enforcement of forest regulations. We found that the impact of the pandemic, combined with the cyclone event, disrupted livelihoods, resulting in income losses and food security challenges that exacerbated farmer vulnerabilities. Sixty eight percent of households reported crop losses due to strong winds and heavy rainfall brought by cyclone Enawo in 2017. The COVID-19 outbreak struck the region just as the residents were recovering from the effects of the cyclone. COVID-19-related travel restrictions in the aftermath of the cyclone took a substantial economic toll, with 54.1% of respondents experiencing a decline in earnings, and 17% facing a total loss of income due to the imposed lockdown. The decline in vanilla prices at the onset of 2020 had a far-reaching additional impact, affecting not only farmers but also residents who rely on other sources of income. Local communities reported using the forest resources more frequently as a safety net during crises in the village with more lenient regulations. This study underscores the importance of understanding the interconnectedness and compounding impacts of cascading crises on food security and natural resource use. We highlight the need for a comprehensive approach to increasing farmer resilience, particularly for those reliant on global market crops such as vanilla.

Municipal Evolution of the levels of Multidimensional Social Vulnerability in Guatemala (2022 to 2018)

Municipal Evolution of the levels of Multidimensional Social Vulnerability in Guatemala (2022 to 2018)

Dynamic assessment of postdisaster road network vulnerability using crowdsourced traffic data

Accurate identification of the spatial and temporal dynamic impacts of disasters on road networks is crucial for making informed decisions regarding postdisaster emergency response and recovery. In this paper, we propose a multidimensional vulnerability assessment framework that utilizes time series crowdsourced data. The framework enables a spatiotemporal analysis of traffic flows at the link level, allowing us to identify the primary factors that contribute to vulnerability after a disaster. The results show that there is a significant variation in link vulnerability over time, with the overall network gradually returning to a normal state. We also observe a global correlation in link vulnerability across the spatial aspect, although the autocorrelation effect is only present among directly contiguous links. Furthermore, metrics affecting link vulnerability varied during different periods of response. Graph-based metrics of road network structure, population density, and road type are key factors influencing postearthquake vulnerability.

The effects of equalization of regional basic public services on multidimensional vulnerability: evidence from China

ABSTRACT Based on the four waves of micro panel data from the China Family Panel Studies (CFPS), this study uses a two-way fixed effect model to analyse the impact of equalization of regional basic public services on the multidimensional vulnerability of families and its mechanism. The main findings of this study are as follows, firstly, regional basic public services and its equalization can significantly alleviate the multidimensional vulnerability of families; Secondly, regional basic public services and its equalization can reduce the multidimensional vulnerability of families by improving the level of regional economic development; Thirdly, the impact of regional basic public services and its equalization on the multidimensional vulnerability of households vary significantly among different groups, urban and rural areas, and different regions.

Multidimensional assessment of agricultural drought vulnerability based on socioeconomic and biophysical indicators

Agricultural drought threatens Türkiye's food security and economy, revealing a lack of multidimensional provincial vulnerability studies. Therefore, the primary objective of this study is to evaluate Türkiye's vulnerability to drought utilizing a multidimensional strategy incorporating biophysical and socio-economic indicators. In this context, an initial step involved the development of a conceptual framework for drought vulnerability, drawing upon the Intergovernmental Panel on Climate Change recommended elements of exposure, sensitivity, and adaptive capacity. Subsequently, this conceptual framework was applied at the provincial level, encompassing parameters such as temperature, precipitation, soil characteristics, water resources, agricultural earnings, demographic traits, educational levels, innovation, insurance coverage, and road density.The Aridity Index was used as an indicator for drought exposure, representing the physical dimension of drought. Under the sensitivity component, a total of 14 variables were defined under the indicators of “soil”, “water and land resources”, “economy”, and “population”, while under the adaptive capacity component, a total of five variables were identified. The weights of these indicators and variables were determined based on expert opinions using the Analytic Hierarchy Process method. As a result, five different indices were obtained by combining the indicators: Exposure Index, Sensitivity Index, Adaptation Capacity Index, Potential Drought Impact Index, and Agricultural Drought Vulnerability Index. In addition, spatial distribution models of these indices were also generated. Research results showed that the climatic regions most exposed to drought are also the most vulnerable. The Central, Southeastern, and Eastern Anatolian regions constitute the regions where the most vulnerable provinces are concentrated spatially.

THE IMPORTANCE OF MULTIDIMENSIONAL VULNERABILITY ANALYSIS IN SUSTAINABLE DEVELOPMENT

The contemporary development discourse is largely concerned with mitigating vulnerabilities, building resilience, and achieving sustainability. The interconnection of the various factors involved in vulnerability, sustainability assessments, and resilience building necessitates a comprehensive analysis. However, bringing together these factors for a multidimensional analysis of vulnerability or sustainability poses significant challenges. Thus, it is imperative to establish a framework that combines multidimensional vulnerability and sustainability analysis to overcome vulnerabilities and achieve sustainable development. This article presents a framework integrating sustainability into multidimensional vulnerability analysis to establish sustainable intervention. Firstly, we review the key concepts and multidimensional frameworks of vulnerability analysis. Secondly, we discuss the various domains and drivers of vulnerabilities and the role of sustainability in analysing the impact of multidimensional vulnerability and framing sustainable intervention strategies. Lastly, we argue that mitigating vulnerability drivers is central to the preliminary framework, which can be achieved by aligning sustainable intervention strategies with the sustainability goals (SDGs).

Construction of a scale to assess multidimensional vulnerability to pesticides in horticultural production in the Food Region of Córdoba

Construction of a scale to assess multidimensional vulnerability to pesticides in horticultural production in the Food Region of Córdoba

Excluded despite their support - The perspectives of energy-poor households on their participation in the German energy transition narrative

EU policy documents pursue a win-win outcome for climate policies and the combatting of energy poverty. Yet current policies do not achieve the full participation of the energy-poor in regard to energy transitions. Structural factors like welfare policy, housing- and energy-market mechanisms, and tenancy prevent the energy poor from benefitting from energy transitions. Based on document analyses and in-depth interviews with 35 German households, we describe how the energy poor perceive the sustainability narrative associated with the German energy transition. Being part of this narrative creates a sense of belonging, while being deprived of the opportunity manifests yet another dimension of social exclusion. We portray three household types: those supporting climate action and energy transition with limited possibility for participation beyond energy saving; indifferent households with low energy consumption due to financial precarity; and extremely overburdened households with (mental) health issues. All groups express support for energy transitions yet remain excluded by its policies that fail to account for multidimensional vulnerability and that remain restricted to either energy-saving or one-time relief measures, both of which quickly reach their limits, especially during energy crises. Highlighting the exclusion of these groups requires specifying that distributional justice debates to include access to measures designed to enhance participation in this narrative. Such measures would enable the fair distribution of coping mechanisms to manage rising energy prices and often determine whether households can contribute to climate action while maintaining the basic comforts of life. On a policy level, only a radical shift towards inclusive, democratic policy design can help overcome the exclusion.

Assessment of multidimensional drought vulnerability using exposure, sensitivity, and adaptive capacity components.

This study provides a method for analyzing the drought-vulnerability index (DVI) from a multidimensional perspective that includes biophysical and social aspects, considering the Intergovernmental Panel on Climate Change's (IPCC) assessment. The proposed method generates the "exposure index (EI)", "sensitivity index (SI)", and "adaptive capacity index (ACI)" components of the proposed DVI using nine sub-indicators and 29 proxy variables. By using it throughout all of Turkey's provinces, the performance of the developed index was evaluated. In this study, the decision matrices were built utilizing expert knowledge, and the weights of the indicators and variables were obtained by using the Analytical Hierarchy Process (AHP) technique. Moreover, the values of these four indices were classified as "very high, high, moderate, low, and very low," and their geographical distribution across the country was drawn, as well as relevant patterns retrieved. The study's major results show that 17 of the 81 provinces are classified as "very high," 16 as "high," 15 as "moderate," 17 as "low," and the remaining 16 as "very low" drought vulnerable. Another significant result is that the majority of people in the country's south, center, and southeast rely on agriculture and are thus more vulnerable to drought due to socioeconomic underdevelopment in those regions.