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Earthquake hazards, though occurring infrequently, can produce catastrophic losses with pronounced right-skewed and heavy-tailed characteristics in both economic damages and fatalities. These impacts often intensify jointly under extreme conditions, posing challenges for reliable regional catastrophe risk assessment. Using earthquake records from 1980 to 2024 in selected provinces (autonomous regions and municipalities) of China, this study develops variable weights spliced Gumbel–GPD and Weibull–GPD distributions to model the marginal behavior of extreme losses. The dependence between economic losses and casualties—particularly in the upper tail—is captured using the SJC Copula, allowing for asymmetric co-extremal behavior. Due to the limited number of high-loss historical events, we analyze the sensitivity of parameter estimates to sample size through numerical simulations. After confirming that the GAN-generated samples are statistically consistent with the original data, they are employed to strengthen the robustness of parameter estimation. Integrating the spliced marginal models with a copula-based dependence framework, this study evaluates extreme loss levels for different regions under historical seismic conditions. The resulting estimates offer quantitative support for identifying key areas requiring enhanced seismic protection and for informing regional disaster-risk management.

Background Adverse events (AEs) cause harm in patients and disturbance for the professionals involved in the event (second victims). This study assessed the impact of AEs in primary care (PC) and hospitals in Spain on second victims. Methods A cross-sectional study was conducted. We carried out a survey based on a random sample of doctors and nurses from PC and hospital settings in Spain. A total of 1087 health professionals responded, 610 from PC and 477 from hospitals. Results A total of 430 health professionals (39.6%) had informed a patient of an error. Reporting to patients was carried out by those with the strongest safety culture (Odds Ratio –OR- 1.1, 95% Confidence Interval –CI- 1.0-1.2), nurses (OR 1.9, 95% CI 1.5-2.3), those under 50 years of age (OR 0.7, 95% CI 0.6-0.9) and primary care staff (OR 0.6, 95% CI 0.5-0.9). A total of 381 (62.5%, 95% CI 59-66%) and 346 (72.5%, IC95% 69-77%) primary care and hospital health professionals, respectively, reported having gone through the second-victim experience, either directly or through a colleague, in the previous 5 years. The emotional responses were: feelings of guilt (521, 58.8%), anxiety (426, 49.6%), re-living the event (360, 42.2%), tiredness (341, 39.4%), insomnia (317, 38.0%) and persistent feelings of insecurity (284, 32.8%). In doctors, the most common responses were: feelings of guilt (OR 0.7 IC95% 0.6-0.8), re-living the event (OR 0.7, IC95% o.6-0.8), and anxiety (OR 0.8, IC95% 0.6-0.9), while nurses showed greater solidarity in terms of supporting the second victim, in both PC (p = 0.019) and hospital (p = 0.019) settings. Conclusions Adverse events cause guilt, anxiety, and loss of confidence in health professionals. Most are involved in such events as second victims at least once in their careers. They rarely receive any training or education on coping strategies for this phenomenon.

The private health sector was officially recognized in the Republic of Congo over 20 years ago June 6, 1988, establishing the conditions for the independent practice of medicine and the medical-related and pharmaceutical professions. The Congolese government recently expressed its commitment to working with the private health sector in order to strengthen the health system, improve the health of the population and preserve the basic human right to a healthy life through the National Health Care Policy, which it adopted in 2003, the 2007-2011 National Health Development Plan and the 2010 Health Care Services Development Program. Throughout these various documents there is an acknowledgement that the lack of coordination with the private health sector is a weakness of the health system. Nevertheless, the scarcity of information about the private sector in policy and planning documents suggests that the government's engagement with the private health sector is limited. There is no official government policy on the private health sector, or strategies or working plans to encourage cooperation between the public and private sectors. The objective of this assessment was to better determine the role, position, and importance of the private sector within the health system, in order to identify the limitations to its development as well as ways it can be integrated into the efforts to meet the objectives of the Plan national de developpement sanitaire (PNDS) [National Health Development Plan]. The World Bank Group contracted with the Results for Development Institute (R4D, United States) and Health Research for Action (HERA, Belgium) as well as with a team of local consultants, to conduct a 'study of the private health sector in the Republic of Congo.' This study was conducted in close collaboration with the Ministry of Health and Population (MSP), which arranged and oversaw a steering committee consisting of actors from the public and private sectors to facilitate and guide the study. The goal of the study and the workshops was a concrete plan of action for the health sector that could be used by the Congolese government, the private sector in the Republic of Congo, and international development partners. Certain aspects of the action plan should be included in the work programs of the Programme de developpement des services de sante (PDSS) [Health System Development Project] for the years 2011-2013.

This report addresses the large flood exposures of Central Europe and proposes efficient financial and risk transfer mechanisms to mitigate fiscal losses from natural catastrophes. In particular, the Visegrad countries (V-4) of Central Europe, namely, Poland, the Czech Republic, Hungary, and the Slovak Republic, have such tremendous potential flood damages that reliance on budgetary appropriations or even European Union (EU) funds in such circumstances becomes ineffective and does not provide needed cash funds for the quick response and recovery needed to minimize economic disruptions. The report is primarily addressed to the governments of the region, which should build into their fiscal planning the necessary contingent funding mechanisms, based on their exposures. The report is addressed to finance ministries and also to the insurance and securities regulators and the private insurance and capital markets, which may all play a role in the proposed mechanisms. An arrangement using a multi-country pool with a hazard-triggered insurance payout mechanism complemented by contingent financing is proposed, to better manage these risks and avoid major fiscal volatility and disruption.

The global property protection gap in natural catastrophe risk has widened steadily over the past 40 years. In historical terms, we find that most underinsurance of extreme events is for climate-related events such as flood and windstorm, but in expected terms, earthquakes comprise the largest share of underinsurance. Using a framework to define the protection gap in historical and expected terms, this paper breaks down the gap by geography and risk type and presents an empirical analysis of the key drivers of the gap. First, uninsured expected Cat losses are estimated using models that combine geophysical vulnerability maps, economic exposure data and insurance market information. Second, each country’s expected (or optimal) property insurance penetration is modelled and compared to actual penetration to derive a measure of property underinsurance. Third, we explore the factors that affect property insurance demand, applying regression analysis to an unbalanced panel data set that includes 53 countries observed over a 15-year period. Several significant economic, financial market, sociodemographic, cultural and institutional variables are identified. The results lead to a taxonomy of the root causes of underinsurance and a set of proposed measures to narrow the protection gap.

As an extension of the (univariate) Birnbaum–Saunders distribution, the Type-II generalized crack (GCR2) distribution, built on an appropriate base density, provides a sufficient level of flexibility to fit various distributional shapes, including heavy-tailed ones. In this paper, we develop a bivariate extension of the Type-II generalized crack distribution and study its dependency structure. For practical applications, three specific distributions, GCR2-Generalized Gaussian, GCR2-Student’s t, and GCR2-Logistic, are considered for marginals. The expectation-maximization algorithm is implemented to estimate the parameters in the bivariate GCR2 models. The model fitting results on a catastrophic loss dataset show that the bivariate GCR2 distribution based on the generalized Gaussian density fits the data significantly better than other alternative models, such as the bivariate lognormal distribution and some Archimedean copula models with lognormal or Pareto marginals.

In this paper, we introduce a bivariate extension of three-parameter generalized crack distribution for modelling loss data. Some basic properties such as the conditional distribution and the measures of association are discussed, and a method of parameter estimation is offered. A simulation-based approach to compute bivariate value-at-risk under the model is also discussed. The proposed model and estimation method are illustrated with a model fitting exercise on a real catastrophic loss data set.

PurposeThe purpose of this article is to investigate the impact of counterparty risk on the basis risk of industry loss warranties as well as on reinsurance with and without collateral under different dependence structures. The authors additionally compare the solvency and Sharpe ratio for different premium loadings and contract parameters.Design/methodology/approachThe authors propose a model framework extension to account for the counterparty risk of risk transfer arrangements. Copulas are used to also take into account non-linear dependencies between risk factors, and Monte Carlo simulation is employed to derive numerical results and to conduct sensitivity analyses.FindingsThe authors show that the impact of counterparty risk is particularly pronounced for higher degrees of dependencies and tail dependent losses, i.e. in cases of basis risk levels that appear low if counterparty risk is not considered. With respect to counterparty risk management, the authors find that already partial collateralization limits counterparty and basis risk to more acceptable levels.Practical implicationsThe study results are particularly relevant to practitioners, as insurers may not only underestimate the “true” basis risk of index-linked instruments, but also the effect of counterparty risk of reinsurance contracts along with the consequences for solvency and profitability.Originality/valueThe authors extend existing literature by allowing for the (partial) default of industry loss warranties and reinsurance under different dependence structures. Furthermore, the authors include profitability in addition to risk considerations. The interaction effects between counterparty risk and the basis risk of index-based alternative risk transfer instruments are largely unstudied, despite their considerable relevance in practice.

Following global catastrophic infrastructure loss (GCIL), traditional electricity networks would be damaged and unavailable for energy supply, necessitating alternative solutions to sustain critical services. These alternative solutions would need to run without damaged infrastructure and would likely need to be located at the point of use, such as decentralized electricity generation from wood gas. This study explores the feasibility of using modified light duty vehicles to self-sustain electricity generation by producing wood chips for wood gasification. A 2004 Ford Falcon Fairmont was modified to power a woodchipper and an electrical generator. The vehicle successfully produced wood chips suitable for gasification with an energy return on investment (EROI) of 3.7 and sustained a stable output of 20 kW electrical power. Scalability analyses suggest such solutions could provide electricity to the critical water sanitation sector, equivalent to 4% of global electricity demand, if production of woodchippers was increased post-catastrophe. Future research could investigate the long-term durability of modified vehicles and alternative electricity generation, and quantify the scalability of wood gasification in GCIL scenarios. This work provides a foundation for developing resilient, decentralized energy systems to ensure the continuity of critical services during catastrophic events, leveraging existing vehicle infrastructure to enhance disaster preparedness.

Modern civilization relies on a complex, globally interconnected industrial agriculture system to produce food. Its unprecedented yields hinge on external inputs like machinery, fertilizers, and pesticides, rendering it vulnerable to disruptions in production and international trade. Such a disruption could be caused by large‐scale damage to the electrical grid. Solar storms, nuclear detonations in the upper atmosphere, pandemics, or cyber‐attacks, could cause this severe damage to electrical infrastructure. To assess the impact of such a global catastrophic infrastructure loss on major food crops (corn, rice, soybean, wheat), we employ a generalized linear model. The predictions show a crop‐specific yield reduction between 15% and 37% in phase 1, the year after the catastrophe, assuming rationed use of fertilizers, pesticides, and fuel stocks. In phase 2, when all stocks are depleted, yields decrease by 35%–48%. Soybean is less affected in phase 1, while all crops experience strong declines in phase 2. Europe, North and South America, and parts of India, China, and Indonesia face major yield reductions, potentially up to 75%, while most African countries are less affected. These findings underscore the necessity for preparation by highlighting the vulnerability of the food system. Modern farming, dependent on machinery, fertilizer and pesticides, is at risk from electrical grid disruptions due to various catastrophes. Yields may drop 15%–37% in the first year and 35%–48% after industrial inputs run out, varying by crop. Europe, the Americas, and parts of Asia can see up to 75% yield reductions. Preparation is crucial.