Search Results (117)

Background: Yellow fever vaccination is recommended for travelers visiting endemic regions in South America and Africa. The live-attenuated vaccine (Stamaril^®, Sanofi Pasteur) is produced in embryonated chicken eggs and contains residual ovalbumin, posing a challenge for individuals with egg protein allergy. Case Presentation: We report the case of a 35-year-old male disaster relief worker with confirmed egg protein allergy and moderate sensitization but no history of anaphylaxis. Under normal circumstances, a statement confirming that vaccination is not possible would be sufficient for entry. However, due to his work-related duties and the relevant guidelines from his employer, there was an urgent need for vaccination despite his egg protein allergy. A comprehensive allergy work-up including skin prick testing, serum-specific IgE, and oral provocation testing revealed a moderate allergy without systemic reactions. Intervention: Following informed consent and risk assessment, a fractional dose (0.1 mL) of the reconstituted yellow fever vaccine was administered under close monitoring. The patient developed a localized dermal reaction without systemic symptoms. Post-vaccination neutralization testing confirmed seroconversion indicating protective immunity. Discussion: Although yellow fever vaccination is considered contraindicated in individuals with severe egg protein allergy, the literature supports its cautious use in selected cases. Fractional dosing has emerged as an effective dose-sparing strategy. Studies show that even in egg protein-allergic individuals, adverse events are rare. Conclusions: In this case, a fractional yellow fever vaccination was safe and an effective option for an egg-allergic individual in a high-risk occupational setting, supporting a personalized approach based on clinical risk assessment and current evidence. Full article

Residential satisfaction serves as a critical metric for lived resilience, reflecting the sustained functionality of sociospatial systems. However, its long-term evolution in post-disaster, rapidly urbanizing landscapes remains under-researched. This study evaluates sociospatial dynamics in İzmit, Turkey, nearly three decades after the 1999 İzmit Earthquake, analyzing how urbanization trajectories shape resilience outcomes. Grounded in a bottom-up spillover model, the research utilizes a Structural Equation Modeling (SEM) framework to analyze resident survey data, complemented by a spatial “sections-based” analysis to capture intraurban variability across distinct development processes. Social capital emerged as the strongest predictor of residential satisfaction, potentially acting as a compensatory mechanism in deprived neighborhoods, despite physical deficiencies. Findings revealed profound sociospatial heterogeneity in long-term urban recovery. Paradoxically, contemporary mass housing exhibited lower satisfaction scores than older informal developments, challenging the assumption that formal planning and modern construction inherently guarantee sustained resilience. By utilizing residential satisfaction to interpret uneven lived resilience across urbanization trajectories, this study advocates for prioritizing the most influential quality domains through targeted interventions. These insights move beyond technical recovery metrics to offer a transferable framework for disaster-prone cities seeking to align institutional planning goals with the actualized residential satisfaction of communities. Full article

Background: Adolescents are particularly vulnerable to psychological distress following natural disasters, especially in low-resource settings. This study examined the short-term psychosocial outcomes associated with Narrative Drawing Intervention (NDI), a structured, trauma-informed, school-based group counselling program integrating expressive drawing and guided narrative reflection, among students affected by an earthquake in rural western China. Methods: Using a quasi-experimental design, 30 trained educators facilitated eight NDI group sessions for 150 students. Of the 120 students who completed the intervention, a randomly selected subset completed standardized psychological assessments. The final analyzed sample included 64 participants (44 intervention; 20 control). Results: The intervention group demonstrated significant reductions in anxiety (p = 0.011, d = 0.40) and PTSD symptoms (p = 0.008, d = 0.42), with a reduction in stress approaching statistical significance (p = 0.063, d = 0.29). In contrast, the control group showed significant increases in anxiety, stress, and PTSD symptoms over the same period. Depressive symptoms did not significantly change in either group. Descriptive drawing comparisons indicated increased visual elaboration and more centralized figure placement following the intervention. Conclusions: Within the context of a quasi-experimental and exploratory design, the findings provide preliminary support for the feasibility of NDI and suggest potential short-term psychosocial benefits in post-disaster school settings. While baseline group differences and the lack of randomization suggest the need for further investigation, the results provide a foundation for future randomized and longitudinal studies that further examine causal pathways and the sustainability of observed effects. Full article

Timely landslide detection and rapid qualitative assessment are fundamental to effective warning systems, hazard management, and risk mitigation. Yet, current practices that rely on on-site surveys and manual expert assessment remain risky, costly, and time-consuming. These limitations result in substantial delays between the event and the availability of actionable information. This study proposes a hybrid, multi-model framework that fuses RGB remote-sensing imagery with geospatial layers to enable timely landslide detection and actionable reporting. The pipeline couples an enhanced SegFormer (denoted as SDF-SegFormer-B2) model for landslide localization, a feature extraction technique for per-slide geo-attribute computation, and a lightweight instruction-tuned LLM (Mistral-7B-Instruct-v0.3) for structured, expert-style reporting. Although a few previous studies have explored landslide captioning, to our knowledge this is the first framework designed to generate structured technical reports enriched with terrain-context interpretation and qualitative intervention-priority indicators. Experiments use 26,758 georeferenced RGB tiles (64 × 64) with 3 m of spatial resolution from PlanetScope satellite imagery over Emilia–Romagna, Italy, with 68,592 annotated landslide boxes collected after the May 2023 rainfall events (~200 mm in 48 h on 1–3 May; 200–250 mm in 48 h on 16–17 May). The proposed SDF-SegFormer-B2 segmentation model achieved a precision of 85.54%, recall of 72.31%, and an F1-score of 78.39% on the unseen test dataset. To evaluate the quality of the generated landslide reports, 100 images were selected for domain-expert assessment. Among these, 58% of the reports were rated as “Very Good,” 30% as “Good,” 8% as “Acceptable,” and 4% as “Poor.” When considering only reports with complete and accurate inputs, 81.48% were rated “Very Good,” and 96.30% were rated either “Good” or “Very Good.” By integrating complementary models and modalities, the proposed approach automates localization-to-reporting and enables the generation of terrain-aware landslide summaries that may support preliminary decision-making and rapid post-disaster screening. Full article

Climate change has intensified the frequency and severity of meteorological disasters, posing significant challenges to the resilience and adaptability of port-centric transport networks (PCTNs) and global trade stability. Unlike previous studies that adopt generalised resilience frameworks or treat disaster types uniformly, this study develops a disaster-specific, integrated assessment framework whose novelty lies in coupling three complementary methods, each playing a distinct role: (i) integer programming optimises post-disaster recovery decisions under budgetary constraints by selecting cost-effective measures that maximise re-stored container-handling capacity; (ii) Monte Carlo simulation (10,000 iterations) captures the stochastic nature of meteorological disruptions and quantifies probabilistic resilience under typhoons, storm surges, and heavy fog; and (iii) an Analytic Hierarchy Process–Evidence Reasoning (AHP–ER) hybrid integrates subjective expert judgement with objective field data to evaluate adaptability across a four-level indicator system, thereby reducing the subjectivity of conventional multi-criteria approaches. Applied to Shanghai Port, the framework yields normalised resilience scores on a [0, 1] scale, where 1.0 denotes full operational continuity (network throughput equals demand) and values below 0.80 indicate substantial disruption requiring urgent intervention. Heavy fog produces the lowest score (0.73, ‘moderate-to-severe disruption’), followed by typhoons (0.81, ‘mild disruption’) and storm surges (0.89, ‘near-normal operation’), revealing that low-visibility events—not high-energy storms—pose the dominant operational threat at Shanghai Port. Translating these findings into practice, the study recommends the following: (1) deploying real-time visibility-monitoring (LiDAR) and AI-driven traffic-scheduling systems to mitigate fog-related disruptions; (2) reinforcing gantry-crane anchoring and prepositioning emergency power supplies in typhoon-prone berths; (3) prioritising hinterland-port handling redundancy in Jiangsu and Anhui sub-networks (adaptability scores 0.639 and 0.642); and (4) piloting an integrated Shanghai–Zhejiang cross-regional emergency-response corridor with shared berthing rights and standardised joint drills. These targeted, quantitatively grounded recommendations offer port authorities and policymakers an evidence base for prioritising infrastructure investment and organisational reform to safeguard global supply chains against escalating climatic threats. Full article

Post-earthquake emergency response planning requires rapid and adaptive resource allocation under disrupted accessibility, uneven district-level demand, and hazardous field conditions. In large metropolitan areas, these challenges are intensified by spatial differences in social vulnerability, infrastructure disruption, operational feasibility, and responder exposure. Static allocation approaches are often insufficient in such environments because they cannot adequately reflect temporal change or the evolving relationship between urgency, accessibility, and operational risk. This study proposes a dynamic multi-objective model for district-level post-earthquake resource allocation that integrates social vulnerability, occupational safety, and Markov-based updating within a single analytical framework. First, district priority scores are derived through an Analytic Hierarchy Process based on building damage ratio, intervention time, social vulnerability, critical infrastructure damage, secondary hazard risk, team capacity, and occupational safety. Second, a Markov-based updating mechanism is used to represent time-dependent redistribution across response periods. Third, a constrained weighted-sum multi-objective optimization model is formulated to balance district priority, social vulnerability, and responder safety under capacity and accessibility limits. The model is applied to Istanbul using official district-level data from national and local institutional sources. Scenario-based analysis is conducted under balanced, priority-oriented, vulnerability-oriented, and safety-oriented settings, together with static and dynamic model comparisons. The results show that the dynamic structure produces a more adaptive allocation profile than the static structure, with the share of the Very High allocation class declining from 37.66% to 34.95% and the Low allocation class increasing from 12.89% to 16.00% over the response horizon. The findings also indicate that greater emphasis on social vulnerability shifts allocation toward more fragile districts, whereas stronger safety emphasis reduces cumulative operational exposure at the cost of moderate reductions in immediate coverage. Overall, the study contributes to the disaster response literature by linking multi-criteria district prioritization, dynamic redistribution, and safety-aware allocation within a unified district-level decision structure. Beyond the Istanbul application, the proposed framework offers a practical basis for more responsive, equitable, and operationally sustainable post-earthquake planning in complex urban environments. Full article

Post-earthquake reconstruction involves complex decision-making that extends beyond structural safety to include economic, environmental, and social considerations under conditions of uncertainty and limited resources. Although sustainability-oriented assessment frameworks and multi-criteria decision-making approaches have increasingly been applied in disaster contexts, existing models typically address localized technical interventions and rarely support strategic reconstruction planning after earthquakes. This study develops a sustainability-based decision-support framework for post-earthquake reconstruction of reinforced concrete buildings using the Integrated Value Model for Sustainability Assessment (MIVES). This framework is derived through a systematic synthesis of the post-earthquake, post-disaster, and MIVES-based literature. Reconstruction alternatives reported in previous studies are first identified and classified to structure the reconstruction decision space. Sustainability requirements, criteria, and indicators are then examined and adapted through processes of retention, modification, elimination, and addition. The principal outcome of the study is an adapted MIVES requirements tree composed of 10 criteria and 19 indicators organized across the sustainability dimensions, providing a context-consistent hierarchical structure for strategic building-level reconstruction decisions. By explicitly linking reconstruction alternatives with sustainability indicators within clearly defined decision boundaries, the framework strengthens methodological rigor in sustainability-oriented reconstruction planning. The present article focuses on the methodological development of the framework (Part I). The operational implementation of the model—including expert-based weighting, value-function definition, indicator aggregation, and empirical validation through case studies—will be presented in a companion study. The proposed framework provides a transparent and transferable basis for sustainability-oriented reconstruction planning and supports informed decision-making by public authorities. Full article

Background: Older adults are highly vulnerable to adverse psychological outcomes following large-scale disasters. Social micro-communities are often assumed to play a protective role in post-disaster recovery. This study examined the association between perceived micro-community support and psychological outcomes among older adults after the 2023 earthquakes in Malatya, Türkiye. Methods: This cross-sectional study included 287 community-dwelling adults aged 60 years and older from the Battalgazi and Yesilyurt districts. Data were collected through face-to-face interviews using a sociodemographic form, the Multidimensional Scale of Perceived Social Support, the Warwick–Edinburgh Mental Well-Being Scale, and the Satisfaction with Life Scale. Non-parametric statistical analyses were applied. Results: Younger participants reported significantly higher perceived social support and psychological well-being (p < 0.05). Male and married participants demonstrated greater life satisfaction (p < 0.05). Educational status was significantly associated with family support and total perceived social support (p < 0.05). Although most participants perceived micro-communities as important, perceived importance was not significantly associated with psychological well-being or life satisfaction. Health problems and economic hardship were the most common post-disaster stressors. Conclusions: Informal social support alone may be insufficient to promote psychological recovery among disaster-affected older adults. Targeted community-based interventions addressing health and socioeconomic needs are required. Full article

Tourism destinations exposed to chronic natural hazards require robust analytical frameworks to understand and prioritize the factors that sustain post-disaster resilience. This study examines Baños de Agua Santa (Ecuador), a volcano-exposed destination whose long recovery trajectory illustrates the complexity of socio-ecological adaptation. Using a multidimensional FAHP model grounded in expert judgments, eight dimensions and fifty-six criteria were evaluated through fuzzy triangular numbers and the extended analysis method of Chang to capture uncertainty and ambiguity in decision-making. Results show a consistent and hierarchical structure of resilience, with experiential, economic-entrepreneurial, and socio-community dimensions emerging as the most influential drivers of post-disaster adaptability. Fifteen criteria—primarily perceptual, community-based, and endogenous—achieved “very high impact” status, including risk perception, basic education, individual resilience capacities, institutional coordination, and entrepreneurial environment. Conversely, limited healthcare infrastructure, low economic diversification, and national-level vulnerabilities were identified as critical weaknesses. The study concludes that post-disaster recovery in Baños is shaped by a bottom-up dynamic that emphasizes agency, learning and socio-ecological memory. It also proposes an evidence-based Action Matrix for adaptive governance to guide prioritized, time-phased interventions. The FAHP model proves effective for transparent, context-sensitive prioritization in highly uncertain tourism environments. Full article

The transformation of public spaces to meet the need for shelter in the post-disaster situation is a practice observed in many countries. However, these temporary alterations are meticulously planned and executed within a defined timeframe following the disaster. This approach hinders the effective utilization of available space. The objective of the study is to reach design decisions by determining the adaptive use potential of sports facilities for temporary shelter in the post-disaster process. In addition, the study will reveal which adaptability strategies can be used to adapt spaces with different functions. The design decisions are reached by comparing sports facilities and temporary shelter needs programs based on eleven adaptability strategies (adjustability, versatility, transformability, scalability, portability, flexibility, expandability, dismountability, reuse, modularity, independence). The conversion of sports facilities into temporary shelters was achieved by employing adaptability strategies, thereby demonstrating the potential for a space with 15 different functions to undergo transformation. A transformability strategy has been employed, whereby changing rooms have been converted into laundry rooms, and grandstands into training areas. A scalability strategy has been employed to facilitate the reuse of cafe-restaurant areas as dining halls. The transformation of the playground into sleeping areas is facilitated by strategies of portability and dismountability. Flexibility and expandability strategies are employed in the transition from the first aid room to the infirmary area. A reuse strategy is employed for administrative units, parking areas, restrooms and prayer areas, ensuring that spaces with similar needs are utilized with minimal intervention. By examining a range of adaptability strategies, analogous adaptability applications can be developed for other public spaces. The study contributes a transferable, criteria-driven framework that supports decision-making for the adaptive reuse of public buildings in post-disaster contexts, offering a structured basis for extending similar transformations to other building typologies. Full article

Extreme natural disasters raise a fundamental question for biologically rigid food production systems: does post-disaster productivity recovery stem from technological change or from adaptive reorganization within existing constraints? In inland aquaculture, where biological processes, fixed production cycles, and capital requirements severely limit short-run technological upgrading, this distinction is particularly critical. Using two post-earthquake time points (2023 and 2025), the analysis documents productivity and efficiency patterns rather than causal recovery trajectories. Accordingly, the analysis is explicitly descriptive and does not attempt to identify causal recovery mechanisms or long-run productivity dynamics. Adaptive efficiency is not directly measured in this study; rather, the term is used as an interpretative construct to describe efficiency changes that are consistent with adaptive behavior under post-disaster constraints. This study examines productivity patterns observed during the post-earthquake period in inland trout aquaculture following the 6 February 2023 earthquake in Eastern Türkiye, with a particular focus on adaptive efficiency as a recovery-consistent mechanism. Using a balanced panel of 290 inland trout farms observed during the immediate post-earthquake adjustment period (2023) and a subsequent recovery phase (2025), the analysis integrates bias-corrected Data Envelopment Analysis, Malmquist productivity decomposition, and resilience-oriented truncated regression. Recovery dynamics are examined conditional on farm survival, allowing within-farm adaptive adjustment to be distinguished from exit-driven selection effects. The results indicate that productivity recovery was driven predominantly by improvements in technical efficiency, while technological change remained close to unity across provinces, suggesting short-run production frontier stability. This pattern is consistent with delayed or constrained investment behavior under heightened uncertainty rather than with technological stagnation. This interpretation is not unique and should be read as one plausible mechanism among several, rather than as a definitive explanation of observed frontier stability. Farms primarily restored performance through operational reorganization, input coordination, and scale adjustment within existing biological and technological constraints, rather than through innovation. Second-stage results further show that the coefficient on access to liquidity is positive, while higher mortality rates and greater distance to markets are systematically associated with weaker post-disaster adjustment. Overall, the findings indicate that short- to medium-term productivity patterns in biologically rigid inland aquaculture systems are governed primarily by efficiency changes consistent with adaptive efficiency rather than technological change. From a policy perspective, post-disaster aquaculture recovery strategies should prioritize liquidity support, biological continuity, and operational stability over premature technology-push interventions. The analysis is based on two post-disaster observation points (2023 and 2025), which allows identification of short- to medium-term recovery-consistent patterns but does not permit causal or long-run inference. Full article

COVID-19 lockdown announcements triggered global waves of panic buying, leading to widespread panic buying of essential goods and supply chain disruptions. Although the acute phase of the pandemic has passed, panic buying continues to emerge during natural disasters, extreme weather events, and other crisis-related disruptions, highlighting the ongoing need for evidence-based strategies to address its psychological drivers. Social cognition constructs, including willingness, intentions, attitudes, subjective norms, and risk perceptions, have been identified as modifiable psychological predictors of panic buying. However, few studies have experimentally tested theory-driven interventions aimed at modifying these mechanisms. This study evaluated the effectiveness of a brief, online intervention based on integrated social cognition models in reducing panic-buying-related cognitions during a hypothetical lockdown scenario. A pre-registered randomized controlled trial was conducted with Australian grocery shoppers (N = 140), who were randomly allocated to an intervention or control condition. Participants completed self-report measures assessing their willingness, intentions, attitudes, subjective norms, and risk perceptions at both pre- and post-intervention times. The hypotheses were partially supported. Compared with the control condition, the intervention group reported greater reductions across targeted psychological constructs. For hygiene products, significant decreases were observed across all five constructs, and for non-perishable foods, willingness, intention, and attitudes significantly decreased. For cleaning products, reductions were evident for attitudes, subjective norms, and intentions. These findings suggest that theory-informed, scalable interventions can effectively modify the social cognition processes underlying panic buying. This study extends existing research and demonstrates the potential for brief, theory-based communication strategies to reduce panic-buying-related cognitions. Future research should evaluate these interventions in real-world settings and explore mechanisms to target automatic cognitive processes. Full article

Post-disaster temporary housing units (PDTHUs) are crucial to the rebuilding process after disasters; however, current designs fall short in several areas, including user comfort, contextual relevance, and long-term flexibility. This situation suggests that design weaknesses emerge through interactions among multiple factors, requiring an analytic approach that goes beyond isolated evaluation. This study aims to (1) identify the main design issues in PDTHUs, (2) explore the relationships among these issues, and (3) prioritize interventions by grouping causes for decision makers. First, eleven primary design problems were identified through a systematic literature review. Next, a matrix-based questionnaire was developed and administered to five experts with experience in post-disaster projects. In the third stage, expert opinions were analyzed using the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method. As a result, the design problems were classified into “cause” and “effect” groups, and a cause-and-effect diagram was created. The findings indicate that the lack of contextual and cultural integration in design (4.485); the absence of pre-disaster planning and prototyping (3.964); and low thermal, acoustic, and ergonomic comfort (3.385) are the most influential issues because they belong to “cause groups” with high Pi values. This study provides a guiding framework for practitioners and policymakers to allocate resources efficiently, plan strategically, and develop context-sensitive designs. Full article

The impact of physical health conditions on coronavirus disease of 2019 (COVID-19) severity in World Trade Center disaster-exposed populations remains understudied. We examined the association of type, number and diagnosis time of pre-existing health conditions with COVID-19 severity, using the WTC Health Registry (WTCHR). We analyzed 3568 WTCHR enrollees with self-reported severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a 2021 follow-up survey. COVID-19 severity was measured by self-reported symptom duration (<2, 2–4, and >4 weeks) and hospitalization (hospitalized versus not). Pre-existing gastroesophageal reflux disease (GERD), respiratory conditions, cardiovascular conditions, and diabetes were self-reported and categorized into four groups (no diagnosis, post-9/11, pre-9/11, and undefinable). We used multinomial logistic regression and binary logistic regression to analyze the association of comorbidities with COVID-19 symptom duration and hospitalization, respectively, adjusting for post-traumatic stress disorder and demographic factors. Analysis was also conducted separately by enrollee type: rescue and recovery workers (RRW) vs. community members (non-RRW). Having all four health conditions post-9/11 was associated with longer symptom duration after SARS-CoV-2 infection (>4 weeks) among RRW (AOR: 2.66, 95% CI: 1.03–6.87). Reporting a post-9/11 respiratory condition was associated with an increased risk of being hospitalized among RRW and an increased risk of longer symptom duration (>4 weeks) among non-RRW. While post-9/11 diabetes was associated with an increased risk of longer symptom duration among RRW, post-9/11 GERD and pre-9/11 cardiovascular conditions were associated with an increased risk of longer symptom duration and being hospitalized among non-RRW, respectively. The impact of certain health conditions on COVID-19 severity varied across enrollee types and time of diagnosis. Given the lasting health impacts of 9/11-related exposures, targeted medical surveillance and proactive healthcare interventions are critical for mitigating the risk of severe COVID-19 illness in this population. Full article

Background: The 2022 Pakistan floods devastated healthcare access for pregnant women in already impoverished areas in Sindh province. This study examines how Cash for Health assistance (CH) of USD 112 alleviated financial burdens and improved maternal health outcomes and resilience, bridging a critical literature gap on cash effectiveness in humanitarian crises. Methodology: This study used a mixed-methods approach to assess the CH assistance intervention for families of pregnant/lactating women in flood-affected rural Sindh, Pakistan. A pre-post quantitative analysis of baseline (May–June 2024) and endline (August–November 2024) survey data in ~100 villages (Jamshoro/Sehwan) examined changes in healthcare access, expenditure, and preferences using t-tests, proportion tests, and multivariable regression. Concurrently, five qualitative case studies from key informant interviews provided thematic content analysis, triangulating findings on economic, health, and social impacts. Results: Respondents predominantly had low literacy rates and were from households of daily wage laborers in vulnerable, flood-affected areas. While income and education remained low, instances of forgone care due to financial barriers increased (68% to 97%, p < 0.001). CH significantly improved healthcare access (58% to 98%, p < 0.001). Access to regular physicians (20% to 69%) and private facilities (10% to 41%) notably expanded. Healthcare expenditure significantly increased from USD 9.3 to USD 25, with a shift in spending preference towards medication, consultations, and diagnostics. CH also significantly improved food security (21% to 97%), meal frequency, and overall household stability, including reducing domestic violence. Qualitative data emphasized pre-existing vulnerabilities and CH’s role in addressing health, nutrition, and psychosocial needs. Conclusions: CH significantly improved healthcare access and reduced financial burdens for vulnerable pregnant women post-disaster. However, a sustainable impact requires integrated “cash plus” models, combining financial aid with stronger health systems, psychosocial support, and literacy for long-term resilience. Full article