Indonesia is a country with high seismic activity due to its location at the convergence of three major tectonic plates. This condition creates a strong need for earthquake pattern analysis and magnitude prediction to support disaster mitigation. This study aims to cluster earthquake data using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and to predict earthquake magnitude using the Random Forest algorithm optimized through hyperparameter tuning. The Indonesian earthquake dataset was obtained from Kaggle with a total of 92,887 valid entries. The DBSCAN clustering results revealed several active seismic zones, particularly in Sumatra, Java, Sulawesi, and Papua. The comparison of R² between the Baseline Random Forest and the Tuned Random Forest shows a significant improvement after the parameter tuning process. The Tuned Random Forest model achieves an R² value of 0.478, which is higher than the Baseline Random Forest's 0.442. This indicates that the tuned model is better able to explain the variance in the data and provides more accurate predictions.

Predicting extreme rainfall is crucial for supporting planning in the agricultural sector, infrastructure development, and disaster mitigation in the city of Bogor. However, the asymmetric distribution of daily rainfall and the presence of outliers make linear regression methods less suitable. Quantile regression offers an alternative that captures the influence of explanatory variables across different parts of the data distribution, particularly in the extreme regions. This study compares the Simplex and Nelder-Mead methods for estimating quantile regression parameters on extreme rainfall data in Bogor. Daily rainfall data were obtained from the West Java BMKG Climate Station for the period from May 2024 to April 2025, comprising 365 observations, with four explanatory variables: average temperature, average humidity, sunshine duration, and average wind speed. Modeling was conducted at the 0.75, 0.85, and 0.95 quantiles to represent extreme rainfall. The results show that the Simplex method outperformed Nelder-Mead, as indicated by lower Pinball Loss and Mean Absolute Error (MAE) values at most quantiles. Humidity and average wind speed had a significantly positive effect on extreme rainfall intensity, while average temperature had a negative effect. Sunshine duration showed less consistent effects. Overall, the Simplex method is recommended for quantile regression optimization in extreme rainfall data due to its greater stability and accuracy in generating model parameters. However, this study is limited by the number of explanatory variables and the relatively short observation period. Incorporating additional variables such as air pressure, ENSO index, or topographical data, along with extending the observation period, could improve model accuracy and generalizability in future research.

This community service activity aims to enhance community capacity for flood disaster mitigation in Tambakrejo Village, Semarang City, through strengthening the management of the Early Warning System (EWS). Tambakrejo is a coastal area vulnerable to floods and tidal inundation due to land subsidence and sea level rise. The main problems include low community preparedness and suboptimal management of the existing EWS. The implementation method involved training, mentoring, and the development of Standard Operating Procedures (SOP) for the local Disaster Preparedness Group (KSB) as the main partner, carried out through stages of socialization, capacity building, implementation, and evaluation. The results showed improved knowledge and skills of KSB members in operating and maintaining the EWS device, along with the creation of a management SOP serving as an operational guide at the community level. This activity demonstrates that community capacity building through participatory and technology-based approaches can strengthen disaster mitigation systems and enhance community preparedness against flood risks in coastal areas.

This study aims to determine the effect of using disaster mitigation guidebooks on increasing the knowledge of the school community and its contribution to optimizing the implementation of SPAB at SMAN 6 Kota Bekasi, particularly in the third pillar, namely disaster risk reduction and prevention education. Initial observations showed that the SPAB optimization level was 63% (almost optimal), with the third pillar at 50% (less optimal). The focus was directed to this pillar due to its strategic role in shaping the knowledge and preparedness of the school community. This study used a quantitative approach with a pre-experimental method of one-group pre-test and post-test design, involving 57 respondents. Data were obtained through knowledge tests on flood and earthquake mitigation. The results showed an increase in the average score from 59.74 (pre-test) to 84.91 (post-test), with a difference of 25.17 points. The paired sample t-test produced a significance value of 0.000 (<0.05), thus the alternative hypothesis (Hₐ) was accepted, meaning that the use of the guidebook had an effect on increasing the knowledge of the school community. After the intervention, the optimization level of the third pillar increased to 83% (highly optimal) and contributed to the increase of the overall SPAB score to 68% (optimal). Therefore, the use of the guidebook was proven to have an effect in improving disaster mitigation knowledge and supporting the success of the SPAB program at SMAN 6 Kota Bekasi.

In recent years, global sea surface temperature (SST) has risen steadily, with 2023 and 2024 breaking successive historical observation records, thus rendering marine heatwaves (MHWs) an unignorable new marine disaster. To scientifically mitigate and assess the impacts of MHW disasters on China’s coastal waters, this study developed a monitoring and weekly forecast product for MHWs based on the OSTIA (Operational SST and Ice Analysis) SST observational fusion data and SST numerical forecast data. Evaluation shows the following: the quarterly average of the RMSE for the weekly MHWs intensity forecasts is 0.52 °C; and the quarterly average score for the weekly MHW’s category forecasts is 94.4. Characteristic analysis of 2024 MHWs reveals 93.7% of China’s coastal waters and adjacent areas experienced MHWs throughout the year, and the average monthly impact rate of MHWs is 43.8%. High-value areas of total days and cumulative intensity are concentrated in the central-eastern part of the Yellow Sea, which makes it the most severely affected area by MHW disasters in 2024. The weekly MHW’s forecast product developed in this study provides deterministic weekly forecasts of MHWs intensity and categories for China’s coastal waters. This product can serve as a guidance basis for MHW disaster prevention and mitigation, and help reduce losses caused by MHWs to the marine environment and marine economy.

Abstract Payments to ameliorate disaster damages are typically provided through public assistance programs or insurance. For large-scale natural hazard disasters, governments have historically played a major role in providing this assistance, especially as comprehensive private disaster insurance coverage can rarely be sustained over time. In Switzerland, New Zealand, and Spain, publicly owned disaster insurance schemes were established as early as a hundred years ago. Currently, with an increasing risk of climate change–related disasters, private insurance retreat is happening more frequently in more places, and the need to devise sustainable public disaster insurance (PDI) systems is gaining policy attention. Useful lessons can be extracted from analysing the processes that have led to the establishment of existing PDIs. Using a narrative review, we describe the process of PDI establishment and identify recurrent themes associated with this process, including the incentives involved, role of risk knowledge, government deliberations, legislative proposals, and associated changes in disaster mitigation policies. We analyse the main implications of these past experiences for current and future transitions to PDI systems following private insurance retreat and explore what is still missing in our knowledge about PDIs’ performance.

With the accelerating pace of urbanization, cities are increasingly affected by rainstorm and flood disasters, which pose severe threats to the safety of residents’ lives and property. Existing models are increasingly inadequate in meeting the accuracy requirements for flood simulation in highly urbanized regions. Thus, it is urgent to develop a new method for flood inundation simulation based on high-resolution urban hydrological units. The novelty of the model lies in the novel structure of the high-resolution Urban Hydrological Units model (HRGM), which replaces coarse sub-catchments with a fine-grained network of urban hydrological units. The primary innovation is the node-based coupling strategy, in which the HRGM provides precise overflow hydrographs at drainage inlets as point sources for LISFLOOD-FP, rather than relying on diffuse runoff inputs from larger areas. In this paper, a high-resolution hydraulic model (HRGM) based on urban hydrological units coupled with a 2D hydrodynamic model (LISFLOOD-FP) was constructed and successfully applied in the Chebeichong watershed. Results show that the model’s simulations align well with observed data, achieving a Nash efficiency coefficient above 0.8 under typical rainfall events. Compared with the SWMM model, the simulation results of HRGM were significantly improved and more consistent with measured results. Taking the rainstorm event on 10 August 2021 as an example, the Nash coefficient increased from 0.7 to 0.85, while the peak flow error decreased markedly from 15.8% to 3.1%. It should be emphasized that urban waterlogging distribution is not continuous but appears as patchy, discontinuous, and fragmented patterns due to the segmentation and blocking effects of roads and buildings in urban areas. The framework presented in this study shows potential for application in other regions requiring flood risk assessment at urban agglomeration scales, offering a valuable reference for advancing flood prediction methodologies and disaster mitigation strategies.

Purpose This study sought to determine whether the integration of operations research (OR) into the Philippines’ national disaster risk reduction and management (DRRM) efforts – through the institutionalization of Project NOAH in the National Disaster Risk Reduction Management Council’s (NDRRMC) Pre-Disaster Risk Assessment (PDRA) system – had a measurable impact on disaster outcomes. Design/methodology/approach Using counterfactual analysis of disaster data from 1986 to 2024, the study compares fatalities and damage trends before (1986–2013) and after (2014–2024) the operationalization of OR in DRRM. Findings The results of our study indicate that the use of OR is at least partially responsible for the reduction in the number of deaths per year since it was embedded in the DRRM interventions of the Philippine government. Through the narrative provided, this paper seeks to explain how applied research and the application of international best practices, when used by the Philippine government, can be instrumental in the mitigation of fatalities due to disasters. Research limitations/implications In order for disaster-related research to have a greater impact, it should be conducted in close coordination with decision makers before, during and after calamities. This can be in the form of embedding research in the operations of government, similar to what was done from 2014 to 2016, where the academe was made part of the PDRA system of the NDRRMC. In the PDRA system, researchers monitored the incoming cyclones using advanced technologies and frontier science to provide hazard-specific, area-focused and time-bound warnings on a 24-h basis during inclement weather. Practical implications OR can also be embedded in the formulation of development and disaster mitigation plans for communities such as Local Climate Change Action Plans (LCCAP), Comprehensive Land Use Plans (CLUP), Comprehensive Development Plans (CDP) and Climate Disaster Risk Assessments (CDRA). All these plans require inputs from experts in the fields of energy, tourism, education, environment, forestry, agriculture, fisheries and mining, among others. Research on disaster-related topics from universities are mainstreamed into the plans of the local government units (LGUs) to provide knowledge that is local, scientific and up-to-date. Originality/value The use of OR, as demonstrated in the study, was found to be an effective strategy in reducing the number of fatalities from disasters and is part of a genuine science-based, transdisciplinary and whole-of-society approach to DRRM.

This study aims to estimate the occurrence patterns of tidal waves and abrasion in Indonesia throughout 2024 using the Kaplan-Meier method. The main focus is on analyzing the time intervals between events to provide insights into coastal areas vulnerable to the impacts of these disasters. The data used were obtained from the National Agency for Disaster Management (BNPB), consisting of records of tidal waves and abrasion events. The analysis results are expected to illustrate the frequency and distribution of events, assisting in disaster mitigation planning in coastal areas. This study does not address causative factors but rather focuses on the temporal patterns and distributions of these events. The findings are anticipated to help identify the most vulnerable coastal regions to tidal waves and abrasion impacts, enabling more targeted and data-driven mitigation efforts. This research offers valuable insights for developing effective disaster mitigation strategies, including early warning systems and improved coastal management. The close relationship between tidal waves and abrasion emphasizes the need for preventive measures, such as mangrove planting and controlling human activities in coastal areas.

Nanxi Town, located in Yunyang County within the Three Gorges Reservoir Area of Chongqing, faces high rainfall and frequent geological disasters, causing significant casualties and property damage. Analyzing the stability of rainfall-induced shallow landslides through physical models is crucial for disaster mitigation. Traditional one- and two-dimensional models fail to account for three-dimensional slope changes. This study introduces a three-dimensional physical model by combining the TRIGRS and Scoops3D models to predict the spatiotemporal distribution of landslides. To improve prediction accuracy, soil zoning of the T-S model was optimized using environmental factor frequency ratios and random forest analysis. Soil and hydrological parameters for each zone were determined through indoor experiments and incorporated into the T-S integrated model. The analysis of landslide distribution under varying rainfall durations showed that after 24 hours of rainfall, the potential landslide area increased by 63.46% compared to the natural state. The zoned model also showed higher prediction accuracy, with the %LRclass index 3.08% and 5.54% higher under natural and 24-hour rainfall conditions, respectively. This study integrates TRIGRS and Scoops3D models with optimized soil zoning, providing an effective method for predicting rainfall-induced shallow landslides.

Frequent geological hazards such as landslides and rockfalls, intensified by human activities and extreme rainfall, highlight the urgent need for rapid, accurate, and interpretable susceptibility assessment. However, existing methods often struggle with insufficient characterization of spatial heterogeneity, fragmented spatial structures, and limited mechanistic interpretability. To overcome these challenges, this study proposes an intelligent landslide susceptibility assessment framework based on the Swin-UNet architecture, which combines the window-based self-attention mechanism of the Swin Transformer with the encoder–decoder structure of U-Net. Eleven conditioning factors derived from remote sensing data were used to characterize the influencing conditions. Comprehensive experiments conducted in Changbai County, Jilin Province, China, demonstrate that the proposed Swin-UNet framework outperforms traditional models, including the information value method and the standard U-Net. It achieves a maximum overall accuracy of 99.87% and consistently yields higher AUROC, AUPRC, F1-score, and IoU metrics. The generated susceptibility maps exhibit enhanced spatial continuity, improved geomorphological coherence, and greater interpretability of contributing factors. These results confirm the robustness and generalizability of the proposed framework and highlight its potential as a powerful and interpretable tool for large-scale geological hazard assessment, providing a solid technical foundation for refined disaster prevention and mitigation strategies.

Purpose To determine how transient island populations differ from resident and mainland populations in decisions regarding sheltering, evacuation ability and communication sources, and to determine if an island environment impacts disaster preparedness. This research will provide local emergency managers with information to help support personal and community hazard mitigation that addresses the needs and capabilities distinctive to transient versus resident populations in island environments. Design/methodology/approach An online Qualtrics survey was distributed to Ross University School of Veterinary Medicine community members regarding actions during Hurricanes Irma and Maria (2017). The survey aimed to: obtain data on decision-making in sheltering and evacuation; better understand the meaning of and factors that might impact “preparedness”; and determine the sources of information used by transient and resident respondents during disasters. Findings Based on 230 transient and 60 resident respondents, sheltering decisions were primarily based on feeling safe in one's home, suggesting that routine home inspections may improve residents’ understanding of home security during a storm. Previous exposure to disasters increased respondents' feelings of preparedness but not true preparedness. This study indicated that island transient and resident populations already had many items recommended for hurricane preparedness, suggesting targeted messaging may be beneficial. Most transient and resident respondents relied on the National Oceanic and Atmospheric Administration for storm information, providing an opportunity for local stations to tailor hazard messaging to the on-the-ground realities. Originality/value This research uncovered differences in how transient and resident island populations consider, prepare for and respond to hazards and disasters. It demonstrates the need for island population-focused research to enhance disaster mitigation, preparedness, relief and recovery efforts, inclusive of transient populations often found in various sectors of Caribbean islands.

Empowering Early Childhood Resilience: Development of Illustrated Storybooks for Disaster Mitigation with Local Wisdom. Objective: This study aimed to develop and evaluate the effectiveness of an illustrated storybook based on Tunjuk Ajar Melayu Riau as an innovative learning medium to enhance disaster preparedness in early childhood. Methods: The research adopted the Borg & Gall Research and Development (R&D) model. Study participants included 60 children aged 5-6 years across three PAUD sites in the Riau region, Indonesia. The intervention was conducted over two weeks with a total of six sessions. Effectiveness was assessed using the Disaster Preparedness Scale for Early Childhood (DPSEC) (12 items, α=0.87) through pre-test and post-test. Quantitative data were analyzed using the Paired-Sample T-test, Normalized Gain (N-Gain), and Cohen’s d Effect Size, complemented by qualitative thematic analysis of interviews. Findings: The book offers novelty by combining local cultural values with interactive features, such as a maze game, specifically designed to foster critical thinking and environmental awareness, addressing the current limitation of passive disaster education media in Indonesia. The effectiveness test results showed a highly significant increase in disaster preparedness scores, soaring from a pre-test mean of 55% to a post-test mean of 90% (t(59)=14.82, p<0.001). The impact was classified as high, with an average N-Gain of 0.71 and a strong Effect Size (d=1.92). Qualitatively, the Cultural Resonance of the Malay characters significantly boosted engagement, while the Maze Game mechanistically stimulated planning and critical thinking. Teachers rated the product as highly practical with an average score of 88%, confirming its feasibility and curricular alignment. Conclusion: The illustrated storybook based on Tunjuk Ajar Melayu Riau is an effective, feasible, and practical learning model for enhancing early childhood disaster preparedness. Its success is driven by the synergy between the maze's cognitive scaffolding and the contextual reinforcement of local wisdom, offering a vital model for culturally-based disaster mitigation education in Indonesia. However, generalization is currently limited to the Riau context. Keywords: cultural identity; disaster mitigation; early childhood education; tunjuk ajar melayu.

Earthquakes can significantly affect children's development both physically and psychologically. School experience in disaster management becomes one of the foundations for formulating needs and policies in earthquakes disaster mitigation within the school environment. This study aimed to capture the experience of schools in Bantul, Yogyakarta, in dealing with earthquakes events. Using a qualitative approach, data were collected through in-depth interviews and analyzed thematically to identify codes and themes emerging from the data, related to school-based disaster management. Analysis yielded nine major categories describing how schools prepare for, respond to, and recover from earthquakes. The findings highlight the critical role of disaster education and preparedness within school settings and reveal the need for clear procedures supporting children’s physical and psychological recovery after an earthquake. These insights underscore the importance of cross-sector collaboration and policy development to strengthen school-based disaster mitigation and post-earthquake recovery programs.

The phenomenon of global sea level rise is accelerating the rate of erosion that threatens the stability of coastal areas in various countries. As an archipelagic country with extensive coastlines, Indonesia faces serious risks from prolonged coastal erosion along its coastline, which spans hundreds of thousands of kilometers. Indonesia's coastal areas are vulnerable to coastal erosion, which impacts both the environment and settlements. Pantai Cermin District, Serdang Bedagai Regency, is one of the areas experiencing significant erosion. One sustainable non-structural mitigation effort is through environmental-based education, particularly the introduction of the role of coastal vegetation. This study aims to determine the effect of disaster mitigation education on abrasion through the introduction of the role of vegetation on the improvement of knowledge and awareness of students at SMP Negeri 1 Pantai Cermin. The study uses a quantitative approach with a pretest–posttest design involving 60 students. Instruments. The research instruments consisted of questionnaires and knowledge tests. Based on the collected data, there was a significant increase in the understanding scores from an average of 10.85 before the intervention to 14.58 after the material was delivered. These findings indicate that vegetation-based coastal abrasion mitigation education is effective in increasing students' knowledge and awareness of coastal erosion.

This study aims to develop the Pop Up Book media "Ayo Siaga Bencana" (Let's Be Prepared for Disaster) to foster disaster mitigation awareness in early childhood. The development model used is ADDIE (Analysis, Design, Development, Implementation, Evaluation), but this study is limited to the limited scale implementation stage. The research approach uses mixed methods with children aged 5-6 years old group B at the Kembangan District PAUD institution. Needs analysis was conducted through observation, interviews, and teacher and parent questionnaires. The Pop Up Book product was validated by three experts (material, media, and practitioners) with very high feasibility percentage results, respectively 87.5% (material experts), 95% (media experts), and 87.5% (practitioner experts). The trial was carried out in stages (individual, small group, large group) in three PAUD institutions, then a limited scale implementation was carried out on 10 children in group B of Al-Ikhlas Joglo PAUD. The results showed a teacher response of 97.5% (very good category) and a child response of 95% (very good category). Thus, this Pop-Up Book is deemed suitable, engaging, and effective as a disaster mitigation learning medium for early childhood. This medium can increase children's attention, enthusiasm, and understanding of simple disaster management steps, making it an innovative alternative for preparedness education in early childhood education (PAUD).

The Special Region of Yogyakarta (DIY) is characterized by high seismic activity due to its proximity to the subduction zone and the presence of active fault systems, particularly the Opak Fault. The 2006 Yogyakarta earthquake revealed significant vulnerability in local building structures and highlighted the complex geological conditions governing seismic wave propagation. This study aims to calculate and map the Peak Ground Acceleration (PGA) distribution in Prambanan District, Klaten Regency—one of the areas closest to the 2006 earthquake source. PGA values were estimated using the McGuire attenuation relationship, based on a moment magnitude of Mw 6.3 and the hypocentral distance to 88 observation points distributed at approximately 900-meter intervals. The resulting PGA map indicates values ranging from 26.7 to 31.7 gal, with a clear spatial trend showing increasing intensity from the northern to the southern parts of the study area. Higher PGA values occur in regions near the Opak Fault and in areas dominated by unconsolidated volcanic deposits of the young Merapi formation. These loose sediments amplify seismic waves, resulting in stronger ground motion compared to areas composed of more compact sedimentary rocks. The spatial pattern of PGA corresponds well with the distribution of structural damage recorded during the 2006 earthquake. The findings emphasize the significant role of local geology and fault proximity in shaping seismic hazard levels. Consequently, this study provides essential insights for disaster mitigation strategies, land-use planning, and structural vulnerability assessment within the Prambanan area.

Background: Indonesia is among the world’s most disaster-prone countries, where early childhood education (ECE) institutions remain vulnerable due to limited preparedness and infrastructure. Teachers often lack confidence and structured procedures for emergency situations. This study aimed to evaluate the effectiveness of the GEMA TANGGUH (Movement for Mitigation and Education to Improve Disaster Response) model in enhancing the holistic resilience—cognitive, affective, and psychomotor—of ECE teachers. Methods: This university-based community service program employed a one-group pre–post test design. Eleven teachers and staff, along with 91 students from Aisyiyah Banyudono Playgroup, Boyolali, participated. The intervention consisted of interdisciplinary training on disaster mitigation, installation of IoT-based EWS, and structured evacuation simulations. The evaluation stage was conducted by collecting data through pre–post questionnaires and structured observations, which were then analyzed descriptively to determine mean score improvements and percentage changes across three evaluated domains. Results: The GEMA TANGGUH model produced substantial improvements across all domains. Teachers’ knowledge increased from an average score of 47.5 (pre) to 70.0 (post), a relative gain of 47.4%. Teachers reporting “very confident” rose from 10% to 50%. Psychomotor performance reached 100% accuracy, and student compliance achieved 98.89% (90 out of 91 students), indicating effective knowledge transfer. Conclusion: The GEMA TANGGUH model effectively strengthens comprehensive disaster preparedness among ECE teachers. Uniquely integrating IoT-based Early Warning Systems and Psychological First Aid (PFA)-oriented simulations, the model provides an evidence-based and scalable framework for building holistic resilience, supporting the advancement of disaster-resilient educational institutions in disaster-prone areas.

As of the regions with a high frequency and significant impact of flood disasters, Deli Serdang in North Sumatera, Indonesia highly requires spatial-based hazard mapping as a foundation for mitigation efforts. This study aims to map the flood hazard levels by integrating the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS). Five parameters were analyzed to construct the model: elevation, slope, rainfall, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI), with data acquired through the Google Earth Engine platform. The AHP weighting results indicate that rainfall is the most dominant factor (40%) influencing the hazard level. The resulting hazard map identifies a clear spatial pattern with a north-to-south gradation, where 50.17% of the total area falls into the high-hazard category, 47.57% into the moderate category, and the remainder into the low-hazard category. A significant finding reveals that all sub-districts within the study area are classified as either moderate or high hazard, confirming the northern coastal zone as the most critical area. The results of this research can serve as a scientific basis for local government in formulating more adaptive and targeted disaster mitigation policies and spatial planning.

Background and aim: The global increase in natural and human-made hazards—exacerbated by climate change—calls for strengthened national disaster mitigation and response capacities. Türkiye, located at the crossroads of Europe, Asia, and Africa, is highly vulnerable to earthquakes, wildfires, and floods. Disaster medicine addresses healthcare delivery under extraordinary conditions where health infrastructure is insufficient. However, in the country, disaster medicine is not formally integrated into medical curriculum and medical faculties do not offer structured disaster medicine education at the undergraduate level. This study explores medical students’ awareness and preparedness for disasters, identifies gaps in disaster medicine knowledge, and evaluates their willingness to engage in disaster response through education and volunteering. Materials and methods: A descriptive, cross-sectional study was conducted among first- and sixth-year medical students at Marmara University, Istanbul, during the 2024–2025 academic year. Data were collected between April and June 2025 using a 21-item online questionnaire covering socio-demographic characteristics, housing conditions, personal and familial disaster experiences, familiarity with disaster-related terminology, the Fear of Earthquake Scale and earthquake preparedness situation, interest in disaster medicine education, and willingness to volunteer. Results: In total, 193 students responded (41.4% response rate), with a majority being female (67.3%). Most had personal or familial experience with disasters, especially earthquakes. Among sixth-year students, 72.3% correctly identified the definition of triage. The Fear of Earthquake Scores were higher among women. Most students lacked an emergency kit (76.4%) or an action plan (72%). More first-year students had participated in drills. Overall, 84.4% expressed interest in disaster medicine training, favouring simulation and gamification methods. Willingness to join a disaster volunteer project was 54.4%, and was notably higher among those interested in training. Conclusion: Integrating disaster medicine into medical education is increasingly recognized as vital to prepare future healthcare professionals and engage medical students in disaster response, thereby enhancing disaster preparedness and resilience in high-risk regions like Türkiye.