Trends and Gaps in Global Catastrophic Insurance Literature: A Bibliometric Review (2000–2024)

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It is to sketch the intellectual and thematic landscape of the field, identify its leading contributors, analyse the collaboration structure, mark geographic and thematic gaps, and provide future directions. Catastrophic insurance now becomes core in resilience-building and risk transfer in the face of increasing climate disasters, pandemics, and systemic risks. Design/Methodology/Approach - The data were extracted from the Scopus database using an adapted and well-constructed query search string. PRISMA-based inclusions and exclusions were applied to ensure quality and relevance. Bibliometric analysis was performed in VOSviewer for science mapping (co-authorship, co-citation, keyword co-occurrence), whereas Excel was used to visualize the trends. Performance analysis considered parameters in scientists, journals, institutions, and countries, looking for production and impact. Scientometric concepts such as the Lotka Law or the Bradford Law validated the author production and the journal concentration distribution, respectively. Findings – Catastrophic insurance (Lin et al., 2023 )research apparently diversified steadily, with alternating peak moments in 2015–2023, corresponding to global crises, stockpiles, and interests in disaster financing. However, contributions from geographically outside the realm of developed countries remain limited in attracting interest from vulnerable and low-income regions in the market. From the thematic viewpoint, the structure becomes evident: risk modelling, actuarial pricing, and economic assessment dominate, with a lack of representation for issues of public policy and governance, and technological innovations, such as AI, blockchain, or parametric insurance. The collaboration networks are scattered: isolated groups of authors work in their silos, thus contributing enterprisingly little to interdisciplinary integration. Originality/Value – Scientometric principles are applied methodically to the literature on catastrophic insurance in this bibliometric review for the first time. The study contextualizes insurance as a financial and governance mechanism and identifies intellectual trends through integrating quantitative bibliometric mapping with sociological theory (Beck's Risk Society). The review offers a well-organised research agenda on innovation, inclusivity, and interdisciplinarity. Catastrophic insurance Risk Disaster Climate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Changes in the radius of catastrophe and other dimensions of natural phenomena have made the global community aware of the necessity of having robust risk financing mechanisms. Insurance is the most apparent means of securing development during a catastrophe among all the market-financing mechanisms(Linnerooth-Bayer & Hochrainer-Stigler, 2015 ). This also includes insurance against catastrophe risks, which enhances resilience by enabling recovery and mitigating long-term socioeconomic disruption(Kousky, 2019 ). The discussion has evolved with the advent of urbanisation, environmental degradation, and climate change as global risks, on the design, governance, and implementation of insurance mechanisms that primarily cater towards private interests, while also being an instrument for the public good during large-scale disasters. During the past two decades, the researcher, policymaker, and insurance practitioner communities have been trying to understand how insurance systems respond to catastrophic risks, by whom they are governed, and what factors influence their performance. This includes institutional frameworks, pricing mechanisms, public-private partnerships, reinsurance, and other emerging tools, such as parametric insurance and AI-based risk modelling(Bhattacharya et al., 2025 ). However, despite all the growth in alliance literature, it has not produced a comprehensive bibliometric study. To fill this gap, we present a detailed bibliometric study with literature on catastrophe insurance from 2000 to 2024, leveraging Scopus-indexed publications and visualisation software such as VOS viewer. We mapped the intellectual structure of the catastrophe insurance field to unveil the most significant authors, countries, institutions, and themes. This consists of analyzing co-authorships, keyword co-occurrences, citation networks, and thematic clusters to see how the field has evolved and where fragmentation or underrepresentation still exists. Moreover, the study reveals that global research on catastrophic insurance remains concentrated in high-income countries, primarily in the United States, the United Kingdom, and a few European countries. While low- and middle-income countries are most vulnerable to catastrophic events, they contribute very little to the literature. The findings from this bibliometric review can inform more balanced research agendas and foster wider academic collaborations in pursuit of inclusive and equitable climate adaptation, disaster preparedness, and financial resilience models. The paper sets out to answer some key questions: Who leads thinking on the research of catastrophic insurance? What are the dominant themes and new areas? How is knowledge geographically spread? Moreover, where are the main gaps? With this study, we seek to create a strategic knowledge map for this field and identify directions for future research, especially with the rise in worldwide catastrophes and systemic risks. Catastrophic risks threaten economies and societies worldwide, ranging from pandemics and geopolitical crises to climate-related disasters like hurricanes, floods, and wildfires(Botzen et al., 2019 ). An essential risk-financing tool that promotes recovery, lessens long-term socioeconomic upheaval, and redistributes losses among populations is insurance. In this context, catastrophic insurance is one of the most important tools for guaranteeing resilience. Catastrophic insurance has changed in practice and research over the last 20 years. Researchers have examined institutional frameworks, pricing mechanisms, parametric insurance, catastrophe bonds, public-private partnerships, and AI-driven risk modeling(Jia et al., 2025 ). Notwithstanding these advancements, the literature is still dispersed, focusing on wealthy nations and scant representation from vulnerable areas where the effects of disasters are most significant. The need for a thorough bibliometric analysis of the literature on catastrophic insurance is addressed in this paper. There are conceptual and narrative reviews, but no thorough scientometric mapping of the field that incorporates thematic clustering, collaboration mapping, and performance analysis has been done. In doing so, this research aims to respond to the following queries: Which writers, publications, and organizations are the most successful and significant in catastrophic insurance research? Which research themes are prevalent and developing? How is knowledge production geographically distributed, and what collaboration patterns exist? Regarding geography, interdisciplinarity, and thematic focus, where are the important research gaps? The study contributes by providing a strategic knowledge map that educates academics, decision-makers, and practitioners about the state of the field and its prospects for advancement. Objectives To identify the most productive and influential authors and countries in catastrophic insurance literature (2000–2025). To examine co-authorship and co-citation patterns for understanding collaborative structures. To map keyword clusters and uncover emerging research themes. To identify gaps in the literature regarding geographic coverage, thematic integration, and interdisciplinary collaboration. Literature Review (Hoeppe, 2016 )The insurance sector, particularly Munich Re, has monitored losses from natural disasters for four decades. According to these statistics, weather-related occurrences like storms and floods have tripled. This trend is exacerbated by socioeconomic variables such as population expansion and urbanization, but is also influenced by global warming. Extreme weather patterns are influenced by natural climate cycles, such as ENSO and AMO. Although it is challenging to attribute the cause of losses to global warming clearly, research shows that they continue to increase even after corrections. Insurers must modify rates to account for evolving risks as climate change develops. To avoid significant losses in the future, preemptive measures for climate protection and adaptation are crucial. (WEITZMAN, 2012 ) states that this study challenges conventional climate change economic models that rely on thin-tailed temperature distributions and a quadratic damage function. According to this argument, these models might significantly understate the possible welfare losses brought on by catastrophic climate outcomes. The study highlights the indirect benefits of stringent greenhouse gas (GHG) concentration objectives. These goals, which are supported by numerical examples, act as insurance against disastrous temperature increases. The results imply that conventional models do not adequately capture the gravity of high-impact, low-probability occurrences. Therefore, more substantial mitigation activities might be required in extreme uncertainty to reduce the probability of catastrophic climate-related impacts and achieve desired objectives. (Lo, 2013 ) examined how risk perception and social norms influence people's decisions to purchase flood insurance in cities in eastern Australia. Researchers polled 501 residents. They discovered that insurance adoption was significantly predicted by social norms rather than direct risk perception. Path analysis demonstrated how perceived social norms were shaped by risk perception, which indirectly affected insurance decisions. These results demonstrate the importance of socio-cultural context in responding to climate risk and show that social factors influence behavior. (Collier, 2008 ) explores "enactment" as a novel form of knowledge distinct from traditional social understandings, particularly in estimating catastrophic future risks. Through historical analysis of U.S. civil defence, natural hazard modelling, and terrorism risk assessment, the study highlights how expert practices construct risk as an object of governance. The article contributes to risk society debates by arguing that these approaches are not subjective anomalies but structured forms of knowledge that demand genealogical and institutional analysis within contemporary risk management frameworks. Since many agricultural risks are challenging to cover sustainably, (Hazell, 1992 ) criticizes multiple-risk crop insurance plans as expensive and generally ineffective. However, if regulatory restrictions are loosened, there may be opportunities to insure farm assets, rural health, and particular risks through private insurers. According to the study, which highlights the need for creative ways to ensure low-income rural households, straightforward insurance plans based on indices and connected to local meteorological data provide an affordable way to guard against devastating climate-related disasters like floods or droughts. (Ullah et al., 2015 ) used a risk matrix and the Equally Likely Certainty Equivalent approach to examine farmers' attitudes about risk and their perceptions of catastrophic risks. According to the report, most farmers are risk-averse and consider pests, floods, and excessive rains significant hazards. At the same time, access to formal information and credit increased risk perceptions, and socioeconomic factors such as age, education, income, land ownership, and informal credit availability influenced risk attitudes. Policymakers and insurers can use the data to develop focused agricultural risk management plans and assistance programs. (Panwar & Sen, 2019 ) re-evaluated the short- to medium-term economic impacts of natural disasters across 102 countries (1981–2015), using a system GMM approach. Analyzing floods, droughts, storms, and earthquakes, the study found that disaster impacts vary by sector, disaster type, and intensity. Crucially, the effects are more pronounced in developing nations. The findings emphasize the importance of ex-ante disaster risk financing tools—such as insurance and catastrophic bonds—for protecting assets and supporting sustainable development, particularly in vulnerable, low-income economies. In their analysis of the American insurance industry's reaction to the terrorist events of September 11, 2001, (Ericson & Doyle, 2004 ) showed how the government and insurers worked together to restructure markets to maintain terrorism coverage. The system made up for losses and exposed the sector's structural weakness. The study challenges Ulrich Beck's claims regarding disaster risk by demonstrating insurance's dual function of reducing uncertainty and creating new disparities and crises through market reactions. It emphasizes how essential insurers are in determining risk management and risk-based exclusion. (Chen et al., 2004 ) addressed the spatial mismatch between hazard data (raster-based) and exposure data (areal-based) in catastrophe loss estimation models. Using Sydney as a case study, they introduced a dissymmetric mapping approach to define occupied residential areas at risk. Their findings showed that finer-resolution exposure data significantly improved loss estimates for small-footprint hazards like hailstorms, while large-area events like earthquakes were less affected. The study highlights the importance of accurate spatial delineation in integrating environmental and socioeconomic data for more reliable catastrophe loss assessments. (Bougen, 2003 ) explores the rise of catastrophe-financing mechanisms involving reinsurance and capital markets as responses to growing concerns about the non-insurability of catastrophic events in contemporary risk society. The paper examines these mechanisms through two lenses: the fragility and sustainability of risk networks, and the innovative, market-driven approaches emerging from liberal governance. It highlights how these financial instruments reflect anxieties over catastrophic risk and capitalist creativity, offering valuable insights into evolving trajectories of risk management and the dynamics of insurability in a neoliberal context. (Botzen & Van Den Bergh, 2009 ) highlight how climate and socioeconomic changes contribute to increased frequency and intensity of catastrophic disasters. They support robust risk management plans incorporating risk-sharing, preventive, and mitigation techniques. In the context of low-probability, high-impact occurrences made worse by climate change, the study emphasizes the function of insurance and its significance in climate adaptation methods to lessen and manage the socioeconomic costs of disasters. (Grove, 2012 ) critically examines the Caribbean Catastrophic Risk Insurance Facility (CCRIF), arguing that it exemplifies the "financialization of disaster management." While CCRIF is promoted as a tool for climate adaptation through disaster recovery financing, Grove contends it reconfigures population adaptability into a securitized and market-leveraged risk. By blending risk pooling and parametric insurance, CCRIF enhances state infrastructure resilience while reinforcing state control and capital accumulation under the guise of climate risk management. In their analysis of the 2015 South Carolina flash flood, (Cutter et al., 2018 ) trace the evolution of flood risk over time and emphasize two central paradoxes: the local government conundrum and the safe development paradox. The paper uses archival evidence to show how low flood insurance uptake, bad zoning, and urban growth increased flood risk. The incident led to minor policy adjustments despite significant losses, particularly among affluent inhabitants, highlighting a lack of institutional learning and ongoing development-driven risk exposure. (Johnson, 2013 ) explores how catastrophe bonds transform geophysical, biological, and meteorological disasters into securitized, tradable risks within the insurance-linked securities (ILS) market. Through catastrophe modeling, contingent assets are generated from environmental and financial vulnerabilities. The paper highlights pension funds' dual role as investors in catastrophe bonds and sellers of longevity risk, illustrating the complex entanglement of labor, finance, and contingency. This reflects a broader shift toward securitized risk as an economic governance and accumulation modality. (Pita et al., 2015 ) comprehensively review building vulnerability assessment methods for hurricane catastrophe models, identifying five key approaches: past-loss data, enhanced damage data, heuristic, physics-based, and simulation models. The study critiques limitations of loss-only models and highlights the evolution toward engineering-informed and probabilistic simulations. It also examines post-disaster validation studies and mapping of model developments. The paper underscores prospects, including interior damage modeling and broader applications in catastrophe risk assessment. (Johnson, 2015 ) explores how the (re)insurance industry navigates climate change impacts as socio-ecological fixes for crises of overaccumulation. The paper argues that catastrophic losses during soft markets devalue capital, prompting recalibrations in catastrophe models and enabling capital reinvestment. Climate change uncertainty is framed not as an existential threat, but as a financial opportunity. The study critiques reliance on market mechanisms, warning of emerging "splintered protectionism" and uneven climate adaptation shaped by rising premiums and state-managed retreat. (CARDENAS et al., 2007 ) examine Mexico's pioneering 2006 initiative to transfer public-sector natural catastrophe risk to international markets via reinsurance and catastrophe bonds. Analyzing the decision-making process of Mexico's Ministry of Finance, the study uses IIASA's CATSIM model to evaluate risk-transfer options as public investment decisions. It highlights the importance of fiscal and institutional contexts, noting that while financial instruments ensure post-disaster liquidity, their high costs necessitate careful benefit-risk assessment, especially for developing countries. (Cohen et al., 2008 ) propose a novel preference representation model under risk that incorporates experience-dependent risk perception. By framing preferences around decision-experience pairs, the authors construct a dynamic choice model explaining temporal shifts in insurance demand. Through an illustrative example, the study demonstrates how this approach better captures behavioral changes in catastrophic risk insurance markets—patterns that standard models struggle to justify—highlighting the significance of past experiences in shaping risk-related decision-making. (TALBERTH et al., 2006 ) investigate how homeowners allocate resources between insurance and averting activities in response to catastrophic wildfire risk. Using contingent valuation and experimental data, the study finds that, contrary to expected utility theory, individuals often choose both strategies when nonmarket losses are significant. Factors such as amenity values, perceived risk, averting efficacy, and demographics influence willingness to pay and averting behavior. Additionally, wildfire risk zone information significantly shapes decision-making, supporting theoretical predictions. (Collier, 2014 ) explores the role of insurance in U.S. flood policy during the 1960s, highlighting how it functioned not only as a technical solution to disaster loss and compensation but also as a political technology. The study illustrates how insurance reshaped governance by redefining state-citizen responsibilities and reframing security through economic rationality. It challenges conventional narratives on risk and responsibility, offering critical insights into the neoliberal transformation of public policy and disaster management. METHODOLOGY Theoretical Framework The bibliometric analysis is grounded in scientometric principles , which provide tools for measuring and interpreting patterns in scholarly communication. Lotka's Law (1926) claimed a scientific productivity pattern to have been of the power-law type, where a few authors contributed the highest number of publications, whereas most others authored just one. Applying this law would give us an idea whether catastrophic insurance research follows the distributions of expected productivity or whether it is a more fragmented area. Bradford's Law (1934) explains journal concentration by stating that in any discipline, a few core journals publish most of the literature. This helps identify the journals that have had the most significant impact on catastrophic insurance, and determines whether the field is becoming consolidated or fragmented. According to Zipf's Law (1949) concerning keyword frequency, one may state that it is the recurrence of particular terms in written literature. The application of this principle reveals the most crucial thematic terms ("risk assessment," "disaster management") along with their clustering into intellectual subfields. The study is also informed by Beck's Risk Society theory (1992), which stresses the role of modern institutions in managing systemic unpredictable risks. Insurance is thus not a mere financial tool; it is a governance mechanism through which risk is framed, losses are redistributed, and choices are made regarding adaptation strategies. Complementing scientometric investigations with risk theory offers a richer interpretation of bibliometric research findings by situating them within broader socio-political contexts. Methodological Framework This study employs a structured quantitative bibliometric methodology, combined with performance analysis and science mapping, to identify global research trends in catastrophic insurance. Bibliometric analysis is particularly productive when employed in synthesising vast amounts of academic literature and showing hidden patterns of the production and dissemination of knowledge (Donthu et al., 2021 ). This study employs an exploratory design to address key questions about the most productive authors, institutions with the greatest influence, the most researched themes, and areas that have received little attention. The Scopus database, chosen primarily for its broad, multidisciplinary coverage and consistent indexing of peer-reviewed literature, provided the study's data. To gather documents published between 2000 and 2025, a carefully constructed query based on terms such as "natural hazard insurance," "disaster insurance," and "catastrophic insurance" was provided. Only English-language conference proceedings, reviews, and publications were considered to ensure quality and consistency. After eliminating duplicate records and unnecessary documents, the final datasets were exported in CSV format for additional analysis. Bibliometric analyses were conducted using VOSviewer, a recognised and competent software tool for science mapping methodology, which generated network visualisations for author collaboration, co-citation, and keyword co-occurrence. Academic production and impact performance metrics were drawn from publication counts, citation counts, and h-indexes of the authors, countries, and journals. Relational metrics were applied to determine the organisational structure of scientific cooperation and clustering in research themes. This methodological approach ensures a systematic, replicable, visually interpretable analysis of the catastrophic insurance literature. It also enables the identification of gaps and the formulation of research recommendations grounded in empirical bibliometric evidence. Figure 2 illustrates the evolving scholarly interest in the topic by displaying the annual distribution of research papers from 2000 to 2025. The number of publications remained low during the first phase (2000–2010), with an annual range of two to five papers. This suggests an early period of study effort when little scholarly attention was paid to the subject. However, starting in 2011, a noticeable change occurred, with the number of publications doubling to eight papers, signalling the start of a significant growth period. With 14 papers, this rising trend reached its peak in 2015, indicating a surge in interest from academics, as well as potentially from industry or policymakers. After peaking, the number of publications dropped sharply between 2016 and 2018, when it only produced five papers annually. Funding cycles, research saturation, or shifting scholarly goals are commonly cited as reasons for these decreases. Interestingly, there was a resurgence in 2019, as seen by the number of publications returning to 12, indicating that research interest had been reignited, possibly due to new issues or advancements in technology. The most notable peak, marked by 15 publications in 2023, likely indicates an increase in scholarly activity, probably prompted by world events, regulatory changes, or advances in the discipline. However, the following year, 2024, saw a steep drop to 6 publications, suggesting a normal post-peak adjustment period. A modest rebound to eight publications is observed by 2025. The trend indicates a cyclic but growing academic interest, with periods of intense activity followed by brief decreases, characteristic of nascent and rapidly expanding study topics. 1. Keywords Co-occurrence Network Table 1 tabular column illustrating the number of times the keywords that is been occurred in the extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025). Rank Keywords Occurrences 1 Insurance 54 2 Catastrophic Event 40 3 Insurance System 34 4 Risk Assessment 30 5 Disaster Management 23 6 Human 22 7 Humans 18 8 United States 17 9 Disasters 14 10 Article 13 11 Risk 12 12 Risk Management 12 13 Vulnerability 11 14 Natural Disaster 11 15 Female 10 Figure 3 illustrates the co-occurrence network of keywords in the catastrophic insurance literature, revealing emerging research trends. Three prominent clusters appear there in the network: Red (Risk Assessment, Insurance Industry, Hazard Modelling), Blue (Disaster Management, Adaptation Strategies), and Green (Health Expenditures, Socioeconomic Impacts). The centrality of the keyword "insurance" suggests that it has been crucial in bridging several research disciplines, primarily risk management and socioeconomic impact studies. The clustering pattern highlights the interdisciplinary field, even at distinct integration points, particularly where complementary work between public health economics and climate risk insurance is scarce. And also, Table 1 gives us the keywords and their number of occurrences in the cited papers 2. Co-Citation Author Network Figure 4 shows the co-citation relationships that exist between influential authors. Two major strands of research can be seen: the Red Cluster (Wagstaff A., Zhang L.), which focuses on health economics and catastrophic financial risk. At the same time, the Green Cluster (Kunreuther H.) approaches risk management and insurance for natural disasters. The sparse links that these clusters maintain among themselves represent the fragmented nature of the literature, with limited citations across disciplines. This gap also represents a key opportunity for future researchers to build integrative frameworks that link socioeconomic risk assessments with models of disaster insurance. 3. Country Collaboration Network Table 2 tabular column illustrating the number of times the countries have occurred in the dataset extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025). Rank Countries Citations 1 United States 1510 2 Australia 497 3 United Kingdom 379 4 India 298 5 Germany 263 6 Canada 254 7 Netherlands 215 8 China 183 9 Switzerland 183 10 Pakistan 149 11 Thailand 149 12 Austria 115 13 France 105 14 Spain 100 15 Iran 88 16 Mexico 66 17 South Africa 43 18 Singapore 42 19 Belgium 38 Figure 5 shows international research collaborations. Table 2 lists the countries and their citations. The U.S., followed by China, India, and a few other European nations, are the most productive and collaborative countries. Other developing countries, such as Nigeria, Pakistan, and Turkey, remain relatively isolated with few collaboration ties. This indicates a lack of geographic research coverage, particularly in areas that are highly vulnerable to catastrophic climate-related incidents. Therefore, alliances need to be forged with these downtrodden countries to develop a more inclusive and globally relevant insurance practice. 4. Authorship Network Figure 6 presents the co-authorship patterns, giving an insight into the framework of collaboration within the field. The visualisation is heavily fragmented, with many researchers working in isolation or small, closed groups. Examples of the few noteworthy partnerships include Kun Reuther, Howard, and Clarke, Daniel J. The absence of large co-authoring networks suggests that very little interdisciplinary or inter-institutional collaboration exists, a notable gap that must be addressed to encourage integrative research on catastrophic insurance. 5. Author Citation Network Table 3 tabular column illustrating the number of times the authors ' names and the years of publication that have occurred in the dataset extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025). Authors Year Cited by Hoeppe P. 2016 246 Weitzman M.L. 2012 222 Lo A.Y. 2013 207 Collier S. 2008 206 Selvaraj S.; Karan A.K. 2012 158 Ullah R.; Shivakoti G.P.; Ali G. 2015 149 Panwar V.; Sen S. 2019 132 Ericson R.V.; Doyle A. 2004 125 Chen K.; McAneney J.; Blong R.; Leigh R.; Hunter L.; Magill C. 2004 99 Bougen P.D. 2003 94 Botzen W.J.W.; Van Den Bergh J.C.J.M. 2009 78 Grove K. 2012 77 Prakongsai P.; Limwattananon S.; Tangcharoensathien V. 2009 71 Cutter S.L.; Emrich C.T.; Gall M.; Reeves R. 2018 71 Blau D.M.; Gilleskie D.B. 2006 70 Figure 7 displays the author citation network, aiding in identifying influential authors in the field. Groups such as Johnson Leigh and Doyle Aaron show dense internal citation states, while the rest of the network remains permeably connected. This means some authors do dominate in the thematic niche to some extent; however, due to a lack of cross-citation among the thematic domains (for example, health economics and environmental risk insurance), the citation practice remains relatively isolated, thereby restraining thematic integration essential to resolving complications that are multi-dimensional by nature and posed due to climate-based catastrophic risks. The list of authors, the year of their publication, and their citations are listed in Table 3 . Conclusion This bibliometric review of catastrophic insurance literature from 2000 to 2025 offers a thorough overview of the field's intellectual, thematic, and geographic growth. The study identifies the most influential authors and countries, highlights collaborative structures, uncovers emerging research themes, and exposes significant gaps in global coverage and interdisciplinary integration by addressing the stated objectives. The results corroborate that research in this field primarily focuses on high-income nations, including the United States, the United Kingdom, and certain European regions. In contrast, input from low- and middle-income areas remains minimal despite their heightened susceptibility to catastrophic occurrences. The analyses of co-authorship and co-citation show that the networks are broken up into small groups of researchers who do not work together very often. This lack of integration shows the importance of stronger global and interdisciplinary partnerships to bring together ideas from finance, climate science, public policy, and technology. Keyword analyses further demonstrate that, although risk assessment, disaster management, and insurance mechanisms predominate in research, a significant underrepresentation of innovative approaches incorporating AI, blockchain, and the socio-political aspects of insurance exists. When viewed together, the results show both progress and gaps that still exist. The literature has grown a lot in the last twenty years, but it still does not cover all the themes and regions equally. Future research should focus on enhancing partnerships with institutions in at-risk areas, integrating policy-driven frameworks, and promoting interdisciplinary studies that align insurance practices with emerging global risks. By bridging these gaps, catastrophic insurance research can better help the world be more resilient, share risks fairly, and develop long-term plans for adapting to disasters that are becoming more common. Declarations Conflict of interest The authors declare no conflict of interest Ethical approval This article does not contain any studies with human participants performed by any of the authors Funding This study has not received any specific funding Author Contribution Mary remeena R wrote the main manuscript text, and Saravanakrishnan reviewed and corrected the manuscript Data Availability Full data are available from authors upon request References Bhattacharya S, Castignani G, Masello L, Sheehan B (2025) AI revolution in insurance: bridging research and reality. Frontiers in Artificial Intelligence , 8 . https://doi.org/10.3389/frai.2025.1568266 Botzen WJW, Deschenes O, Sanders M (2019) The Economic Impacts of Natural Disasters: A Review of Models and Empirical Studies. Rev Environ Econ Policy 13(2):167–188. https://doi.org/10.1093/reep/rez004 Botzen WJW, Van Den Bergh JCJM (2009) Managing natural disaster risks in a changing climate. 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P., MCKEE, M., JONES M, IN THE WILDLAND–URBAN INTERFACE: IMPLICATIONS OF SURVEY AND EXPERIMENTAL DATA FOR WILDFIRE RISK REDUCTION POLICY (2006) AVERTING AND INSURANCE DECISIONS. Contemp Econ Policy 24(2):203–223. https://doi.org/10.1093/cep/byj021 Ullah R, Shivakoti GP, Ali G (2015) Factors affecting farmers’ risk attitude and risk perceptions: The case of Khyber Pakhtunkhwa, Pakistan. Int J Disaster Risk Reduct 13:151–157. https://doi.org/10.1016/j.ijdrr.2015.05.005 WEITZMAN ML (2012) GHG T argets as I nsurance A gainst C atastrophic C limate. J Public Econ Theor 14(2):221–244. %3E D amages https://doi.org/10.1111/j.1467-9779.2011.01539.x Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8773653","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585025177,"identity":"72a1c7ac-8ca7-4788-95ed-7ff4814ebf60","order_by":0,"name":"Mary Remeena","email":"data:image/png;base64,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","orcid":"","institution":"Christ University","correspondingAuthor":true,"prefix":"","firstName":"Mary","middleName":"","lastName":"Remeena","suffix":""},{"id":585025178,"identity":"110dcfaf-af09-42a2-86b0-b1d9aa033b8f","order_by":1,"name":"Saravana Krishnan","email":"","orcid":"","institution":"Christ University","correspondingAuthor":false,"prefix":"","firstName":"Saravana","middleName":"","lastName":"Krishnan","suffix":""}],"badges":[],"createdAt":"2026-02-03 09:24:54","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8773653/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8773653/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101830525,"identity":"8637f0a4-c6a4-4393-87e9-6c6b3851ff6c","added_by":"auto","created_at":"2026-02-04 06:22:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35157,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA 2020 Flow Diagram for the Identification, Screening, and Inclusion of Studies for this paper: Adapted from (Page et al., 2021)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/f40d8b7ea08d20cc70757f99.png"},{"id":101881295,"identity":"8559fe4f-4f97-4ba9-bf5e-a9517ec8ccab","added_by":"auto","created_at":"2026-02-04 15:11:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50209,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical data illustrating the rise in active research activity associated with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/f7d4f660754cd54fffc016d1.png"},{"id":101880929,"identity":"dec8a488-61b5-4923-84fb-6c7197cb4082","added_by":"auto","created_at":"2026-02-04 15:08:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":871764,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence network of keywords in catastrophic insurance literature\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/2b9e7809edf941fa1401c52b.png"},{"id":101830520,"identity":"45f616e9-20eb-43a9-b4d3-97bc18ba8903","added_by":"auto","created_at":"2026-02-04 06:22:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51968,"visible":true,"origin":"","legend":"\u003cp\u003eThe co-citation relationships that exist between influential authors\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/1548f11e7405a1868dcee605.png"},{"id":101830522,"identity":"409b22bd-454f-47a8-a679-f7e68bcdbc8d","added_by":"auto","created_at":"2026-02-04 06:22:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":36777,"visible":true,"origin":"","legend":"\u003cp\u003eInternational research collaborations\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/d5edebf47f12855bed546598.png"},{"id":101880922,"identity":"6e8b01fb-a63d-465b-ba3c-9f731a9ee7cf","added_by":"auto","created_at":"2026-02-04 15:07:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":106741,"visible":true,"origin":"","legend":"\u003cp\u003eNetworking of authors\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/fabe98bdb4cb70d1eb852de6.png"},{"id":101830523,"identity":"a75dd8cd-cc99-4ced-983d-f4e206373e0a","added_by":"auto","created_at":"2026-02-04 06:22:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":105481,"visible":true,"origin":"","legend":"\u003cp\u003eAuthor citation network\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/8a7b8fe6c6a71897f56d32a4.png"},{"id":104405018,"identity":"20f84242-bf6e-425e-a5a7-2e79a30d1be9","added_by":"auto","created_at":"2026-03-11 12:21:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1808162,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8773653/v1/82488369-0434-48a6-8af9-ff74c57215c1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trends and Gaps in Global Catastrophic Insurance Literature: A Bibliometric Review (2000–2024)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChanges in the radius of catastrophe and other dimensions of natural phenomena have made the global community aware of the necessity of having robust risk financing mechanisms. Insurance is the most apparent means of securing development during a catastrophe among all the market-financing mechanisms(Linnerooth-Bayer \u0026amp; Hochrainer-Stigler, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This also includes insurance against catastrophe risks, which enhances resilience by enabling recovery and mitigating long-term socioeconomic disruption(Kousky, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The discussion has evolved with the advent of urbanisation, environmental degradation, and climate change as global risks, on the design, governance, and implementation of insurance mechanisms that primarily cater towards private interests, while also being an instrument for the public good during large-scale disasters.\u003c/p\u003e \u003cp\u003eDuring the past two decades, the researcher, policymaker, and insurance practitioner communities have been trying to understand how insurance systems respond to catastrophic risks, by whom they are governed, and what factors influence their performance. This includes institutional frameworks, pricing mechanisms, public-private partnerships, reinsurance, and other emerging tools, such as parametric insurance and AI-based risk modelling(Bhattacharya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, despite all the growth in alliance literature, it has not produced a comprehensive bibliometric study.\u003c/p\u003e \u003cp\u003eTo fill this gap, we present a detailed bibliometric study with literature on catastrophe insurance from 2000 to 2024, leveraging Scopus-indexed publications and visualisation software such as VOS viewer. We mapped the intellectual structure of the catastrophe insurance field to unveil the most significant authors, countries, institutions, and themes. This consists of analyzing co-authorships, keyword co-occurrences, citation networks, and thematic clusters to see how the field has evolved and where fragmentation or underrepresentation still exists.\u003c/p\u003e \u003cp\u003eMoreover, the study reveals that global research on catastrophic insurance remains concentrated in high-income countries, primarily in the United States, the United Kingdom, and a few European countries. While low- and middle-income countries are most vulnerable to catastrophic events, they contribute very little to the literature. The findings from this bibliometric review can inform more balanced research agendas and foster wider academic collaborations in pursuit of inclusive and equitable climate adaptation, disaster preparedness, and financial resilience models.\u003c/p\u003e \u003cp\u003eThe paper sets out to answer some key questions: Who leads thinking on the research of catastrophic insurance? What are the dominant themes and new areas? How is knowledge geographically spread? Moreover, where are the main gaps? With this study, we seek to create a strategic knowledge map for this field and identify directions for future research, especially with the rise in worldwide catastrophes and systemic risks.\u003c/p\u003e \u003cp\u003eCatastrophic risks threaten economies and societies worldwide, ranging from pandemics and geopolitical crises to climate-related disasters like hurricanes, floods, and wildfires(Botzen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). An essential risk-financing tool that promotes recovery, lessens long-term socioeconomic upheaval, and redistributes losses among populations is insurance. In this context, catastrophic insurance is one of the most important tools for guaranteeing resilience.\u003c/p\u003e \u003cp\u003eCatastrophic insurance has changed in practice and research over the last 20 years. Researchers have examined institutional frameworks, pricing mechanisms, parametric insurance, catastrophe bonds, public-private partnerships, and AI-driven risk modeling(Jia et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Notwithstanding these advancements, the literature is still dispersed, focusing on wealthy nations and scant representation from vulnerable areas where the effects of disasters are most significant.\u003c/p\u003e \u003cp\u003eThe need for a thorough bibliometric analysis of the literature on catastrophic insurance is addressed in this paper. There are conceptual and narrative reviews, but no thorough scientometric mapping of the field that incorporates thematic clustering, collaboration mapping, and performance analysis has been done. In doing so, this research aims to respond to the following queries:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhich writers, publications, and organizations are the most successful and significant in catastrophic insurance research?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhich research themes are prevalent and developing?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHow is knowledge production geographically distributed, and what collaboration patterns exist?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRegarding geography, interdisciplinarity, and thematic focus, where are the important research gaps?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe study contributes by providing a strategic knowledge map that educates academics, decision-makers, and practitioners about the state of the field and its prospects for advancement.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjectives\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo identify the most productive and influential authors and countries in catastrophic insurance literature (2000\u0026ndash;2025).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo examine co-authorship and co-citation patterns for understanding collaborative structures.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo map keyword clusters and uncover emerging research themes.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo identify gaps in the literature regarding geographic coverage, thematic integration, and interdisciplinary collaboration.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Literature Review","content":"\u003cp\u003e(Hoeppe, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)The insurance sector, particularly Munich Re, has monitored losses from natural disasters for four decades. According to these statistics, weather-related occurrences like storms and floods have tripled. This trend is exacerbated by socioeconomic variables such as population expansion and urbanization, but is also influenced by global warming. Extreme weather patterns are influenced by natural climate cycles, such as ENSO and AMO. Although it is challenging to attribute the cause of losses to global warming clearly, research shows that they continue to increase even after corrections. Insurers must modify rates to account for evolving risks as climate change develops. To avoid significant losses in the future, preemptive measures for climate protection and adaptation are crucial.\u003c/p\u003e \u003cp\u003e(WEITZMAN, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) states that this study challenges conventional climate change economic models that rely on thin-tailed temperature distributions and a quadratic damage function. According to this argument, these models might significantly understate the possible welfare losses brought on by catastrophic climate outcomes. The study highlights the indirect benefits of stringent greenhouse gas (GHG) concentration objectives. These goals, which are supported by numerical examples, act as insurance against disastrous temperature increases. The results imply that conventional models do not adequately capture the gravity of high-impact, low-probability occurrences. Therefore, more substantial mitigation activities might be required in extreme uncertainty to reduce the probability of catastrophic climate-related impacts and achieve desired objectives.\u003c/p\u003e \u003cp\u003e(Lo, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) examined how risk perception and social norms influence people's decisions to purchase flood insurance in cities in eastern Australia. Researchers polled 501 residents. They discovered that insurance adoption was significantly predicted by social norms rather than direct risk perception. Path analysis demonstrated how perceived social norms were shaped by risk perception, which indirectly affected insurance decisions. These results demonstrate the importance of socio-cultural context in responding to climate risk and show that social factors influence behavior.\u003c/p\u003e \u003cp\u003e(Collier, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) explores \"enactment\" as a novel form of knowledge distinct from traditional social understandings, particularly in estimating catastrophic future risks. Through historical analysis of U.S. civil defence, natural hazard modelling, and terrorism risk assessment, the study highlights how expert practices construct risk as an object of governance. The article contributes to risk society debates by arguing that these approaches are not subjective anomalies but structured forms of knowledge that demand genealogical and institutional analysis within contemporary risk management frameworks.\u003c/p\u003e \u003cp\u003eSince many agricultural risks are challenging to cover sustainably, (Hazell, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) criticizes multiple-risk crop insurance plans as expensive and generally ineffective. However, if regulatory restrictions are loosened, there may be opportunities to insure farm assets, rural health, and particular risks through private insurers. According to the study, which highlights the need for creative ways to ensure low-income rural households, straightforward insurance plans based on indices and connected to local meteorological data provide an affordable way to guard against devastating climate-related disasters like floods or droughts.\u003c/p\u003e \u003cp\u003e(Ullah et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) used a risk matrix and the Equally Likely Certainty Equivalent approach to examine farmers' attitudes about risk and their perceptions of catastrophic risks. According to the report, most farmers are risk-averse and consider pests, floods, and excessive rains significant hazards. At the same time, access to formal information and credit increased risk perceptions, and socioeconomic factors such as age, education, income, land ownership, and informal credit availability influenced risk attitudes. Policymakers and insurers can use the data to develop focused agricultural risk management plans and assistance programs.\u003c/p\u003e \u003cp\u003e(Panwar \u0026amp; Sen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) re-evaluated the short- to medium-term economic impacts of natural disasters across 102 countries (1981–2015), using a system GMM approach. Analyzing floods, droughts, storms, and earthquakes, the study found that disaster impacts vary by sector, disaster type, and intensity. Crucially, the effects are more pronounced in developing nations. The findings emphasize the importance of ex-ante disaster risk financing tools—such as insurance and catastrophic bonds—for protecting assets and supporting sustainable development, particularly in vulnerable, low-income economies.\u003c/p\u003e \u003cp\u003eIn their analysis of the American insurance industry's reaction to the terrorist events of September 11, 2001, (Ericson \u0026amp; Doyle, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) showed how the government and insurers worked together to restructure markets to maintain terrorism coverage. The system made up for losses and exposed the sector's structural weakness. The study challenges Ulrich Beck's claims regarding disaster risk by demonstrating insurance's dual function of reducing uncertainty and creating new disparities and crises through market reactions. It emphasizes how essential insurers are in determining risk management and risk-based exclusion.\u003c/p\u003e \u003cp\u003e(Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) addressed the spatial mismatch between hazard data (raster-based) and exposure data (areal-based) in catastrophe loss estimation models. Using Sydney as a case study, they introduced a dissymmetric mapping approach to define occupied residential areas at risk. Their findings showed that finer-resolution exposure data significantly improved loss estimates for small-footprint hazards like hailstorms, while large-area events like earthquakes were less affected. The study highlights the importance of accurate spatial delineation in integrating environmental and socioeconomic data for more reliable catastrophe loss assessments.\u003c/p\u003e \u003cp\u003e(Bougen, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) explores the rise of catastrophe-financing mechanisms involving reinsurance and capital markets as responses to growing concerns about the non-insurability of catastrophic events in contemporary risk society. The paper examines these mechanisms through two lenses: the fragility and sustainability of risk networks, and the innovative, market-driven approaches emerging from liberal governance. It highlights how these financial instruments reflect anxieties over catastrophic risk and capitalist creativity, offering valuable insights into evolving trajectories of risk management and the dynamics of insurability in a neoliberal context.\u003c/p\u003e \u003cp\u003e(Botzen \u0026amp; Van Den Bergh, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) highlight how climate and socioeconomic changes contribute to increased frequency and intensity of catastrophic disasters. They support robust risk management plans incorporating risk-sharing, preventive, and mitigation techniques. In the context of low-probability, high-impact occurrences made worse by climate change, the study emphasizes the function of insurance and its significance in climate adaptation methods to lessen and manage the socioeconomic costs of disasters.\u003c/p\u003e \u003cp\u003e(Grove, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) critically examines the Caribbean Catastrophic Risk Insurance Facility (CCRIF), arguing that it exemplifies the \"financialization of disaster management.\" While CCRIF is promoted as a tool for climate adaptation through disaster recovery financing, Grove contends it reconfigures population adaptability into a securitized and market-leveraged risk. By blending risk pooling and parametric insurance, CCRIF enhances state infrastructure resilience while reinforcing state control and capital accumulation under the guise of climate risk management.\u003c/p\u003e \u003cp\u003eIn their analysis of the 2015 South Carolina flash flood, (Cutter et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) trace the evolution of flood risk over time and emphasize two central paradoxes: the local government conundrum and the safe development paradox. The paper uses archival evidence to show how low flood insurance uptake, bad zoning, and urban growth increased flood risk. The incident led to minor policy adjustments despite significant losses, particularly among affluent inhabitants, highlighting a lack of institutional learning and ongoing development-driven risk exposure.\u003c/p\u003e \u003cp\u003e(Johnson, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) explores how catastrophe bonds transform geophysical, biological, and meteorological disasters into securitized, tradable risks within the insurance-linked securities (ILS) market. Through catastrophe modeling, contingent assets are generated from environmental and financial vulnerabilities. The paper highlights pension funds' dual role as investors in catastrophe bonds and sellers of longevity risk, illustrating the complex entanglement of labor, finance, and contingency. This reflects a broader shift toward securitized risk as an economic governance and accumulation modality.\u003c/p\u003e \u003cp\u003e(Pita et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) comprehensively review building vulnerability assessment methods for hurricane catastrophe models, identifying five key approaches: past-loss data, enhanced damage data, heuristic, physics-based, and simulation models. The study critiques limitations of loss-only models and highlights the evolution toward engineering-informed and probabilistic simulations. It also examines post-disaster validation studies and mapping of model developments. The paper underscores prospects, including interior damage modeling and broader applications in catastrophe risk assessment.\u003c/p\u003e \u003cp\u003e(Johnson, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) explores how the (re)insurance industry navigates climate change impacts as socio-ecological fixes for crises of overaccumulation. The paper argues that catastrophic losses during soft markets devalue capital, prompting recalibrations in catastrophe models and enabling capital reinvestment. Climate change uncertainty is framed not as an existential threat, but as a financial opportunity. The study critiques reliance on market mechanisms, warning of emerging \"splintered protectionism\" and uneven climate adaptation shaped by rising premiums and state-managed retreat.\u003c/p\u003e \u003cp\u003e(CARDENAS et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) examine Mexico's pioneering 2006 initiative to transfer public-sector natural catastrophe risk to international markets via reinsurance and catastrophe bonds. Analyzing the decision-making process of Mexico's Ministry of Finance, the study uses IIASA's CATSIM model to evaluate risk-transfer options as public investment decisions. It highlights the importance of fiscal and institutional contexts, noting that while financial instruments ensure post-disaster liquidity, their high costs necessitate careful benefit-risk assessment, especially for developing countries.\u003c/p\u003e \u003cp\u003e(Cohen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) propose a novel preference representation model under risk that incorporates experience-dependent risk perception. By framing preferences around decision-experience pairs, the authors construct a dynamic choice model explaining temporal shifts in insurance demand. Through an illustrative example, the study demonstrates how this approach better captures behavioral changes in catastrophic risk insurance markets—patterns that standard models struggle to justify—highlighting the significance of past experiences in shaping risk-related decision-making.\u003c/p\u003e \u003cp\u003e(TALBERTH et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) investigate how homeowners allocate resources between insurance and averting activities in response to catastrophic wildfire risk. Using contingent valuation and experimental data, the study finds that, contrary to expected utility theory, individuals often choose both strategies when nonmarket losses are significant. Factors such as amenity values, perceived risk, averting efficacy, and demographics influence willingness to pay and averting behavior. Additionally, wildfire risk zone information significantly shapes decision-making, supporting theoretical predictions.\u003c/p\u003e \u003cp\u003e(Collier, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) explores the role of insurance in U.S. flood policy during the 1960s, highlighting how it functioned not only as a technical solution to disaster loss and compensation but also as a political technology. The study illustrates how insurance reshaped governance by redefining state-citizen responsibilities and reframing security through economic rationality. It challenges conventional narratives on risk and responsibility, offering critical insights into the neoliberal transformation of public policy and disaster management.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"METHODOLOGY","content":"\u003ch2\u003eTheoretical Framework\u003c/h2\u003e\u003cp\u003eThe bibliometric analysis is grounded in \u003cb\u003escientometric principles\u003c/b\u003e, which provide tools for measuring and interpreting patterns in scholarly communication.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cul\u003e \u003cli\u003e \u003cp\u003eLotka's Law (1926) claimed a scientific productivity pattern to have been of the power-law type, where a few authors contributed the highest number of publications, whereas most others authored just one. Applying this law would give us an idea whether catastrophic insurance research follows the distributions of expected productivity or whether it is a more fragmented area.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBradford's Law (1934) explains journal concentration by stating that in any discipline, a few core journals publish most of the literature. This helps identify the journals that have had the most significant impact on catastrophic insurance, and determines whether the field is becoming consolidated or fragmented.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAccording to Zipf's Law (1949) concerning keyword frequency, one may state that it is the recurrence of particular terms in written literature. The application of this principle reveals the most crucial thematic terms (\"risk assessment,\" \"disaster management\") along with their clustering into intellectual subfields.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe study is also informed by Beck's Risk Society theory (1992), which stresses the role of modern institutions in managing systemic unpredictable risks. Insurance is thus not a mere financial tool; it is a governance mechanism through which risk is framed, losses are redistributed, and choices are made regarding adaptation strategies. Complementing scientometric investigations with risk theory offers a richer interpretation of bibliometric research findings by situating them within broader socio-political contexts.\u003c/p\u003e\n\u003ch3\u003eMethodological Framework\u003c/h3\u003e\n\u003cp\u003eThis study employs a structured quantitative bibliometric methodology, combined with performance analysis and science mapping, to identify global research trends in catastrophic insurance. Bibliometric analysis is particularly productive when employed in synthesising vast amounts of academic literature and showing hidden patterns of the production and dissemination of knowledge (Donthu et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This study employs an exploratory design to address key questions about the most productive authors, institutions with the greatest influence, the most researched themes, and areas that have received little attention.\u003c/p\u003e \u003cp\u003eThe Scopus database, chosen primarily for its broad, multidisciplinary coverage and consistent indexing of peer-reviewed literature, provided the study's data. To gather documents published between 2000 and 2025, a carefully constructed query based on terms such as \"natural hazard insurance,\" \"disaster insurance,\" and \"catastrophic insurance\" was provided. Only English-language conference proceedings, reviews, and publications were considered to ensure quality and consistency. After eliminating duplicate records and unnecessary documents, the final datasets were exported in CSV format for additional analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBibliometric analyses were conducted using VOSviewer, a recognised and competent software tool for science mapping methodology, which generated network visualisations for author collaboration, co-citation, and keyword co-occurrence. Academic production and impact performance metrics were drawn from publication counts, citation counts, and h-indexes of the authors, countries, and journals. Relational metrics were applied to determine the organisational structure of scientific cooperation and clustering in research themes.\u003c/p\u003e \u003cp\u003eThis methodological approach ensures a systematic, replicable, visually interpretable analysis of the catastrophic insurance literature. It also enables the identification of gaps and the formulation of research recommendations grounded in empirical bibliometric evidence.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the evolving scholarly interest in the topic by displaying the annual distribution of research papers from 2000 to 2025. The number of publications remained low during the first phase (2000\u0026ndash;2010), with an annual range of two to five papers. This suggests an early period of study effort when little scholarly attention was paid to the subject. However, starting in 2011, a noticeable change occurred, with the number of publications doubling to eight papers, signalling the start of a significant growth period. With 14 papers, this rising trend reached its peak in 2015, indicating a surge in interest from academics, as well as potentially from industry or policymakers.\u003c/p\u003e \u003cp\u003eAfter peaking, the number of publications dropped sharply between 2016 and 2018, when it only produced five papers annually. Funding cycles, research saturation, or shifting scholarly goals are commonly cited as reasons for these decreases. Interestingly, there was a resurgence in 2019, as seen by the number of publications returning to 12, indicating that research interest had been reignited, possibly due to new issues or advancements in technology.\u003c/p\u003e \u003cp\u003eThe most notable peak, marked by 15 publications in 2023, likely indicates an increase in scholarly activity, probably prompted by world events, regulatory changes, or advances in the discipline. However, the following year, 2024, saw a steep drop to 6 publications, suggesting a normal post-peak adjustment period. A modest rebound to eight publications is observed by 2025. The trend indicates a cyclic but growing academic interest, with periods of intense activity followed by brief decreases, characteristic of nascent and rapidly expanding study topics.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1. Keywords Co-occurrence Network\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003etabular column illustrating the number of times the keywords that is been occurred in the extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeywords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOccurrences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInsurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatastrophic Event\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInsurance System\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk Assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisaster Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHumans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisasters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVulnerability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNatural Disaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the co-occurrence network of keywords in the catastrophic insurance literature, revealing emerging research trends. Three prominent clusters appear there in the network: Red (Risk Assessment, Insurance Industry, Hazard Modelling), Blue (Disaster Management, Adaptation Strategies), and Green (Health Expenditures, Socioeconomic Impacts). The centrality of the keyword \"insurance\" suggests that it has been crucial in bridging several research disciplines, primarily risk management and socioeconomic impact studies. The clustering pattern highlights the interdisciplinary field, even at distinct integration points, particularly where complementary work between public health economics and climate risk insurance is scarce. And also, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e gives us the keywords and their number of occurrences in the cited papers\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Co-Citation Author Network\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the co-citation relationships that exist between influential authors. Two major strands of research can be seen: the Red Cluster (Wagstaff A., Zhang L.), which focuses on health economics and catastrophic financial risk. At the same time, the Green Cluster (Kunreuther H.) approaches risk management and insurance for natural disasters. The sparse links that these clusters maintain among themselves represent the fragmented nature of the literature, with limited citations across disciplines. This gap also represents a key opportunity for future researchers to build integrative frameworks that link socioeconomic risk assessments with models of disaster insurance.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Country Collaboration Network\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003etabular column illustrating the number of times the countries have occurred in the dataset extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountries\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e497\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePakistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouth Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingapore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows international research collaborations. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e lists the countries and their citations. The U.S., followed by China, India, and a few other European nations, are the most productive and collaborative countries. Other developing countries, such as Nigeria, Pakistan, and Turkey, remain relatively isolated with few collaboration ties. This indicates a lack of geographic research coverage, particularly in areas that are highly vulnerable to catastrophic climate-related incidents. Therefore, alliances need to be forged with these downtrodden countries to develop a more inclusive and globally relevant insurance practice.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. Authorship Network\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the co-authorship patterns, giving an insight into the framework of collaboration within the field. The visualisation is heavily fragmented, with many researchers working in isolation or small, closed groups. Examples of the few noteworthy partnerships include Kun Reuther, Howard, and Clarke, Daniel J. The absence of large co-authoring networks suggests that very little interdisciplinary or inter-institutional collaboration exists, a notable gap that must be addressed to encourage integrative research on catastrophic insurance.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. Author Citation Network\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003etabular column illustrating the number of times the authors ' names and the years of publication that have occurred in the dataset extracted from Scopus with the keywords (a) catastrophic insurance, (b) insurance. Data courtesy: Scopus (acquired in September 2025).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCited by\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoeppe P.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeitzman M.L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLo A.Y.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollier S.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelvaraj S.; Karan A.K.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUllah R.; Shivakoti G.P.; Ali G.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePanwar V.; Sen S.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEricson R.V.; Doyle A.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChen K.; McAneney J.; Blong R.; Leigh R.; Hunter L.; Magill C.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBougen P.D.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBotzen W.J.W.; Van Den Bergh J.C.J.M.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrove K.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrakongsai P.; Limwattananon S.; Tangcharoensathien V.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCutter S.L.; Emrich C.T.; Gall M.; Reeves R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlau D.M.; Gilleskie D.B.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e displays the author citation network, aiding in identifying influential authors in the field. Groups such as Johnson Leigh and Doyle Aaron show dense internal citation states, while the rest of the network remains permeably connected. This means some authors do dominate in the thematic niche to some extent; however, due to a lack of cross-citation among the thematic domains (for example, health economics and environmental risk insurance), the citation practice remains relatively isolated, thereby restraining thematic integration essential to resolving complications that are multi-dimensional by nature and posed due to climate-based catastrophic risks. The list of authors, the year of their publication, and their citations are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis bibliometric review of catastrophic insurance literature from 2000 to 2025 offers a thorough overview of the field's intellectual, thematic, and geographic growth. The study identifies the most influential authors and countries, highlights collaborative structures, uncovers emerging research themes, and exposes significant gaps in global coverage and interdisciplinary integration by addressing the stated objectives. The results corroborate that research in this field primarily focuses on high-income nations, including the United States, the United Kingdom, and certain European regions. In contrast, input from low- and middle-income areas remains minimal despite their heightened susceptibility to catastrophic occurrences.\u003c/p\u003e \u003cp\u003eThe analyses of co-authorship and co-citation show that the networks are broken up into small groups of researchers who do not work together very often. This lack of integration shows the importance of stronger global and interdisciplinary partnerships to bring together ideas from finance, climate science, public policy, and technology. Keyword analyses further demonstrate that, although risk assessment, disaster management, and insurance mechanisms predominate in research, a significant underrepresentation of innovative approaches incorporating AI, blockchain, and the socio-political aspects of insurance exists.\u003c/p\u003e \u003cp\u003eWhen viewed together, the results show both progress and gaps that still exist. The literature has grown a lot in the last twenty years, but it still does not cover all the themes and regions equally. Future research should focus on enhancing partnerships with institutions in at-risk areas, integrating policy-driven frameworks, and promoting interdisciplinary studies that align insurance practices with emerging global risks. By bridging these gaps, catastrophic insurance research can better help the world be more resilient, share risks fairly, and develop long-term plans for adapting to disasters that are becoming more common.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declare no conflict of interest\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003eThis article does not contain any studies with human participants performed by any of the authors\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study has not received any specific funding\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMary remeena R wrote the main manuscript text, and Saravanakrishnan reviewed and corrected the manuscript\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eFull data are available from authors upon request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBhattacharya S, Castignani G, Masello L, Sheehan B (2025) AI revolution in insurance: bridging research and reality. \u003cem\u003eFrontiers in Artificial Intelligence\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/frai.2025.1568266\u003c/span\u003e\u003cspan address=\"10.3389/frai.2025.1568266\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBotzen WJW, Deschenes O, Sanders M (2019) The Economic Impacts of Natural Disasters: A Review of Models and Empirical Studies. 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J Public Econ Theor 14(2):221\u0026ndash;244. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e%3E\u0026thinsp;D amages\u003c/span\u003e\u003cspan address=\"http://%3E\u0026thinsp;D amages\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1467-9779.2011.01539.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1467-9779.2011.01539.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Catastrophic insurance, Risk, Disaster, Climate","lastPublishedDoi":"10.21203/rs.3.rs-8773653/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8773653/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003e\u0026ndash; The study provides a comprehensive bibliometric review of destruction cover-sellings between 2000 and 2024. It is to sketch the intellectual and thematic landscape of the field, identify its leading contributors, analyse the collaboration structure, mark geographic and thematic gaps, and provide future directions. Catastrophic insurance now becomes core in resilience-building and risk transfer in the face of increasing climate disasters, pandemics, and systemic risks.\u003c/p\u003e\u003ch2\u003eDesign/Methodology/Approach\u003c/h2\u003e \u003cp\u003e- The data were extracted from the Scopus database using an adapted and well-constructed query search string. PRISMA-based inclusions and exclusions were applied to ensure quality and relevance. Bibliometric analysis was performed in VOSviewer for science mapping (co-authorship, co-citation, keyword co-occurrence), whereas Excel was used to visualize the trends. Performance analysis considered parameters in scientists, journals, institutions, and countries, looking for production and impact. Scientometric concepts such as the Lotka Law or the Bradford Law validated the author production and the journal concentration distribution, respectively.\u003c/p\u003e\u003ch2\u003eFindings\u003c/h2\u003e \u003cp\u003e\u0026ndash; Catastrophic insurance (Lin et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)research apparently diversified steadily, with alternating peak moments in 2015\u0026ndash;2023, corresponding to global crises, stockpiles, and interests in disaster financing. However, contributions from geographically outside the realm of developed countries remain limited in attracting interest from vulnerable and low-income regions in the market. From the thematic viewpoint, the structure becomes evident: risk modelling, actuarial pricing, and economic assessment dominate, with a lack of representation for issues of public policy and governance, and technological innovations, such as AI, blockchain, or parametric insurance. The collaboration networks are scattered: isolated groups of authors work in their silos, thus contributing enterprisingly little to interdisciplinary integration.\u003c/p\u003e\u003ch2\u003eOriginality/Value\u003c/h2\u003e \u003cp\u003e\u0026ndash; Scientometric principles are applied methodically to the literature on catastrophic insurance in this bibliometric review for the first time. The study contextualizes insurance as a financial and governance mechanism and identifies intellectual trends through integrating quantitative bibliometric mapping with sociological theory (Beck's Risk Society). The review offers a well-organised research agenda on innovation, inclusivity, and interdisciplinarity.\u003c/p\u003e","manuscriptTitle":"Trends and Gaps in Global Catastrophic Insurance Literature: A Bibliometric Review (2000–2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-04 06:22:46","doi":"10.21203/rs.3.rs-8773653/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fe04d577-b40b-474d-9402-13d587fff808","owner":[],"postedDate":"February 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T12:57:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-04 06:22:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8773653","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8773653","identity":"rs-8773653","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}