Pathways of ecosystem-based disaster risk reduction: A global review of empirical evidence.

Ecosystems provide valuable services in reducing the risks of disasters through various pathways, which are increasingly recognized as sustainable strategies for disaster management. However, there remains limited information on the underlying ecological processes of risk reduction. This paper addresses this gap by synthesizing ecological mechanisms and evaluating the 'level of evidence' and 'scale of use' through a review of 64 peer-reviewed research articles published between 2015 to 2022. These research articles covered nine types of disasters, predominantly floods (42.19 %), followed by urban heat waves (18.75 %), storm runoff (10.94 %), coastal erosion (9.38 %), tsunamis (4.69 %), and avalanches and landslides (6.25 % each). The level of evidence supporting ecological processes for disaster risk reduction is moderate, as is the 'scale of use'. Results show that there are a few studies describing the mechanism of ecosystem-mediated risk reduction and are mostly limited to the causal relationship. Empirical evidence demonstrates that forest and freshwater ecosystems buffer the risk of urban heat through processes such as transpiration, solar radiation interception, and evaporative cooling, while flood risks are mitigated by enhancing evapotranspiration, reducing water runoff time, and facilitating infiltration rates. Coastal erosion is reduced by dissipating wave energy and through beach nourishment, which facilitates ecological succession. The review underscores that hazard attenuation depends on factors such as forest type (e.g., species composition, age structure, and area), and landscape characteristics (e.g., matrix, composition and configuration). Moreover, the geographic scope of published research is largely confined to developed countries and the global north. Multidisciplinary research involving ecologists and disaster experts is imperative to address existing knowledge gaps and enhance the integration of ecosystem-based adaptation into disaster risk reduction strategies.

Study on agricultural drought disaster risk assessment in Heilongjiang reclamation area based on SSAPSO optimization projection pursuit model.

Heilongjiang reclamation area serves as a crucial hub for commodity grain production and strategic reserves in China, playing a vital role in maintaining national food security. Investigating the assessment of agricultural drought risk in this region can yield valuable insights into spatial and temporal variations in drought risk. Such insights can aid in formulating effective strategies for disaster prevention and mitigation, thereby minimizing food losses caused by drought disasters. This study employs a comprehensive indicator system comprising 17 indicators categorized into hazard, exposure, vulnerability, and resistance capacity. The projection pursuit model is applied to evaluate regional drought risk, while the PSO algorithm, optimized by the SSA algorithm, addresses the limitations of low local search ability and search accuracy during the large-scale search process of the PSO optimization algorithm. This study examines and compares the optimization and convergence capabilities of three algorithms: real number encoding-based genetic algorithm (RAGA), particle swarm optimization algorithm (PSO), and sparrow algorithm-based improved particle swarm optimization algorithm (SSAPSO). The analysis demonstrates that SSAPSO exhibits superior optimization performance and convergence properties, establishing it as a highly effective algorithm for optimization tasks. The findings reveal the following trends: over time, agricultural drought risk in Heilongjiang reclamation area has generally declined, with fluctuations observed in hazard and vulnerability, an increase in exposure, and a continuous enhancement of resistance capacity. Spatially, the western region exhibits significantly higher agricultural drought risk compared to the eastern region, primarily due to elevated hazard and vulnerability, coupled with lower resistance capacity. As the agricultural economy grows and agricultural expertise accumulates, the risk of agricultural drought decreases. However, variations in economic growth among different regions lead to diverse spatial distributions of risk.

Travel surveillance uncovers dengue virus dynamics and introductions in the Caribbean.

Dengue is the most prevalent mosquito-borne viral disease in humans, and cases are continuing to rise globally. In particular, islands in the Caribbean have experienced more frequent outbreaks, and all four dengue virus (DENV) serotypes have been reported in the region, leading to hyperendemicity and increased rates of severe disease. However, there is significant variability regarding virus surveillance and reporting between islands, making it difficult to obtain an accurate understanding of the epidemiological patterns in the Caribbean. To investigate this, we used travel surveillance and genomic epidemiology to reconstruct outbreak dynamics, DENV serotype turnover, and patterns of spread within the region from 2009-2022. We uncovered two recent DENV-3 introductions from Asia, one of which resulted in a large outbreak in Cuba, which was previously under-reported. We also show that while outbreaks can be synchronized between islands, they are often caused by different serotypes. Our study highlights the importance of surveillance of infected travelers to provide a snapshot of local introductions and transmission in areas with limited local surveillance and suggests that the recent DENV-3 introductions may pose a major public health threat in the region.

Vegetation dieback in the Mississippi River Delta triggered by acute drought and chronic relative sea-level rise.

Vegetation dieback and recovery may be dependent on the interplay between infrequent acute disturbances and underlying chronic stresses. Coastal wetlands are vulnerable to the chronic stress of sea-level rise, which may affect their susceptibility to acute disturbance events. Here, we show that a large-scale vegetation dieback in the Mississippi River Delta was precipitated by salt-water incursion during an extreme drought in the summer of 2012 and was most severe in areas exposed to greater flooding. Using 16 years of data (2007-2022) from a coastwide network of monitoring stations, we show that the impacts of the dieback lasted five years and that recovery was only partial in areas exposed to greater inundation. Dieback marshes experienced an increase in percent time flooded from 43% in 2007 to 75% in 2022 and a decline in vegetation cover and species richness over the same period. Thus, while drought-induced high salinities and soil saturation triggered a significant dieback event, the chronic increase in inundation is causing a longer-term decline in cover, more widespread losses, and reduced capacity to recover from acute stressors. Overall, our findings point to the importance of mitigating the underlying stresses to foster resilience to both acute and persistent causes of vegetation loss.

Coordination and modularization: the experience of the joint prevention and control mechanism to COVID emergencies in China.

Background: The integration of disparate emergency resources and the improvement of emergency response teamwork are the underlying trends and shared requirements for building resilience in an era of multiple global public health crises. Objective: This study investigated the emergency response with emergency collaboration networks of each functional module and the overall Joint Epidemic Prevention and Control Mechanism (JPCM) network in China's COVID outbreak prevention and control. Methods: The study employed a scholarly framework of "the integration of JPCM coordination and emergency collaborative modularization" to explore the attributes of JPCM using social network analysis. The data were obtained from administrative records from JPCM's official website, spanning January 2020 to December 2022. Results: The study examined the JPCM coordination and found several functional working modules of JPCM, such as Interrupt Spread, Manage Supply, Medical Rescue, Restore Work and Production, and Implement Responsibility modules. The network structure indicators showed that the Manage Supply module had the most extensive network connectivity, the shortest communication distance, and the most consistent collaboration. The E-I index of the overall JPCM network and the Manage Supply network were - 0.192 and - 0.452, respectively (at p < 0.001 and p < 0.05), indicating more internal relationships than external relationships. The E-I index of the Medical Rescue and Implement Responsibility collaboration networks were 0.122 and 0.147, respectively (at p < 0.001 and p < 0.05), indicating more external relationships than internal relationships. The QAP regression analysis showed that the most vital driver on the overall JPCM network was the Interrupt Spread module, followed by the Implement Responsibility and Medical Rescue modules. Discussion: The Interrupt Spread module initiated emergency coordination with most departments and agencies. The Manage Supply module ensured the flow of medical supplies and survival essentials, while the Medical Rescue module addressed the core aspects of the health emergency response. The Restore Work and Production module repaired the halt in production and livelihoods caused by the outbreak, strengthening and developing emergency coordination and roles across emergency organizations. The Implement Responsibility module provided more heterogeneous emergency response resources for the overall JPCM coordination, complementing the COVID cross-organizational emergency response coordination. Conclusion: The study on the JPCM case in China improves public health emergency management and aids informed decision-making.

Use of virtual reality exercises in disaster preparedness training: A scoping review.

Background: The scope and number of disasters have increased over the years. This has called for more robust disaster preparedness training and plans. The use of virtual reality exercises in addition to tabletop exercises is considered a new approach to the preparation of disaster preparedness plans. Virtual reality exercises are being developed to either replace or complement current traditional approaches to disaster preparedness training. Objectives: To review and summarize the current existing literature regarding the effectiveness, advantages and limitations of using virtual reality exercises in disaster preparedness as a complementary/replacement mechanism for real-time drills and tabletop exercises. Methods: In this scoping review, we searched PubMed, Cochrane, EMBASE, PLOS, and Google Scholar for research publications involving virtual reality exercises in disaster training from 2008 to 2022 using "AND" and "OR" operators for the keywords "disaster," "preparedness," "virtual reality," and "tabletop." From a total of 333 articles that resulted in our search and were then evaluated by the authors, 55 articles were finally included in this review. Results: Virtual reality exercises are found to be better in the formulation of disaster preparedness plans compared to tabletop exercises. Virtual reality exercises can be used as the primary means of creating a real-life-like experience in disaster preparedness training and proved at least as better complementary to tabletop exercises. Virtual reality exercises have many advantages over traditional real-life or tabletop exercises and are more cost-effective, but some drawbacks are still identified. Conclusion: The advantages of virtual reality exercises are remarkable and underline their benefits and uses versus costs. We highly encourage decision-makers and institutions dealing in disaster preparedness to adopt using virtual reality exercises in training for disaster preparedness.

Collaborative virtual reality environment in disaster medicine: moving from single player to multiple learners.

BACKGROUND: The use of virtual reality (VR) in healthcare education is on the increase. In disaster medicine, it could be a solution to the cost and logistic constraints for a "full-scale" scenarios. However, VR is mainly designed for single players, which is not appropriate for the objectives pursued in disaster medicine. We decided to evaluate the educational value of using individual VR simulation in disaster medicine on a group of learners. METHODS: The VR scenario used was a reproduction of a major train crash, with 21 victims and whose objectives were START triage and first aid techniques. The sessions were carried out in multi-participant groups with different roles (active and immersed with headset, paper triage without headset, and active for communications not immersed in the headset). Their perceived self-efficacy was assessed before (T0), after (T1) and 2 months (T2) after the training. Satisfaction and confidence in learning were also measured. RESULTS: The median levels of satisfaction and confidence in learning were of 21/25 and 32/40 respectively. Their perceived self-efficacy increased significantly between T0 and T1 (p < 0.001), and remained stable until T2. The different roles of participant showed no difference in terms of satisfaction, confidence in learning or changes in perceived self-efficacy. One third of the participants agreed that the number of participants had interfered with their learning. A significant negative correlation (rS = -0.51, p = 0.002) was found between satisfaction and the fact of having been hindered by the number of participants. Around 90% of participants found the activity entertaining and found the new technologies appropriate for learning technical skills. CONCLUSIONS: This first experience of VR in a group setting is satisfactory and shows its positive effects. The limitations highlighted here will enable areas of improvement to be identified for the use of VR in disaster medicine, pending the development of multi-player tools. It would now be appropriate to analyse the impact of this type of simulation on learning and its retention over time.

An assessment of nurses' perceived and actual household emergency preparedness.

Nurses' household preparedness is critical if they are to avoid role conflict and report for duty during an emergency. To date, the alignment between nurses' perceived and actual household preparedness remains under examined. Investigating one of these variables in isolation fails to consider that perceived and actual household preparedness must be high and aligned. If misaligned, vulnerabilities could surface during emergencies, like concerns about family safety, potentially impacting a nurse's commitment to duty during a crisis, or nurses may lack the actual preparedness to continue working long hours during an emergency. An online questionnaire was distributed to registered nurses in Ireland. The questionnaire was informed by a review of the literature and captured nurses' perceived and actual household preparedness, attitudes towards and exposure to a range of emergencies, and pertinent demographic characteristics. The results showed a relationship between how nurses view their household preparedness and their actual preparedness. Regression analyses indicate that while there is an overlap, the factors associated with how prepared nurses think they are and how prepared they are can differ. This means that strategies to boost actual preparedness may differ from those needed to boost perceived preparedness. This finding underscores the importance of psychosocial preparedness. Feeling prepared is crucial as it can influence how one responds in an emergency. Considering both the perceived and actual aspects of household preparedness can lead to a more effective response during emergencies.

Wastewater based epidemiology as a surveillance tool during the current COVID-19 pandemic on a college campus (East Carolina University) and its accuracy in predicting SARS-CoV-2 outbreaks in dormitories.

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.

Mid-ocean ridge unfaulting revealed by magmatic intrusions.

Mid-ocean ridges (MORs) are quintessential sites of tectonic extension1-4, at which divergence between lithospheric plates shapes abyssal hills that cover about two-thirds of the Earth's surface5,6. Here we show that tectonic extension at the ridge axis can be partially undone by tectonic shortening across the ridge flanks. This process is evidenced by recent sequences of reverse-faulting earthquakes about 15 km off-axis at the Mid-Atlantic Ridge and Carlsberg Ridge. Using mechanical models, we show that shallow compression of the ridge flanks up to the brittle failure point is a natural consequence of lithosphere unbending away from the axial relief. Intrusion of magma-filled fractures, which manifests as migrating swarms of extensional seismicity along the ridge axis, can provide the small increment of compressive stress that triggers reverse-faulting earthquakes. Through bathymetric analyses, we further find that reverse reactivation of MOR normal faults is a widely occurring process that can reduce the amplitude of abyssal hills by as much as 50%, shortly after they form at the ridge axis. This 'unfaulting' mechanism exerts a first-order influence on the fabric of the global ocean floor and provides a physical explanation for reverse-faulting earthquakes in an extensional environment.

Literature Review of Pathogen Agnostic Molecular Testing of Clinical Specimens From Difficult-to-Diagnose Patients: Implications for Public Health.

To better identify emerging or reemerging pathogens in patients with difficult-to-diagnose infections, it is important to improve access to advanced molecular testing methods. This is particularly relevant for cases where conventional microbiologic testing has been unable to detect the pathogen and the patient's specimens test negative. To assess the availability and utility of such testing for human clinical specimens, a literature review of published biomedical literature was conducted. From a corpus of more than 4,000 articles, a set of 34 reports was reviewed in detail for data on where the testing was being performed, types of clinical specimens tested, pathogen agnostic techniques and methods used, and results in terms of potential pathogens identified. This review assessed the frequency of advanced molecular testing, such as metagenomic next generation sequencing that has been applied to clinical specimens for supporting clinicians in caring for difficult-to-diagnose patients. Specimen types tested were from cerebrospinal fluid, respiratory secretions, and other body tissues and fluids. Publications included case reports and series, and there were several that involved clinical trials, surveillance studies, research programs, or outbreak situations. Testing identified both known human pathogens (sometimes in new sites) and previously unknown human pathogens. During this review, there were no apparent coordinated efforts identified to develop regional or national reports on emerging or reemerging pathogens. Therefore, development of a coordinated sentinel surveillance system that applies advanced molecular methods to clinical specimens which are negative by conventional microbiological diagnostic testing would provide a foundation for systematic characterization of emerging and underdiagnosed pathogens and contribute to national biodefense strategy goals.

The impact of creatine kinase and base excess on the clinical outcome of crush injuries sustained during the Kahramanmaras/Turkey earthquakes on February 6, 2023.

The aim of the study is to determine the usefulness of base excess (BE) and creatine kinase (CK) in predicting the extent of damage to the extremities, the need for hemodialysis, and the likelihood of mortality in crush injuries. Our study included patients who were affected by the earthquakes that occurred in Kahramanmaras/Turkey on February 6, 2023 and were diagnosed with crush injuries. The study was a retrospective observational study. We used chi-square test, independent sample t test, analysis of variance (ANOVA) to examine whether CK and BE values can be used to predict damage to the extremities, hemodialysis requirement, and mortality. A total of 299 patients were included in the study. A statistically significant relationship was found between BE and extremity damage, hemodialysis requirement, and mortality (P < .005). A statistically significant difference was also seen in terms of extremity damage and hemodialysis requirement with CK (P < .001), while there was no statistically significant difference seen in mortality (P = .204). BE may serve as a predictive biomarker for the development of extremities damage, hemodialysis requirement, and mortality. CK is not predictive of mortality.

Prevalence of airway patency and air pocket in critically buried avalanche victims - a scoping review.

INTRODUCTION: Survival of critically buried avalanche victims is directly dependent on the patency of the airway and the victims' ability to breathe. While guidelines and avalanche research have consistently emphasized on the importance of airway patency, there is a notable lack of evidence regarding its prevalence. OBJECTIVE: The aim of this review is to provide insight into the prevalence of airway patency and air pocket in critically buried avalanche victims. METHODS: A scoping review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline extension for scoping reviews. MEDLINE and Cochrane databases, as well as additional manual searching was performed to identify literature reporting data on airway patency and the presence of an air pocket in critically buried avalanche victims. After eliminating duplicates, we screened abstracts and main texts to identify eligible studies. RESULTS: Of 4,109 studies identified 154 were eligible for further screening. Twenty-four publications and three additional data sources with a total number of 566 cases were included in this review. The proportion of short-term (< 35 min) to long-term burial (≥ 35 min) in the analysed studies was 19% and 66%, respectively. The burial duration remained unknown in 12% of cases. The prevalence of airway patency in critically buried avalanche victims was 41% while that of airway obstruction was 12%, with an overall rate of reporting as low as 50%. An air pocket was present in 19% of cases, absent in 46% and unknown in 35% of the cases. CONCLUSION: The present study found that in critically buried avalanche victims patent airways were more than three times more prevalent than obstructed, with the airway status reported only in half of the cases. This high rate of airway patency supports the ongoing development and the effectiveness of avalanche rescue systems which oppose asphyxiation in critically buried avalanche victims. Further effort should be done to improve the documentation of airway patency and the presence of an air pocket in avalanche victims and to identify factors affecting the rate of airway obstruction.

A robust optimization model for multi-objective blood supply chain network considering scenario analysis under uncertainty: a multi-objective approach.

Annually, different regions of the world are affected by natural disasters such as floods and earthquakes, resulting in significant loss of lives and financial resources. These events necessitate rescue operations, including the provision and distribution of relief items like food and clothing. One of the most critical challenges in such crises is meeting the blood requirement, as an efficient and reliable blood supply chain is indispensable. The perishable nature of blood precludes the establishment of a reserve stock, making it essential to minimize shortages through effective approaches and designs. In this study, we develop a mathematical programming model to optimize supply chains in post-crisis scenarios using multiple objectives. Presented model allocates blood to various demand facilities based on their quantity and location, considering potential situations. We employ real data from a case study in Iran and a robust optimization approach to address the issue. The study identifies blood donation centers and medical facilities, as well as the number and locations of new facilities needed. We also conduct scenario analysis to enhance the realism of presented approach. Presented research demonstrates that with proper management, crises of this nature can be handled with minimal expense and deficiency.

Assessment of using Google Trends for real-time monitoring of infectious disease outbreaks: a measles case study.

Measles remains a significant threat to children worldwide despite the availability of effective vaccines. The COVID-19 pandemic exacerbated the situation by leading to the postponement of supplementary measles immunization activities. Along with this postponement, measles surveillance also deteriorated, with the lowest number of submitted specimens in over a decade. In this study, we focus on measles as a challenging case study due to its high vaccination coverage, which leads to smaller outbreaks and potentially weaker signals on Google Trends. Our research aimed to explore the feasibility of using Google Trends for real-time monitoring of infectious disease outbreaks. We evaluated the correlation between Google Trends searches and clinical case data using the Pearson correlation coefficient and Spearman's rank correlation coefficient across 30 European countries and Japan. The results revealed that Google Trends was most suitable for monitoring acute disease outbreaks at the regional level in high-income countries, even when there are only a few weekly cases. For example, from 2017 to 2019, the Pearson correlation coefficient was 0.86 (p-value< 0.05) at the prefecture level for Okinawa, Japan, versus 0.33 (p-value< 0.05) at the national level for Japan. Furthermore, we found that the Pearson correlation coefficient may be more suitable than Spearman's rank correlation coefficient for evaluating the correlations between Google Trends search data and clinical case data. This study highlighted the potential of utilizing Google Trends as a valuable tool for timely public health interventions to respond to infectious disease outbreaks, even in the context of diseases with high vaccine coverage.

Assessment of the integrated disease surveillance and response system implementation in health zones at risk for viral hemorrhagic fever outbreaks in North Kivu, Democratic Republic of the Congo, following a major Ebola outbreak, 2021.

BACKGROUND: The Democratic Republic of the Congo (DRC) experienced its largest Ebola Virus Disease Outbreak in 2018-2020. As a result of the outbreak, significant funding and international support were provided to Eastern DRC to improve disease surveillance. The Integrated Disease Surveillance and Response (IDSR) strategy has been used in the DRC as a framework to strengthen public health surveillance, and full implementation could be critical as the DRC continues to face threats of various epidemic-prone diseases. In 2021, the DRC initiated an IDSR assessment in North Kivu province to assess the capabilities of the public health system to detect and respond to new public health threats. METHODS: The study utilized a mixed-methods design consisting of quantitative and qualitative methods. Quantitative assessment of the performance in IDSR core functions was conducted at multiple levels of the tiered health system through a standardized questionnaire and analysis of health data. Qualitative data were also collected through observations, focus groups and open-ended questions. Data were collected at the North Kivu provincial public health office, five health zones, 66 healthcare facilities, and from community health workers in 15 health areas. RESULTS: Thirty-six percent of health facilities had no case definition documents and 53% had no blank case reporting forms, limiting identification and reporting. Data completeness and timeliness among health facilities were 53% and 75% overall but varied widely by health zone. While these indicators seemingly improved at the health zone level at 100% and 97% respectively, the health facility data feeding into the reporting structure were inconsistent. The use of electronic Integrated Disease Surveillance and Response is not widely implemented. Rapid response teams were generally available, but functionality was low with lack of guidance documents and long response times. CONCLUSION: Support is needed at the lower levels of the public health system and to address specific zones with low performance. Limitations in materials, resources for communication and transportation, and workforce training continue to be challenges. This assessment highlights the need to move from outbreak-focused support and funding to building systems that can improve the long-term functionality of the routine disease surveillance system.

Chemical release risk assessment in earthquake: Natech event scenario.

Introduction: In recent decades, an increase in natural disasters has led to the Natech events occurrence, which are technological accidents triggered by natural hazards. This study aims to assess the risk of chemical release of the H2S toxic gas following an earthquake from the refinery. Method: The Natech risk assessment was carried out in potential earthquake risk scenarios via a semi-quantitative method using Rapid-N software. The reference scenario was obtained using the Australian SMUG Model, which has presented precise prioritization. Findings: The Natech risk assessment has shown 40 possible earthquake risk scenarios from 5 enclosing Faults in Tehran (North Tehran, Mosha, North Ray, South Ray, and Kahrizak) with an extension of more than 15 km. The earthquake moment magnitudes of 7.5, 7.1, 6.5, and 5.9 were obtained on the Richter scale and at two Focal depths of 5 and 10 km. The South-Ray Fault (HSR-1) was selected as the reference scenario with a moment magnitude of 7.5 on the Richter scale at a Focal depth of 5 km and a distance of 5.5 km from the earthquake epicenter. The highest probability of Natech risk has shown the release of H2S toxic gas in an area with a radius of 6.59 km from the studied vessel in atmospheric stability conditions. Conclusion: Legislation in line with risk reduction, planning for the transfer of potentially dangerous industries to outside urban areas, monitoring land use laws, and promoting coordination between the government, industries, and people in the management of risks caused by industries containing hazardous substances and processes, assessing the risk of Natech events and their consequences, strengthening risk communication and the installation of early warning systems, and public education to adopt personal and socially safe behaviors when facing natural disasters are recommended.

Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters.

Taiwan, frequently affected by extreme weather causing phenomena such as earthquakes and typhoons, faces a high incidence of rockfall disasters due to its largely mountainous terrain. These disasters have led to numerous casualties, government compensation cases, and significant transportation safety impacts. According to the National Science and Technology Center for Disaster Reduction records from 2010 to 2022, 421 out of 866 soil and rock disasters occurred in eastern Taiwan, causing traffic disruptions due to rockfalls. Since traditional sensors of disaster detectors only record changes after a rockfall, there is no system in place to detect rockfalls as they occur. To combat this, a rockfall detection and tracking system using deep learning and image processing technology was developed. This system includes a real-time image tracking and recognition system that integrates YOLO and image processing technology. It was trained on a self-collected dataset of 2490 high-resolution RGB images. The system's performance was evaluated on 30 videos featuring various rockfall scenarios. It achieved a mean Average Precision (mAP50) of 0.845 and mAP50-95 of 0.41, with a processing time of 125 ms. Tested on advanced hardware, the system proves effective in quickly tracking and identifying hazardous rockfalls, offering a significant advancement in disaster management and prevention.

Comparison of analysis methods to classify cholera hotspots in Ethiopia from 2015 to 2021.

Cholera continues to represent a major public health concern in Ethiopia. The country has developed a Multi-sectoral National Cholera Elimination Plan in 2022, which targets prevention and control interventions in cholera hotspots. Multiple methods to classify cholera hotspots have been used in several countries. Since 2014, a classification method developed by United Nations Children's Fund has been applied to guide water, sanitation and hygiene interventions throughout Sub-Saharan Africa based on three outbreak parameters: frequency, duration and standardized attack rate. In 2019, the Global Task Force on Cholera Control (GTFCC) proposed a method based on two parameters: average annual cholera incidence and persistence. In 2023, an updated GTFCC method for multisectoral interventions considers three epidemiological indicators (cumulative incidence, cumulative mortality and persistence,) and a cholera-case confirmation indicator. The current study aimed to classify cholera hotspots in Ethiopia at the woreda level (equivalent to district level) applying the three methods and comparing the results to optimize the hotspot targeting strategy. From 2015 to 2021, cholera hotspots were located along major routes between Addis Ababa and woredas adjacent to the Kenya and Somalia borders, throughout Tigray Region, around Lake Tana, and in Afar Region. The multi-method comparison enables decision makers to prioritize interventions according to a sub-classification of the highest-priority areas.