Identifying Indicators Contributing to the Social Vulnerability Index via a Scoping Review

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper is well-written and scientifically sound. It focuses on the Social Vulnerability Index (SVI), a crucial tool for assessing how societal characteristics influence community resilience to extreme events, such as natural disasters and public health crises. The use of the PRISMA-ScR methodology for conducting a scoping review is highly appropriate for evaluating existing literature and identifying indicators relevant to SVI development. While the paper does not represent a significant methodological advancement, this type of research and its findings are in high demand within the research community focused on vulnerability studies. I have no additional comments to provide.

Author Response

Comments 1: 
The paper is well-written and scientifically sound. It focuses on the Social Vulnerability Index (SVI), a crucial tool for assessing how societal characteristics influence community resilience to extreme events, such as natural disasters and public health crises. The use of the PRISMA-ScR methodology for conducting a scoping review is highly appropriate for evaluating existing literature and identifying indicators relevant to SVI development. While the paper does not represent a significant methodological advancement, this type of research and its findings are in high demand within the research community focused on vulnerability studies. I have no additional comments to provide.

Response 1:
Thank you for your kind and encouraging comments on our manuscript. We are delighted that our work on the Social Vulnerability Index (SVI) and the application of the PRISMA-ScR methodology was considered both scientifically sound and relevant to the research community. Your recognition of the importance and demand for this type of research is truly motivating. We sincerely appreciate your support and would gladly consider any further suggestions or insights you might have in the future.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors,

Your paper is a very interesting research, and I have some suggestions for you:

The SVI, while focused on disasters, has broader uses in health, education, urban planning, and socio-economic issues. Applying it to public health could identify areas vulnerable to pandemics, and in education, it could highlight gaps in literacy and schooling. This would offer a fuller framework for addressing societal challenges.

To improve comparability, a standardized framework for selecting indicators is essential. A core set of indicators, with regional flexibility, would make studies more consistent and replicable.

Crime, political participation, and environmental factors need more focus. Crime impacts community stability, political engagement shows influence over policies, and environmental conditions, like air quality, matter in assessing vulnerability, especially in disaster-prone regions.

The exclusion of predictive studies should be better justified. These studies can offer valuable insights into future vulnerabilities, and a clearer rationale for their exclusion would improve credibility.

Qualitative methods and alternative approaches like AHP or Delphi could complement PCA’s limitations, offering context-specific insights and balancing statistical rigor with local relevance.

Most studies focus on regions like the US, China, and India, limiting global applicability. Expanding the geographic scope with Balkan region (for example Serbia) would provide a more diverse understanding of vulnerability.

SVI studies tend to focus on static factors, but vulnerabilities are dynamic and context-dependent. Temporal analyses, especially in the face of urbanization or climate change, should be prioritized.

While quantitative data is valuable, qualitative insights through interviews and case studies can provide richer context that numbers alone can't capture.

The paper lacks a detailed discussion on policy implications. It should focus more on how findings could inform policies related to disaster risk, urban planning, or social welfare.

Interconnections between domains like education, income, and healthcare should be examined. Understanding how these factors interact would offer a more complete view of vulnerability.

The study does not address data gaps adequately. Discussing solutions, such as improving local data collection, would strengthen the findings. Governance factors, such as corruption and institutional capacity, should also be included, as they affect vulnerability outcomes.

Warm regards

Author Response

Comments 1: The SVI, while focused on disasters, has broader uses in health, education, urban planning, and socio-economic issues. Applying it to public health could identify areas vulnerable to pandemics, and in education, it could highlight gaps in literacy and schooling. This would offer a fuller framework for addressing societal challenges.
Response 1: We appreciate the reviewer’s insightful suggestion regarding the broader applicability of the Social Vulnerability Index (SVI) beyond disaster-related contexts. In the revised manuscript, we have included an analysis of these potential applications. Specifically, we highlighted how the SVI can be utilized in public health to identify regions vulnerable to pandemics by mapping disparities in healthcare access and population density. Similarly, we discussed its potential to uncover gaps in literacy and schooling within the education sector, guiding interventions to reduce systemic inequities. Additionally, we explored the utility of the SVI in urban planning for equitable infrastructure development and socio-economic development, emphasizing its alignment with social equity and sustainability goals. These additions are included in the Discussion section to provide a more comprehensive perspective on the versatility of the SVI, as suggested by the reviewer. While our study primarily focuses on disaster-related contexts, this expanded discussion acknowledges the SVI’s broader relevance and underscores the importance of considering diverse applications in future research. (p. 21)

 

Comments 2: To improve comparability, a standardized framework for selecting indicators is essential. A core set of indicators, with regional flexibility, would make studies more consistent and replicable.
Response 2: We appreciate the reviewer’s insightful suggestion regarding the development of a standardized framework for indicator selection. To address this, we have expanded the discussion by highlighting the importance of such a framework. Specifically, we emphasize the need for a core set of universally applicable indicators—such as age, income levels, and educational attainment—combined with region-specific variables that account for local socio-economic and environmental contexts. This approach, as noted in the revised discussion, would enhance the comparability and replicability of SVI studies while preserving the flexibility needed for localized applications. The revised discussion further underscores the potential benefits of a standardized framework in broadening the applicability of SVI methodologies beyond traditional disaster-focused contexts, extending to areas such as urban planning, public health, and sustainable development. By integrating these elements, the framework would provide a robust foundation for addressing diverse socio-environmental challenges. (p. 19)

 

Comments 3: Crime, political participation, and environmental factors need more focus. Crime impacts community stability, political engagement shows influence over policies, and environmental conditions, like air quality, matter in assessing vulnerability, especially in disaster-prone regions.
Response 3: We appreciate the reviewer’s insightful comment regarding the need to focus on crime, political participation, and environmental factors. In response, we have revised the discussion section to incorporate an in-depth analysis of these underrepresented domains. Specifically, we addressed the importance of crime-related variables in assessing community stability and social cohesion, political participation as a critical indicator of institutional equity and resource distribution, and environmental factors such as air quality and proximity to green spaces in shaping vulnerability dynamics. These additions underscore the multidimensional nature of social vulnerability and highlight the need to integrate these domains into Social Vulnerability Index (SVI) calculations. The revised text emphasizes findings from the reviewed studies, which revealed limited inclusion of these domains in existing SVI methodologies. For example, we noted that only five studies included crime-related variables, five studies utilized political participation indicators, and three studies incorporated environmental factors. These findings were contextualized with examples from the literature to demonstrate their significance and relevance in improving SVI comprehensiveness. By addressing this comment, we aim to provide a more holistic discussion that aligns with the reviewer’s suggestion. Revisions can be found in the discussion section, where we expanded on the role of these domains in understanding social vulnerability and proposed their integration into future SVI frameworks. (pp. 16-17)

 

Comments 4: The exclusion of predictive studies should be better justified. These studies can offer valuable insights into future vulnerabilities, and a clearer rationale for their exclusion would improve credibility.
Response 4: We appreciate the reviewer’s thoughtful feedback regarding the exclusion of predictive studies and agree that these studies can offer valuable insights into future vulnerabilities and disaster preparedness. To address this, we have provided a clearer and more detailed justification for their exclusion in the revised manuscript.
While predictive studies are instrumental in modeling potential future scenarios and outcomes, their methodological emphasis differs from the primary focus of this review. Specifically, predictive studies often rely on assumptions, temporal projections, and hypothetical scenarios, which introduce significant uncertainties. These elements, while valuable for forecasting, do not align with this study’s aim of systematically examining and analyzing social variables within the Social Vulnerability Index (SVI) framework. Furthermore, the integration of external variables, such as economic or environmental forecasts, in predictive studies can obscure the distinct roles and contributions of social indicators, complicating the systematic analysis required to meet the objectives of this review.
To maintain the clarity and relevance of this review, we have focused instead on studies that explore correlations between SVI and other phenomena. Unlike predictive studies, correlation studies do not attempt to forecast specific outcomes but rather investigate relationships among variables. These studies align closely with the goals of this review, as they provide actionable insights into how social variables interact within the SVI framework while preserving methodological transparency and reliability.
We believe that this revised explanation provides a stronger rationale for the exclusion of predictive studies and ensures that the scope of this review remains consistent with its objectives. Please refer to the revised section in the manuscript for further details (pp. 5-6).

 

Comments 5: Qualitative methods and alternative approaches like AHP or Delphi could complement PCA’s limitations, offering context-specific insights and balancing statistical rigor with local relevance.
Response 5: Thank you for this insightful comment. In response, we have expanded the discussion section to include a detailed examination of how qualitative methods and alternative approaches, such as the Analytic Hierarchy Process (AHP) and Delphi method, can complement the limitations of PCA in SVI construction. These methods allow for the integration of expert opinions and stakeholder input, enabling context-specific indicator selection and variable weighting.
Specifically, we highlighted that the Delphi method facilitates structured communication among experts to build consensus on region-specific indicators, while the AHP prioritizes variables based on their relative importance, addressing subjectivity in weighting. These approaches offer valuable tools for addressing the interpretative challenges of purely statistical methods and enhancing the practical relevance of SVI calculations, as outlined in the revised discussion section.
This addition underscores the importance of diversifying methodological tools in SVI research to improve adaptability and accuracy across diverse contexts. (p. 14)

 

Comments 6: Most studies focus on regions like the US, China, and India, limiting global applicability. Expanding the geographic scope with Balkan region (for example Serbia) would provide a more diverse understanding of vulnerability.
Response 6: We thank the reviewer for highlighting the limited geographic scope of our study and the importance of expanding coverage to underrepresented regions such as the Balkans. As noted in the revised Discussion section, this limitation stems from the linguistic constraints applied during our literature search, which restricted the analysis to English and Korean publications. Consequently, the geographic focus was naturally skewed toward regions like the United States, China, and India, where research is more commonly published in these languages. While this limitation reflects the scope of the current study, we agree with the reviewer that including research from regions such as the Balkans, South America, and Africa could provide a more diverse and comprehensive understanding of social vulnerability. To address this, we have emphasized the need for future research to broaden eligibility criteria, integrate multilingual resources, and employ translation technologies to include insights from a wider range of geographic and socio-political contexts. (pp. 21-22)

 

Comments 7: SVI studies tend to focus on static factors, but vulnerabilities are dynamic and context-dependent. Temporal analyses, especially in the face of urbanization or climate change, should be prioritized.
Response 7: We thank the reviewer for highlighting this critical limitation in Social Vulnerability Index (SVI) research. As noted in the revised Discussion section, many SVI studies indeed rely on static factors, such as demographic and socio-economic indicators, which do not fully capture the dynamic and context-dependent nature of vulnerabilities. This limitation reflects the inherent challenge of accounting for temporal and spatial changes, such as urbanization, climate change, and migration patterns, within existing SVI methodologies.
While our review acknowledges this gap, we also discussed the potential benefits of incorporating temporal analyses into future SVI research. For example, longitudinal studies and time-series data could provide valuable insights into how vulnerabilities evolve over time in response to socio-environmental transformations. Additionally, advancements in geospatial technologies, such as satellite imagery and GIS-based temporal mapping, could support these dynamic approaches. However, addressing this limitation was beyond the scope of the current review, as it primarily focuses on the static methodologies employed in existing studies.
We agree with the reviewer that prioritizing temporal analyses in future research would significantly enhance the relevance and applicability of SVI studies. By moving beyond static snapshots, future work could offer a more comprehensive understanding of vulnerabilities, particularly in the context of rapidly changing global challenges. (p. 22)

 

Comments 8: While quantitative data is valuable, qualitative insights through interviews and case studies can provide richer context that numbers alone can't capture.
Response 8: We thank the reviewer for highlighting the importance of qualitative insights in complementing quantitative data for a more comprehensive understanding of social vulnerability. In the revised Discussion section, we acknowledged this limitation and explained on the exclusion of qualitative studies, such as interviews and case studies, from our review process. As noted in revised discussion section, this decision was guided by the need to maintain consistency and comparability across the studies included in the review. However, we recognize that this exclusion inherently limits the ability to capture context-specific insights into systemic inequities and localized challenges.
Recognizing this gap, we emphasized that future research could benefit from adopting mixed-methods approaches. By complementing quantitative data with qualitative methods, such as case studies or participatory mapping, researchers could better understand factors like governance quality, institutional capacity, and regional disparities, which significantly influence vulnerability outcomes. Additionally, emerging methodologies, such as participatory mapping, offer valuable opportunities for integrating qualitative insights into SVI assessments, which could broaden the understanding of social vulnerability across diverse contexts.
While the scope of the current review did not allow for the inclusion of qualitative studies, we agree that addressing this gap is essential for advancing the field. Future research could leverage mixed-methods designs to provide a more holistic and multidimensional understanding of vulnerabilities, supporting the development of more targeted and equitable policy interventions. (p. 22)

 

Comments 9: The paper lacks a detailed discussion on policy implications. It should focus more on how findings could inform policies related to disaster risk, urban planning, or social welfare.
Response 9: We appreciate the reviewer’s valuable feedback regarding the need to elaborate on policy implications. In response, we have revised the discussion section to explicitly connect our findings to actionable policy measures in disaster risk reduction, urban planning, and social welfare. 
The discussion now highlights how the identification of key variables, such as age, education, and income inequality, can support targeted interventions in disaster preparedness and resource allocation. For example, mapping socially vulnerable regions using these indicators enables policymakers to prioritize high-risk populations and regions, improving the efficiency and equity of disaster response measures. 
Additionally, the discussion emphasizes the potential of incorporating underrepresented environmental indicators, such as air quality and access to green spaces, into social vulnerability assessments. These variables provide critical insights for urban planning initiatives, enabling the design of sustainable and inclusive environments that address environmental inequalities while fostering resilience among vulnerable populations. 
Finally, the revised discussion explores the intersection of education, gender, and age disparities as critical dimensions of vulnerability in the context of social welfare. It highlights the importance of addressing them through targeted policies that can reduce vulnerabilities among marginalized groups. Additionally, the discussion emphasizes the potential value of incorporating political participation variables into SVI methodologies. By strengthening civic engagement, promoting equitable resource distribution, and enhancing representation in decision-making processes, policymakers can work toward more robust institutional support systems. These revisions aim to provide a clearer connection between the study’s findings and their potential implications for policy development, as detailed on (pp. 19-20).

 

Comments 10: Interconnections between domains like education, income, and healthcare should be examined. Understanding how these factors interact would offer a more complete view of vulnerability.
Response 10: We appreciate the reviewer’s suggestion to examine the interconnections between domains like education, income, and healthcare, as this perspective is critical for understanding the complexities of social vulnerability. In response, we have expanded the discussion section to address how these domains function as interconnected systems that collectively shape vulnerability. 
We discuss how limited access to education restricts employment opportunities, leading to income disparities that hinder access to essential services such as healthcare and housing. Income inequality intersects with other domains like housing and mobility, illustrating how low-income households often reside in areas with inadequate infrastructure, compounding health risks and perpetuating cycles of vulnerability. Furthermore, healthcare access is influenced by intersections with gender, ethnicity, and social support systems, as marginalized groups face systemic barriers in navigating healthcare resources effectively. Environmental factors and crime further amplify vulnerabilities, with high-crime regions often experiencing reduced investment in schools and healthcare facilities, exacerbating systemic inequalities. 
To address these insights holistically, we emphasize the importance of adopting a multidimensional approach to social vulnerability assessments. By understanding the interconnections between key domains such as education, income, and healthcare, and recognizing how disparities in these areas interact, we can better identify and address compounded vulnerabilities. For instance, targeted interventions that address educational disparities could simultaneously improve income stability and healthcare access, reducing vulnerability across multiple dimensions. Recognizing these interdependencies ensures more effective interventions that build resilience and address systemic inequalities. 
We believe these revisions adequately address the reviewer’s comment and strengthen the manuscript by emphasizing the necessity of a holistic and interconnected approach to social vulnerability assessments. (pp. 20-21)

 

Comments 11: The study does not address data gaps adequately. Discussing solutions, such as improving local data collection, would strengthen the findings. Governance factors, such as corruption and institutional capacity, should also be included, as they affect vulnerability outcomes.
Response 11: We appreciate the reviewer’s insightful comment regarding the importance of addressing data gaps and incorporating governance factors into Social Vulnerability Index (SVI) research. In the revised Discussion section, we acknowledged the significant variability in the indicators and data sources used in the 72 selected studies, which underscores notable data gaps across geographic and socio-economic contexts. We also highlighted the disproportionate reliance on datasets from regions with well-established research infrastructure, such as the United States and Europe, and the underrepresentation of data from regions like Africa, South America, and Southeast Asia. 
While this imbalance reflects the limitations of existing datasets, we discussed the critical need for enhancing local data collection efforts. For example, participatory mapping and community-based surveys could be valuable tools for capturing region-specific indicators, including governance-related factors such as corruption and institutional capacity, which significantly influence vulnerability outcomes but are often overlooked in existing SVI frameworks. Additionally, we emphasized the potential of integrating qualitative insights into SVI methodologies to better account for systemic inequities and localized challenges. 
We agree with the reviewer that addressing these gaps is essential for advancing the field of SVI research. To this end, we proposed that future studies prioritize developing standardized and adaptable data collection practices that reflect diverse socio-cultural contexts and environmental conditions. These practices would help ensure that SVI applications are both methodologically robust and globally inclusive, thereby improving their capacity to inform equitable and effective policy interventions. (pp. 22-23)

Reviewer 3 Report

Comments and Suggestions for Authors

Social vulnerability measures the vulnerability of a society to external shocks. Based on the method of literature review, the author systematically combs the existing literature on social vulnerability, systematically reviews the indicators and commonly used methods of measuring social vulnerability, and puts forward some suggestions. On the whole, this is a topic worthy of attention, but there are still some deficiencies in some aspects. Specific comments are as follows:

       (1) The introduction section is so redundant that there is no need to do so much introduction. It is suggested to make significant deletion and rewriting, focusing on the importance, urgency and innovation of the whole research, there is no need to do too much expansion of who did what.

       (2) The whole research should have a comprehensive theoretical analysis framework, and make some necessary and systematic review of the theories involved in social vulnerability. Without a review of the theoretical analysis framework, the index system and research methods of social vulnerability will be introduced later, which is of no great significance.

       (3) The analysis process is relatively simple and should have a goal or anchor point for analysis. At the same time, it is not clear that the author's combing of social vulnerability has anything to do with land. This may not fit the direction of the Land Journal.

Author Response

Comments 1: The introduction section is so redundant that there is no need to do so much introduction. It is suggested to make significant deletion and rewriting, focusing on the importance, urgency and innovation of the whole research, there is no need to do too much expansion of who did what.
Response 1: Thank you for your valuable feedback regarding the redundancy in the introduction section. We appreciate the suggestion to streamline the content and focus on the importance, urgency, and innovation of the research while avoiding excessive expansion on who did what. In response to your comment, we have thoroughly revised the introduction to ensure clarity and conciseness.
The revised introduction now highlights the significance of social vulnerability in the context of disaster risk reduction and sustainable land management. We emphasize the urgency of addressing disparities in vulnerability, which directly impact disaster preparedness and mitigation efforts. The introduction also underscores the innovation of this study by focusing on the critical issue of indicator selection, identified as the most pressing challenge in Social Vulnerability Index (SVI) research. Additionally, the revised section provides a succinct overview of existing methodologies, such as the SoVI framework, while minimizing detailed accounts of specific researchers' contributions.
This streamlined approach ensures that the introduction remains focused on the study's core objectives, avoiding unnecessary redundancies. By aligning the revised introduction with your suggestions, we believe the manuscript now better communicates the importance, urgency, and novelty of the research.
We hope this revision addresses your concerns effectively, and we thank you once again for your constructive feedback. (pp. 1–3)

 

Comments 2: The whole research should have a comprehensive theoretical analysis framework, and make some necessary and systematic review of the theories involved in social vulnerability. Without a review of the theoretical analysis framework, the index system and research methods of social vulnerability will be introduced later, which is of no great significance.
Response 2: We express our sincere gratitude to the reviewer for emphasizing the significance of incorporating a comprehensive theoretical analytical framework. We concur that conducting a systematic review of the theories that inform social vulnerability is essential for augmenting the manuscript's depth and relevance. In response to this valuable feedback, we have introduced a new section situated between the introduction and methodology, which offers an in-depth examination of the key theoretical foundations pertinent to social vulnerability research. 
This newly added section elaborates on foundational concepts, including Blaikie et al. (1994)’s Pressure and Release (PAR) model and Cutter et al. (2003)’s Social Vulnerability Index (SoVI). The PAR model is particularly noteworthy for its elucidation of the interactions among root causes, dynamic pressures, and unsafe conditions that contribute to vulnerability. Conversely, the SoVI framework illustrates the application of Principal Component Analysis (PCA) in synthesizing various social indicators into a cohesive index. These theoretical perspectives provide essential context for comprehending the methodological approaches and challenges addressed in the study. 
Furthermore, the section highlights critical issues such as indicator selection and methodological limitations, underscoring the necessity for a diverse and contextually relevant set of indicators in vulnerability assessments. By integrating the theoretical and methodological dimensions of the research, the newly added framework not only enhances the manuscript's conceptual rigor but also establishes a coherent foundation for the scoping review and subsequent analyses. 
We believe that this revision significantly enhances the manuscript by addressing the reviewer’s concerns and improving the overall comprehensiveness and academic contribution of the study. We appreciate this constructive feedback, which has been instrumental in refining our work. (pp. 3-4)

 

Comments 3: The analysis process is relatively simple and should have a goal or anchor point for analysis. At the same time, it is not clear that the author's combing of social vulnerability has anything to do with land. This may not fit the direction of the Land Journal.
Response 3: Thank you for your thoughtful feedback. In response, we have thoroughly revised the introduction and key sections of the manuscript to address your concerns. First, to enhance clarity and focus, we have incorporated a new paragraph at the end of the introduction that explicitly outlines the key limitations in Social Vulnerability Index (SVI) research and how this study seeks to address them. Specifically, the revised introduction highlights the critical issue of indicator selection as the most pressing challenge in SVI research. It explains how this study uses a systematic scoping review to identify common practices, gaps, and trends in indicator selection, ultimately providing a foundation for advancing SVI methodologies. By doing so, the study establishes a clear analytical goal: improving the inclusivity and contextual relevance of variable selection to enhance the reliability and applicability of SVI assessments. These revisions ensure that the introduction effectively conveys the objectives of the study and provides a clear context for its focus on addressing the limitations of existing SVI research. By clarifying the analytical goal, the revised introduction establishes a stronger foundation for the subsequent analysis and aligns the study’s purpose with the key challenges in social vulnerability assessments. (p. 3)
Additionally, to address your comment regarding the connection between social vulnerability and land, we have revised the Discussion and Conclusion sections to better emphasize the role of land-related variables in social vulnerability assessments and their practical applications in land-use planning and management. In the Discussion section, we included a detailed analysis of how specific land-related variables were utilized in the reviewed studies and how they contribute to actionable land-use strategies. For instance, Proportion of Built-Up Area is used to evaluate urbanization levels and infrastructure density, which directly inform zoning regulations and the integration of green infrastructure. Similarly, Road Density highlights disparities in transportation infrastructure, which impact mobility and connectivity in underserved regions, while Agricultural Land Use indicators provide insights into vulnerabilities associated with environmental degradation, emphasizing sustainable practices like crop diversification and soil conservation. These examples demonstrate the critical role of land-related variables in shaping region-specific land-use strategies.
In the Conclusion section, we further emphasized the practical implications of integrating land-related variables into social vulnerability assessments for sustainable land-use management. Variables such as Proportion of Built-Up Area, Road Density, and Agricultural Land Use offer actionable insights for addressing urban expansion, resource allocation, and regional disparities. We proposed that future research explore advanced methodologies, including geospatial analysis, to better capture the interplay between social vulnerabilities and land-use dynamics. 
We believe these revisions strengthen the manuscript by addressing both the analytical focus and its alignment with the journal’s scope. We are grateful for your constructive feedback, which has been instrumental in refining our work. Thank you for the opportunity to improve our manuscript. (pp. 3, 17-19, 23-24)

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

I have no other comments, thank you.