Disaster Simulation Research Articles

Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities

Abstract Enhancing resilience against seismic hazards in earthquake-prone regions is essential for reducing the devastating impacts of disasters. Seismic resilience refers to a community’s ability to withstand and recover from earthquake impacts, while preparedness gaps are the areas where current measures are insufficient to effectively respond to or mitigate earthquake damage. This study focuses on Montenegro – a region with frequent seismic activity – aiming to assess resilience levels, identify critical gaps in preparedness, and evaluate the effectiveness of existing response strategies. Using qualitative methods, including semi-structured interviews, the research gathered insights from residents of Montenegro’s most vulnerable cities: Nikšić, Podgorica, Bar, Kotor, Cetinje, Budva, Herceg Novi, and Berane. Participants, chosen for their first-hand experience with significant earthquake impacts, provided valuable perspectives on various aspects of resilience, from local government response to individual preparedness. This research revealed significant disparities in resilience across communities: for instance, approximately 62.5% of the respondents highlighted inadequate education as a barrier to effective earthquake preparedness, and only 37.5% reported awareness of basic earthquake response procedures. Furthermore, while some communities, such as urban areas with accessible services, reported higher preparedness levels, rural areas showed deficiencies, with 50% of the respondents from these areas identifying a lack of organized drills and limited public awareness initiatives. These findings underscore the urgent need for community-specific preparedness programs and enhancements in both structural resilience and public education to bolster community readiness effectively. Also, findings highlight the need for customized preparedness programs tailored to specific community needs, alongside improvements in structural safety measures and educational outreach. The study underscores the importance of a comprehensive approach involving detailed risk assessments, community-focused preparedness training, and stronger public awareness initiatives. Furthermore, the study calls for enhanced local government capabilities to sustain proactive response measures, including rapid mobilization of emergency resources and regular disaster simulations, to build long-term resilience across communities.

Perinatal care in the earthquake disaster of the century: Nurses' and midwives' experiences.

To determine the experiences of nurses and midwives providing perinatal care in an earthquake area. On February 6, 2023, two earthquakes measuring 7.8 and 7.6 magnitudes struck Turkey, affecting a large area. It is crucial for perinatal care to be rapidly organized, provided under the most suitable conditions, and delivered by qualified health professionals. Understanding the post-disaster experiences of nurses and midwives is crucial to addressing this issue. This is a qualitative study using phenomenological methodology with 8 nurses and 12 midwives in the earthquake-affected area. Personal information and semistructured interview forms were used for data collection. Content analysis was used for data analysis. Participants had a mean age of 33.75 years. The experiences of nurses and midwives were grouped into five themes: emotions experienced, challenges encountered, problems in perinatal services, coping mechanisms, and recommendations. The emotions experienced theme encompasses both positive and negative emotions. The challenges encountered theme includes challenging environmental conditions, organizational issues, problems with medical supplies and drugs, and being a victim of the earthquake. The problems in perinatal services theme includes pregnancy, childbirth, and postpartum services. The coping mechanism's theme encompasses problem-focused and emotion-focused coping strategies. The recommendations theme includes education and awareness, preparedness for disasters, and sustainable services. Nurses and midwives working in the earthquake-affected area experienced numerous physical and psychological challenges and encountered difficulties in delivering health services. Adisaster educationcourse including simulated disaster drills and practice can be integrated into the education system. Strengthening healthcare facilities against disasters and raising awareness among the community are crucial.

Analysis of postdisaster economy using high-resolution disaster and economy simulations.

We present an integrated framework that utilizes high-resolution seamless simulations of disasters and national economies for estimating the economic impacts of disasters. The framework consists of three components: a physics-based simulator to simulate the disaster and estimate the response of the infrastructure; a tool that estimates the losses suffered by the infrastructure based on its response; and an agent-based economic model (ABEM) that simulates the national economy considering the infrastructure damage and postdisaster decisions of the economic entities. The ABEM used in the framework has been implemented in a high-performance computing environment to simulate large economies at 1:1 scale. Furthermore, it has been calibrated to the Japanese economy using publicly available macroeconomic data and validated to the Japanese economy under the business-as-usual scenario. We demonstrate the integrated framework by simulating a potential Nankai-trough earthquake disaster and estimating its impacts on the Japanese economy. The seismic response of 1.8 million buildings of the Osaka-bay area has been estimated using a large-scale earthquake disaster simulator and corresponding repair costs are estimated using the Performance Assessment Calculation Tool. As per our estimates, repair costs amount to approximately 15 trillion Yen. Considering the investments made by impacted households and firms toward recovery, the postdisaster economy is simulated using the ABEM for 5 years under two recovery scenarios. Industrial production is expected to recover in three quarters whereas 10-13 quarters will be required to finish all the repairwork.

Improve disaster literacy in nurses: a qualitative descriptive study.

The enhancement of nurses' disaster literacy is crucial for effective disaster emergency management, especially for clinical nurses with no prior experience in disaster rescue. This study aims to explore the perspectives of nurses who have been involved in disaster rescue operations on strategies to advance nurses' disaster literacy. A qualitative descriptive study, which follows unified qualitative study reporting guidelines. Thirty disaster rescue nurses were recruited to participate in this study, who came from 30 third-class hospitals in China. From October to December 2021, information was acquired by conducting semi-structured telephone interviews with participants. Qualitative content analysis was used to examine the data. Six categories and eleven subcategories were created. Strengthening disaster education and training was the main focus, and its subcategories included continuing education, nursing curriculum development, and disaster rescue experience guide. The second focus, which included scene simulation, actual combat/military simulation, and virtual reality simulation, was strengthening disaster simulation and drill. The third focus was on providing psychosocial support, which included improving self-psychological adjustment, developing resilience, and engaging in active coping. The fourth category was to strengthen nurse/hospital managers roles and leadership, which included enhancing professional identity and policies/leadership support. The fifth category was disaster preparedness, and the sixth was enhancing knowledge transformation. Government agencies or healthcare organizations should actively promote the formation of nurses' disaster literacy from multiple viewpoints. Disaster education and training, simulation exercises, and psychosocial support should be prioritized.

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study.

The release of ChatGPT (OpenAI) in November 2022 drastically reduced the barrier to using artificial intelligence by allowing a simple web-based text interface to a large language model (LLM). One use case where ChatGPT could be useful is in triaging patients at the site of a disaster using the Simple Triage and Rapid Treatment (START) protocol. However, LLMs experience several common errors including hallucinations (also called confabulations) and prompt dependency. This study addresses the research problem: "Can ChatGPT adequately triage simulated disaster patients using the START protocol?" by measuring three outcomes: repeatability, reproducibility, and accuracy. Nine prompts were developed by 5 disaster medicine physicians. A Python script queried ChatGPT Version 4 for each prompt combined with 391 validated simulated patient vignettes. Ten repetitions of each combination were performed for a total of 35,190 simulated triages. A reference standard START triage code for each simulated case was assigned by 2 disaster medicine specialists (JMF and MV), with a third specialist (LC) added if the first two did not agree. Results were evaluated using a gage repeatability and reproducibility study (gage R and R). Repeatability was defined as variation due to repeated use of the same prompt. Reproducibility was defined as variation due to the use of different prompts on the same patient vignette. Accuracy was defined as agreement with the reference standard. Although 35,102 (99.7%) queries returned a valid START score, there was considerable variability. Repeatability (use of the same prompt repeatedly) was 14% of the overall variation. Reproducibility (use of different prompts) was 4.1% of the overall variation. The accuracy of ChatGPT for START was 63.9% with a 32.9% overtriage rate and a 3.1% undertriage rate. Accuracy varied by prompt with a maximum of 71.8% and a minimum of 46.7%. This study indicates that ChatGPT version 4 is insufficient to triage simulated disaster patients via the START protocol. It demonstrated suboptimal repeatability and reproducibility. The overall accuracy of triage was only 63.9%. Health care professionals are advised to exercise caution while using commercial LLMs for vital medical determinations, given that these tools may commonly produce inaccurate data, colloquially referred to as hallucinations or confabulations. Artificial intelligence-guided tools should undergo rigorous statistical evaluation-using methods such as gage R and R-before implementation into clinical settings.

The speed and accuracy of prehospital triage for simulated disaster patients: Comparing prehospital emergency triage rapid algorithm (PETRA) and simple triage and rapid treatment (START)

The speed and accuracy of prehospital triage for simulated disaster patients: Comparing prehospital emergency triage rapid algorithm (PETRA) and simple triage and rapid treatment (START)

Pelatihan Manajemen Bencana Dengan Table Top Disaster Simulation: Perintisan Desa Siaga Bencana di Kabupaten Musi Rawas Sumatera Selatan

Minimizing the impact that occurs due to disasters, and preparing for the possibility of a disaster occurring is the most important thing that must be done, including preparing human resources to be ready to face the disaster itself. One form of preparing society to be able to respond well to disasters is by providing good education and training on how to respond to disasters. Table Top Disaster Simulation is an effective education and training method for preparing human resources. This activity aims to increase community knowledge about disaster management as part of the Disaster Preparedness Village pilot in Air Satan Village, Musi Rawas Regency, South Sumatra. This activity is community service using education and training methods with a total of 33 participants. Participants' disaster management knowledge was measured before and after attending education and training using a questionnaire. The evaluation results showed that there was an increase in knowledge before being given the training with the average knowledge score of participants being 44.71, while after being given the training the average knowledge score was 78.32. After conducting education and training using tabletop disaster simulation, public knowledge about disaster management increased. It is hoped that after this pioneering disaster preparedness village activity, education and training will continue to be carried out on other factors in responding to disasters such as training on handling injuries for lay people, training on handling drowning victims for lay people, and so on.

Simulation of spatial flooding disaster on urban roads and analysis of influencing factors: taking main city of Hangzhou as an example

Simulation of spatial flooding disaster on urban roads and analysis of influencing factors: taking main city of Hangzhou as an example

Numerical Analysis of Flood Invasion Path and Mass Flow Rate in Subway Stations under Heavy Rainfall Conditions

The occurrence of extreme weather, such as heavy rainfall and sudden increases in precipitation, has led to a notable rise in the frequency of flooding in subway stations. By conducting numerical simulations of flood disasters in subway stations under heavy rainfall conditions and gaining insights into the patterns of flood invasion inside the stations, it is possible to develop practical and feasible drainage designs for the stations. This paper employs the computational fluid dynamics (CFD) method, utilising the volume of fluid function (VOF) method and the renormalization k-ε group model within the vortex viscosity model. The complete process of flood invasion into subway stations with varying water levels (1500 mm, 2000 mm, and 2450 mm) is modelled, and the distribution of floods at different times under varying operational conditions is analysed to identify the evolutionary patterns of station flood history. The simulation calculations yielded the mass flow rate time history curve at the tunnel entrance and exit, which was then subjected to an analysis of its development trend over time. The total accumulated water in the subway station is calculated by integrating the difference in mass flow rate between the entrance and the tunnel exit, using the mass flow rate curve. In conclusion, the paper proposes drainage measures that provide valuable insights into pumping strategies when floodwaters infiltrate subway stations. The results indicate that the speed of flood spreading in subway stations increases with higher groundwater levels, and that the mass flow rate of floodwater entering the tunnels increases over time, eventually reaching a stable state. It was observed that, at certain times, the mass flow rate of floodwater into the tunnels exhibited a linear relationship with time.

A combined extended triple collocation and cumulative distribution function merging framework for improved daily precipitation estimates over mainland China

Accurate monitoring of daily precipitation is essential for many applications, such as simulation and prediction of watershed water-related disasters. However, precipitation data from satellite and gauge-based precipitation products face challenges in capturing true observations because of their large uncertainties. To improve daily precipitation estimates, this study proposed a new merging framework, ETCCCDF, that combines an extended triple collocation (ETCC) with maximized correlation and cumulative distribution function (CDF) matching with reduced bias. The ETCCCDF framework was applied to systematically integrate three independent precipitation products from SM2RAIN-ASCAT satellite soil moisture estimator, IMERG Early Run satellite retrieval, and CPC unified gauge-based analysis. A new merged precipitation product, with a fine spatiotemporal resolution of 0.25°/1 d, was developed and then thoroughly evaluated using 2304 stations over mainland China from 2007 to 2014. The results showed that the ETCCCDF framework significantly improved the precipitation representation in terms of the correlation, bias, and absolute difference, and it increased modified Kling-Gupta efficiency value relative to any of the parent precipitation products, demonstrating the effectiveness of the proposed merging framework. In addition, the ETCCCDF framework is more robust than the ETCC, triple collocation (TC) merging, and combined strategy of TC with CDF, in which CDF matching successfully corrects the precipitation biases in collocation fusions. The accuracy of the merged products in heavy rainfall estimation during Typhoon Morakot in 2009 and Typhoon Fitow in 2013 was further evaluated. The results confirmed that the ETCCCDF-merged product performed satisfactorily for heavy rainfall events and presented superior statistical scores. This study proves that the ETCCCDF framework is a promising solution for obtaining high-quality precipitation data, particularly for limited-gauge areas.

Geographic Information System for Shortest Route Search for Clinics in Pamekasan Regency Using the Djikstra Method

Earthquake natural disasters can cause significant infrastructure damage, hindering community access and mobility. In such a situation, determining the shortest path for evacuation becomes very important. This research uses linear programming by utilising Excel Solver to determine the shortest evacuation route for earthquake natural disasters. Excel Solver is a feature in Microsoft Excel that serves as an analytical tool to solve linear optimisation problems. Excel solver can be used to find solutions that maximise or minimise the objective function, with respect to predetermined constraints. This research utilises relevant earthquake natural disaster simulation data as constraints in the optimisation model. The results show that the model can generate shortest paths that fulfil various constraints and criteria. The model can also be used to predict the time required to reach the destination. This research makes an important contribution to the development of tools and methods for shortest path optimisation in natural disaster scenarios. The optimisation model developed in this research can be used to assist decision makers in improving the efficiency and effectiveness of evacuation and disaster relief operations.

ANALISIS KEBERLANJUTAN PROGRAM PRO-BEBAYA DI KOTA SAMARINDA PASCA PILKADA 2024

This study aims to describe and analyze the safety behavior of residents towards emergency disaster mitigation efforts around the Samarinda Fuel Terminal. This research was conducted using a quantitative descriptive method. The population is all heads of families in the RT 27 area of Teluk Lerong Ulu Village as many as 44 people and all of them are used as research samples (total sampling). Data collection was carried out on June 1-20 2023 by direct interview method using a questionnaire with a closed list of questions. The results of the study obtained information that most residents stated the importance of installing evacuation routes in disaster-prone environments such as fire hazards, residents stated that evacuation route signs should be installed using materials that are not flammable and not easily damaged and are willing to take part in disaster simulation activities and maintain Evacuation sign facilities that have been installed at this time.

Methodology for risk assessment of multi-event scenarios on radioactive waste repository

Deep geological disposal, which is a permanent method that isolates a storage facility in rocks 200 to 1000 m deep underground, plays a role in safely disposing spent nuclear fuel to prevent excessive radioactive species from leaking out and its safety should be primarily proved. Risk for various radionuclide leakage scenarios should be calculated to be used as a safety indicator. One of the scenarios that significantly affects the safety of repository is the occurrence of external events such as an earthquake scenario. Several occurrences of such external disasters are expected over a long period of time which the safety functions of the deep disposal site must be maintained. Rather than performing a conservative single event evaluation, we expected that performing a more realistic evaluation, such as considering the number of events, is preferrable for design and operation optimization, particularly in an early project phase. This paper suggests a need for assessing multi-event scenarios and the methodology for simulation of several external disasters using earthquakes as an example. The methodology and algorithm of simulating multiple earthquakes and assessing risk distribution under those events at repository site is introduced in GoldSim software, and its results are expected to be used at simulating other event scenarios.

Multi-disciplinary mass burn casualty simulation exercise

Disaster simulation exercises are important to test service processes, capabilities, and deficiencies and disaster response planning should encompass the entire multidisciplinary team over an extended period. Our service simulated a modest eight burn casualty scenario to test our service capabilities over a 10-week period across medical, nursing, and allied health professions. Requirements due to the mass burns casualty cohort were predicted in terms of theatre requirements, allied health treatment hours required, and nursing hours requirements. Prospective business-as-usual service provision data was also collected over the 10-week study period in respect to theatre utilisation, allied health workload, nursing hours and burns ward bed census. This data was then superimposed on predicted mass burn casualty requirements to gauge total workload demands over the study period. Results showed an expected significant initial spike in theatre requirements in the first week post mass casualty with ongoing deficiencies in theatre allocation occurring throughout the 10-week study period. Allied health staff were working at or near capacity in a business-as-usual setting with major spikes in workload demand occurring due to the mass burn casualty cohort. Total workload demands clearly exceeded current staff capacity for most of the allied health professions over the 10-week period. Bed census exceeded funded nursing bed capacity for all but seven days of the study period. Predicted combined nursing hours required exceeded funded capacity for all but two days. This simulation clearly demonstrated the high and immediate increase in workload demands across all professions over a prolonged 10-week period and that high business-as-usual demand can greatly affect staff capacity to cope with a mass casualty surge in admissions. It was able to provide evidence, and awareness, for leadership and management on the need for resources and resource re-allocation in a mass burn casualty scenario. It also informed a review of our current triggers for activating our SA Health Multiple Burns Plan.

Strengthening Community Disaster Education for Disaster Mitigation

Indonesia, particularly Java Island, is highly vulnerable to natural disasters, which have frequently resulted in significant loss of life, property damage, and fatalities. Given this high level of risk, it is crucial to enhance community preparedness to mitigate the impacts of such disasters. This paper highlights the critical role of disaster education in effective disaster mitigation efforts. Utilizing a library research methodology, this study involved a comprehensive review of literature, including books, journals, and secondary data related to disaster education. The findings indicate that there is currently no standardized method for delivering disaster education. Instead, various approaches are employed, including disaster training programs, awareness campaigns, seminars, simulations, and exhibitions. These alternative methods aim to improve public knowledge and preparedness, although a unified and systematic approach is still lacking.

Optimisation of Evacuation Route Determination in an Earthquake Natural Disaster Scenario Using an Excel Solver

Earthquake natural disasters can cause significant infrastructure damage, hindering community access and mobility. In such a situation, determining the shortest path for evacuation becomes very important. This research uses linear programming by utilising Excel Solver to determine the shortest evacuation route for earthquake natural disasters. Excel Solver is a feature in Microsoft Excel that serves as an analytical tool to solve linear optimisation problems. Excel solver can be used to find solutions that maximise or minimise the objective function, with respect to predetermined constraints. This research utilises relevant earthquake natural disaster simulation data as constraints in the optimisation model. The results show that the model can generate shortest paths that fulfil various constraints and criteria. The model can also be used to predict the time required to reach the destination. This research makes an important contribution to the development of tools and methods for shortest path optimisation in natural disaster scenarios. The optimisation model developed in this research can be used to assist decision makers in improving the efficiency and effectiveness of evacuation and disaster relief operations.

The Effectiveness and Benefits of Disaster Simulation Training for Undergraduate Medical Students in Saudi Arabia.

There is a growing recognition of the need for disaster management training for medical students in Saudi Arabia, but there is limited research on its effectiveness. Thus, this study evaluated the effectiveness of a disaster simulation training program for undergraduate medical students in Saudi Arabia. A disaster management simulation activity was conducted for 32 medical students. The students attended a 30-minute lecture about mass casualty incidents (MCIs) and completed a pre-simulation survey. They were then randomly assigned to one of three groups (performer, actor, observer) and asked to apply their skills to triage patients after a Level C MCI. A debriefing session was conducted using the plus/delta debriefing method. Then, the students completed a post-simulation survey. The results showed that after the simulation training the students' self-confidence in their ability to respond to a disaster increased from 40.7% to 59.4% (p value < 0.01), to utilize incident command structure increased from 37.9% to 62.5% (p value < 0.01), to demonstrate START triage for victims of a disaster increased from 28.2% to 65.7% (p value < 0.01), and to apply safe search and rescue techniques increased from 40.7% to 59.4% (p value < 0.01). The students' self-confidence in their ability to perform basic first aid skills also increased after the simulation. The study findings suggest that disaster management simulation training can be an effective way to increase medical students' self-confidence and preparedness for disaster response.

Optimizing the level of disaster preparedness for coastal children in creating a disaster resilient generation

Indonesia is home to various natural disasters, including earthquakes and tsunamis, due to its location in the Ring of Fire. Jember Regency in East Java is one of the areas with a high risk of these disasters. Sabrang Village, bordering the South Coast of Jember, has the potential to become a disaster-resilient village. This program aims to increase disaster preparedness for children on the south coast, optimize partner empowerment in increasing child preparedness, and establish a Disaster Empowerment Center (DEC) in Sabrang Village. The DEC program was implemented over three months, involving coastal children. Methods included education, training, and empowerment through Communication, Information, and Education (IEC) and disaster simulation training. Program evaluation used a preparedness questionnaire covering participants' knowledge, attitudes, and skills. The DEC program succeeded in increasing disaster preparedness for children in Sabrang Village. Collaboration with the village government, public health center, and other partners was crucial to the program's success. DEC implementation can serve as a model for community empowerment in dealing with earthquakes and tsunamis.

Association and Effect Strength of Simulation Characteristics and Transfer of Learning Attitudes in a Disaster Simulation for Prelicensure Nursing Students.

Nurse educators design simulations with the intent that students transfer previous academic learning. Transfer of learning (TOL) is a complex and abstract concept with critical literature gaps needing measurement research. This study examined the association between simulation characteristics and students' TOL attitudes and the effect strength. This baseline study evidenced simulation design characteristics, as category groupings, were associated with students' TOL attitudes with positive and mostly modest effects. The resulting educational implications include applying instructional design to simulation, teaching students what TOL is, and modeling thinking in the classroom for transfer to simulation.

Simulating Civil Society in the Middle East and North Africa (MENA): Fog, Friction, and the Lebanese Port Explosion

Introduction Though the effects of fog and friction on decision-making are frequently simulated in military settings, they are less frequently extended to non-military and non-governmental MENA spaces. This article provides a description and evaluation of a disaster simulation rooted in the real-world event of the August 4, 2020 Lebanese port explosion. The aim of the simulation is to prompt student learning of the decision-making dynamics of CSOs amidst fog and friction in democratizing MENA spaces. Background A brief overview of the Lebanon-CSO landscape is provided. As part of their ruling strategy, sectarian elites engineer fog and friction to co-opt and fragment CSOs. This complex power sharing milieu creates dilemmas for CSOs. The Intervention The simulation was designed for an entire classroom of students to experience the fog and friction in decision-making that CSOs encounter in MENA conditions of limited resources and urgent humanitarian need. Methods and Limitations Student learning, framed by Bloom’s taxonomy of levels of intellectual behavior, was assessed using qualitative entry and exit classroom surveys based on three iterations of the simulation. Qualitative interpretive content analysis was used to categorize survey responses. The sample is not statistically significant given the small class sizes at the College. The study serves as an initial exploration for assessing the promising pedagogical benefits of the Lebanon port explosion simulation. Results Before the simulation, students had knowledge and understanding of CSOs, democratization, and the Lebanese context. After the simulation, student surveys yielded results that evidenced higher- ordered learning. Students discovered the challenge of applying their knowledge of Lebanese CSOs amidst fog. Next, the panel stress- testing and critical reflection essay exercises prompted an analysis and evaluation of CSOs as weak or fraught vehicles for democratization in the region. In sum, fog and friction prompted students to experience and learn how CSOs may subvert democratization in the MENA despite intentions to “do good.” Discussion The Lebanon port explosion survey data indicate the value of simulations as “experience vehicles” that may push students to higher orders of abstracted thinking about CSOs in the MENA. Conclusion Coupled with historical knowledge of co-optation and fragmentation strategies of elites vis-à-vis CSOs in Lebanon, the classroom simulation experience provided a low-cost and high-reward learning opportunity for students to grapple with the constraints and consequences of fog and friction on CSO decision-making.