Search Results (83)

(1) Background: Indonesia is one of the world’s largest consumers of asbestos, with widespread use of asbestos-cement roofing. Java Island, characterized by high population density and seismic vulnerability, presents a complex risk landscape for asbestos exposure. This study aimed to develop a district-level asbestos exposure risk map for Java by integrating asbestos roof prevalence, population density, and seismic hazard. (2) Methods: A descriptive, semi-quantitative approach was applied using secondary data from national statistics and geological hazard portals. Three variables—asbestos roof prevalence, population density, and seismic hazard—were categorized into five ordinal levels (very low to very high) and combined using GIS-based risk matrices to generate composite exposure risk maps. Sensitivity and statistical analyses were conducted to assess the robustness and internal consistency of the risk classification. (3) Results: Of 119 districts/municipalities, 43 (36%) were classified as very high risk and 45 (38%) as high risk under the primary GIS-based risk matrix classification. Major metropolitan corridors, including Greater Jakarta and Bandung, showed elevated risk where substantial asbestos use coincided with very high population density, whereas several southern and inland districts gained priority because of higher seismic hazard. Sensitivity analyses indicated that the classification was generally robust to moderate changes in weighting and threshold boundaries, although the predefined population density thresholds provided limited discrimination within Java. (4) Conclusions: Asbestos exposure risk in Java is both widespread and heterogeneous, shaped by the intersection of infrastructure, demographics, and seismic vulnerability. The map offers a practical tool for prioritizing asbestos control, public awareness campaigns, health surveillance, and disaster risk reduction measures in Indonesia. Full article

Indonesia is one of the world’s most seismically active countries, experiencing frequent earthquakes that make assessing regional resilience essential for disaster risk reduction. This study dynamically evaluates socioeconomic resilience in 28 regencies/municipalities affected by destructive earthquakes between 2016 and 2022. Resilience was quantified using the Adjusted Mazziotta–Pareto Index (AMPI) at three periods: pre-event (T₀), during the event (T₁), and post-event (T₂). Index changes were interpreted as resistance (Δ₁ = T₁ − T₀), recovery (Δ₂ = T₂ − T₁), and adaptive capacity (Δ₃ = T₂ − T₀). Results show substantial regional differences in resilience trajectories: some areas experienced only minor declines during the earthquake, while others were heavily affected but recovered quickly. Cluster analysis revealed distinct typologies, including consistently high-resilience regions, rapid-recovery regions, and persistently vulnerable regions. These disparities are associated with variation in economic capacity, social vulnerability, labor market conditions, and access to health services. Overall, the findings highlight the value of a multidimensional, time-sensitive approach to measuring socioeconomic resilience. The study advances an AMPI-based temporal measurement framework and offers policy insights for development planning and disaster mitigation. Full article

Natural disasters such as floods and earthquakes cause severe physical, social, and economic losses, highlighting the critical need for timely and reliable early warning systems. Conventional water level and structural health monitoring technologies are often costly, limiting deployment to high-priority infrastructure only. This paper presents the development and validation of two low-cost Internet of Things (IoT) systems for multi-hazard disaster monitoring and early warning, explicitly supporting UN Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure) and 11 (Sustainable Cities and Communities) by enabling equitable monitoring of rural or minor bridges. The proposed system achieves a significant cost reduction (approximately $300 compared to conventional systems typically exceeding $5000), highlighting its potential for scalable and sustainable deployment. The first system integrates a Raspberry Pi, Pi Camera, Lidar Lite V3, and ADXL355 accelerometer to simultaneously capture floodwater images, measure water levels, and record bridge vibrations, with distance measurements recorded at user-defined intervals and vibration data sampled up to 100 Hz. Laboratory repeatability and uncertainty analyses of the Lidar Lite V3 indicate a root mean square error of ~2.4 cm over a 0–25 cm range, demonstrating stable performance for flood monitoring and sufficient accuracy for early warning applications using low-cost sensing systems. The ADXL355 accelerometer is validated through harmonic excitation tests (0.1–2 Hz) and real earthquake recordings, confirming its suitability for low-frequency structural response monitoring. The second system combines a Raspberry Pi, an HX711 amplifier, and a CDP25 displacement transducer to measure bridge-bearing displacements up to 25 cm, with data acquisition at sampling rates of up to 80 Hz, with laboratory tests demonstrating consistent and repeatable measurements during both loading and unloading cycles. The IoT framework is resilient, incorporating solar power and local data storage to ensure operation during power or network outages. Unlike prior studies focusing on individual sensors, this work delivers a fully integrated multi-sensor platform with formalized early warning logic based on predefined thresholds. The results demonstrate the feasibility of scalable, real-time, low-cost monitoring for disaster risk reduction and infrastructure resilience, providing a sustainable solution for community-scale early warning applications. Full article

In March 2018, seismic events associated with rock salt mining in Maceió, northeastern Brazil, led to the emergency relocation of families from risk areas, resulting in increased companion animal abandonment. This study assessed the association between systematic monitoring and environmental education and the reduction in abandonment during these relocation processes. Between March 2018 and September 2020, 567 animals were recorded in affected households, of which only 245 (43.2%) were relocated with their guardians. In response, the Integra Animal Project was implemented, integrating environmental education, continuous monitoring, sanitary management, and population control. By December 2024, 2559 households and 6673 animals had been monitored. A substantial reduction in abandonment and escape rates was observed over time, with abandonment decreasing from 56.8% to 5.45%. Cats showed significantly higher escape rates than dogs (chi-square test). These findings suggest that integrated strategies combining monitoring and environmental education are associated with improved animal retention during disaster-driven relocation, supporting their relevance for animal welfare, public health, and One Health approaches. Full article

Low-altitude UAV scheduling and planning has become a critical technological pillar in disaster response systems; however, systemic challenges in complex environments and under uncertain risk conditions remain insufficiently understood. Although substantial progress has been achieved in model formulation and algorithm design in recent years, scheduling and planning frameworks still lack a systematic representation of key risk factors, such as meteorological disturbances, terrain damage, and communication constraints, thereby undermining operational safety and decision reliability. This study conducts a systematic review of low-altitude UAV scheduling and planning research over the past decade, covering representative disaster scenarios including forest fires, large building fires, earthquakes, floods, major public health emergencies, and traffic accidents. By comparatively analyzing scheduling objectives and technical pathways across the pre-disaster, during-disaster, and post-disaster stages, this paper summarizes the dominant research paradigms and limitations of multi-UAV coordination, air–ground coordination, and risk reduction-oriented scheduling and planning. This review reveals that existing approaches generally lack explicit modeling of dynamic risks and uncertainties, highlighting an urgent need to incorporate risk-aware considerations and reliability analysis frameworks into scheduling and planning to enhance the overall robustness and decision credibility of UAV systems in disaster environments. Full article

Background: Human health is closely interconnected to our ecosystem. Several studies found evidence that nature-based interventions improve mental health. Very recently, these approaches have started including mindfulness practices. Nature-based mindfulness interventions (NBMIs) combine contemplative practices with exposure to natural environments and are increasingly recognised as promising tools for supporting mental health and resilience within a One Health perspective, fostering physio-psychological wellbeing whilst promoting nature awareness and a sense of connection with our planet—“biofilia”, as defined by American biologist Edward Wilson. Given the growing psychological impacts of climate-related stressors, NBMIs may offer particular value for regions with high climate-risk and ecological vulnerability. Methods: A narrative literature review was conducted following established principles for high-quality non-systematic reviews. A non-systematic but structured search of PubMed, Scopus, Web of Science and Cochrane Library (January 2018–November 2025), complemented by grey literature, identified studies involving adolescents and adults participating in interventions integrating mindfulness practices with natural environments. Extracted data included study context, participant characteristics, intervention type, mental health and resilience outcomes. Results: Across heterogeneous designs, NBMIs consistently reduced stress, anxiety, depressive symptoms and rumination, while improving sleep, vitality, attention and self-regulation. Most studies reported enhanced nature connectedness—an important mediator of wellbeing and pro-environmental behaviour. Programmes delivered to disaster-affected populations showed reductions in distress. Conclusions: NBMIs are feasible, low-cost and adaptable interventions with dual benefits for mental health and ecological awareness. They offer promising One Health-aligned strategies for strengthening psychological resilience in climate-vulnerable regions, warranting further research and context-specific adaptation. Full article

Background: Quilombola communities, Afro-descendant Brazilian rural settlements with collectivistic culture, have suffered historical invasions and non-legalization of their territories, exposure to environmental degradation/hazards, and educational and health care deprivation by the government. Global climate changes have increased sea levels and the occurrence of floods. This study presents original empirical findings from ongoing qualitative fieldwork in Quilombola communities in Southern Brazil that were severely affected by the 2024 floods, focusing on post-disaster quality of life, health impacts, and community coping strategies. These dimensions remain underexamined in public health and environmental justice research. Methods: Guided by interdisciplinary frameworks of environmental racism, intersectionality, and critical disaster studies, flooding is analyzed not as a natural hazard, but as a socially produced risk shaped by racialized territorial exclusion, historical marginalization, and chronic governance failures. Data were generated by household testimonies, community observations, and assessments of governmental disaster responses. Results: Fragmented disaster management, unequal access to infrastructure, and limited participatory governance mechanisms intensified vulnerability, constrained adaptive capacity, and exacerbated health inequities among Quilombola populations. Despite these constraints, communities demonstrated strong resilience grounded in traditional knowledge, local solidarity networks, and collective agency. Conclusions: The study underscores the urgent need for equity-centered environmental governance and inclusive disaster risk reduction strategies to address healthy aging inequities. Full article

Coastal settlements in Bangladesh are geographically flood-prone areas. This physical nature erodes the size and shape of those settlement boundaries over time. Such changes leave communities vulnerable in terms of securing a living place and livelihoods. However, the research arena rarely addresses the long-term changing aspects of settlement and the local governance responses to vulnerability. To examine this situation, this study explored settlement transformation patterns and governance challenges, using the case study of Chattogram Division in Bangladesh from 2005 to 2025. It applied a mixed-methods approach. The analysis, using the technique of Multi-temporal Landsat imagery with Random Forest classification, revealed complex settlement trajectories. It showed built-up areas expanded significantly between 2005 and 2015 but shrank by 2025, reflecting both hazard exposure and displacement pressures. Union-level analysis identified 62 coastal unions with high to very high settlement change. Conducting field surveys in selected Juidandi and Kalamarchhara unions through focus group discussions with communities and interviews with local officials highlighted recurring inundation, permanent land loss affecting thousands of households, and persistent disruptions to livelihoods. This study also found moderate emergency responses in selected unions; however, strategic planning for relocation, health, and well-being of communities is insufficient. Continuous resource constraints and poor coordination with communities and line organizations made local implementation less effective, which blurs the effectiveness of disaster risk reduction policies. These findings underscore the necessity of union-level governance capacity building, integrating community-based adaptation with formal interventions, and developing spatially differentiated relocation strategies to enhance the resilience of climate-vulnerable coastal settlements. Full article

Intensive Care Units (ICUs) face unprecedented challenges in resource allocation, particularly during health crises in which algorithmic systems may be exposed to adversarial manipulation. A transformer-based expert system, ICU-Transformer, is presented to optimize resource allocation across 200 ICUs in Physionet while maintaining robustness against data poisoning attacks. The framework incorporates a Robust Multi-Head Attention mechanism that achieves an AUC-ROC of 0.891 in mortality prediction under 20% data contamination, outperforming conventional baselines. The system is trained and evaluated using data from the MIMIC-IV and eICU Collaborative Research Database and is deployed to manage more than 50,000 ICU admissions annually. A Resource Optimization Engine (ROE) is introduced to dynamically allocate ventilators, Extracorporeal Membrane Oxygenation (ECMO) machines, and specialized clinical staff based on predicted deterioration risk, resulting in an 18% reduction in preventable deaths. A Surge Capacity Planner (SCP) is further employed to simulate disaster scenarios and optimize cross-hospital resource distribution. Deployment across the Physionet ICU Network demonstrates improvements, including a 2.1-day reduction in average ICU bed turnover time, a 31% decrease in unnecessary admissions, and an estimated USD 142 million in annual operational savings. During the observation period, 234 algorithmic manipulation attempts were detected, with targeted disparities identified and mitigated through enhanced auditing protocols. Full article

Community-based organisations (CBOs) play a crucial role supporting clients during emergencies yet often lack adequate preparation. This study examined how Australian CBOs perceived and enacted dual responsibilities: ensuring service continuity during emergencies and facilitating person-centred preparedness for high-risk populations. A national cross-sectional online survey of community-based health and social care organisations was conducted between December 2021 and April 2022, employing strategic outreach and snowball sampling. Among 244 respondents, disability services (69%) and housing and homelessness services (27%) were the most common providers. Many organisations showed strong emergency preparedness, including comprehensive insurance, staff empowerment, and adaptive service delivery. Barriers to business continuity plans (BCPs) included resource constraints and limited emergency information access. Organisations with established networks and collaborations with emergency services demonstrated greater capacity for sustained service delivery (p < 0.001). Logistic regression analysis revealed local networking with emergency service agencies was positively associated with CBOs’ ability to support client preparedness (p < 0.001), while lack of tools (p = 0.007) and training (p = 0.037) limited capacity to facilitate person-centred emergency planning for high-risk populations. Embedding business continuity planning within operations and strengthening cross-sector collaboration can enable CBOs to fulfil their aforementioned dual responsibilities, while advancing sustainable organisational resilience and inclusive disaster risk reduction. Full article

The research on river and lake resilience management, ecological restoration, and disaster reduction technologies aims to comprehensively improve the health, stability, and sustainability of aquatic ecosystems. It seeks to reduce the natural disaster risk, promote the sustainable use of water resources, protect biodiversity, strengthen water ecological environment supervision, and advance the widespread practice of the green development concept. This study integrates remote sensing, geographic information system (GIS), and biological slope protection technologies, supported by investigation and geomorphological surveys, to achieve real-time monitoring and data analysis of river and lake ecosystems. Additionally, the application of innovative ecological restoration materials and technologies significantly improves restoration outcomes and operational efficiency. The construction of multi-level wetlands, combined with active community participation, further enhances ecological resilience and stability. Experimental results show that the river and lake resilience management structure increases the strength of slope protection by more than 1.5 times and improves the overall stability by more than 25%. These findings underscore the critical role of integrated ecological and engineering approaches in achieving sustainable development of river and lake ecosystems while effectively reducing the risks of natural disasters. Full article

Urbanization is rapidly transforming cities, especially in the Global South, with Sub-Saharan Africa expected to see the fastest growth in the next 30 years. In South Africa’s Mopani District, this urban expansion has led to the growth of informal settlements, increasing disaster risks related to water, health, and fire. This study focuses on Giyani Local Municipality, examining disaster risks in its informal settlements and the factors influencing the implementation of spatial planning tools. Using a SWOT analysis combined with the Analytical Hierarchy Process (AHP), the study found that while the municipality has strong land use and disaster management policies, poor enforcement, lack of integration, and weak governance limit their effectiveness. Opportunities for improvement include securing grants from the National Government and Disaster Management Centre to support disaster risk reduction (DRR) initiatives. However, challenges such as land shortages and ecological degradation threaten sustainable planning. The findings provide important insights for policymakers, urban planners, and disaster management professionals. The SWOT-AHP approach helps in prioritizing resource allocation, identifying risk trends, and focusing on key areas for mitigation. Overall, the study supports efforts to enhance resilience and promote sustainable urban development in informal settlements through better spatial planning. Full article

In early 2025, the Santorini–Amorgos area (Aegean Volcanic Arc, Greece) experienced a seismic swarm, with dozens of M ≥ 4.0 earthquakes and a maximum magnitude of M = 5.2. Beyond its seismological interest, the sequence was notable for triggering rare increased preparedness actions by Greek Civil Protection operational structures in anticipation of an imminent destructive earthquake. These actions included (i) risk communication, (ii) the reinforcement of operational structures with additional personnel and equipment on the affected islands, (iii) updates to local emergency plans, (iv) the dissemination of self-protection guidance, (v) the activation of emergency alert systems, and (vi) volunteer mobilization, including first aid and mental health first aid courses. Although it was in line with contingency plans, public participation was limited. Volunteers helped bridge this gap, focusing on vulnerable groups. The implemented actions in Greece are also compared with increased preparedness during the 2024–2025 seismic swarms in Ethiopia, as well as preparedness before the highly anticipated major earthquake in Istanbul (Turkey). In Greece and Turkey, legal and technical frameworks enabled swift institutional responses. In contrast, Ethiopia highlighted the risks of limited preparedness and the need to embed disaster risk reduction in national development strategies. All cases affirm that preparedness, through infrastructure, planning, communication, and community engagement, is vital to reducing earthquake impacts. Full article

Global warming and ozone layer depletion signal the onset of climate change, a “slow-onset” disaster exacerbating poverty and social inequality. Addressing this requires global cooperation, as exemplified by the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 13, which focuses on climate action. Mitigation measures include reducing greenhouse gas emissions, transitioning to clean energy, and enhancing community resilience. Social workers play a crucial role in climate change adaptation, engaging in community resilience, advocacy, and policy influence. Their work spans individual counseling, social protection, and addressing environmental refugee crises. As climate change impacts intensify, social workers must expand their roles internationally, advocating for human rights, social justice, and disaster risk reduction. Human rights frameworks guide social workers in addressing climate-related health and social inequalities, emphasizing empowerment and equity. International social workers contribute significantly to disaster response, pandemic recovery, and community resilience, advocating for vulnerable populations and promoting sustainable development. Their evolving role underscores the need for a comprehensive, transnational approach to social protection, ensuring equitable access to resources and fostering a more just and resilient global community. Full article

Monitoring and evaluation of soil ecological environments are very important to ensure saline–alkali soil health and the safety of agricultural products. It is of foremost importance to, within a regional ecological risk-reduction strategy, develop a useful online system for soil ecological assessment and prediction to prevent people from suffering the threat of sudden disasters. However, the traditional manual or empirical parameter adjustment causes the mismatch of the hyperparameters of the model, which cannot meet the urgent need for high-performance prediction of soil properties using multi-dimensional data in the WebGIS system. To this end, this study aims to develop a saline–alkali soil ecological monitoring system for real-time monitoring of soil ecology in the Yellow River Delta, China. The system applied advanced web-based GIS, including front-end and back-end technology stack, cross-platform deployment of machine learning models, and a database embedded in multi-source environmental variables. The system adopts a five-layer architecture and integrates functions such as data statistical analysis, soil health assessment, soil salt prediction, and data management. The system visually displays the statistical results of air quality, vegetation index, and soil properties in the study area. It provides users with ecological risk assessment functions to analyze heavy metal pollution in the soil. Specially, the system introduces a tree-structured Parzan estimator (TPE)-optimized machine learning model to achieve accurate prediction of soil salinity. The TPE–RF model had the highest prediction accuracy (R² = 94.48%) in the testing set in comparison with the TPE–GBDT model, which exhibited a strong nonlinear relationship between environmental variables and soil salinity. The system developed in this study can provide accurate saline–alkali soil information and health assessment results for government agencies and farmers, which is of great significance for agricultural production and saline–alkali soil ecological protection. Full article