Articles tagged with Disaster Management
A new UN University publication reveals that many people in England fail to take action to protect themselves during heatwaves despite receiving warnings. The most common reason is a lack of perception of personal risk, highlighting the need for improved communication and long-term adaptation strategies.
A new study reveals that over half of the 100,117 sites listed on the National Register of Historic Places face measurable wildfire exposure. The western United States and regions like Oklahoma, Arkansas, and the southeastern coast are particularly at risk due to climate change.
A new study of an Israeli hospital's response to the October 7 attacks reveals critical gaps in communication, staffing, logistics, and casualty distribution. The findings offer practical lessons that could help hospitals worldwide prepare for prolonged armed conflicts and other large-scale emergencies.
Researchers found that crowd crushes and stampedes may develop gradually through repeated physical contact and pushing. Understanding these conditions can help improve safety planning, reduce injuries, and identify high-risk zones.
A University of Houston professor is using artificial intelligence to connect roadway crash data, identifying pavement conditions associated with elevated crash risk. The study assesses pavement structure, surface condition, road geometry and crash records, helping transportation agencies select candidate pavement-safety projects.
Researchers analyzed phone data from Marshall Fire evacuees, finding they chose destinations based on social connections and community resemblance. Those with stronger social networks were more likely to return home over time.
Researchers have developed pressurized sand dampers that can withstand extreme temperatures and provide a cost-effective solution for structures. These dampers can be replaced or repaired quickly, reducing economic losses from vibrations in high-rise buildings.
A study found that social media helped spread information during the Rolling Fork tornado, but also revealed communication challenges facing rural areas due to limited broadband access and fragmented media. Researchers suggest a need for personalized messaging strategies to address diverse community needs.
Researchers identified nine typical disaster chain types driven by endogenic and exogenic dynamics, highlighting the need for interdisciplinary integration to understand complex geological disaster chains. The study also emphasizes the importance of 'multi-critical phase transitions' in understanding dynamic processes of disaster chains.
A study found that forecast error types influence public emotion during disasters, with anxiety and worry being the most common emotions. The researchers suggest that communicating forecast uncertainty effectively could improve public trust and reduce emotional distress during future extreme weather events.
Healthcare-associated transmission of Andes virus is uncommon but can occur when infection is not recognized early or protective measures are delayed, research suggests. Implementing transmission-based precautions at earliest stages of infection can prevent transmission in healthcare settings.
Researchers have introduced laser reflective tomography to overcome the speed-resolution trade-off in NLOS imaging, achieving kilometer-scale high-resolution imaging without scanning mechanisms. This innovative approach combines single-point detection with multi-angle projection data for accurate scene reconstruction.
A University of Houston engineering professor developed a mathematical model to help decision-makers decide where to spend limited dollars on infrastructure resilience. The model accounts for real-world uncertainty and identifies critical assets to invest in, providing the greatest benefit before disaster strikes.
A study by researchers at Science Tokyo found that non-structural disaster measures in Macau significantly improved coastal resilience and reduced storm-surge impacts. The city's emphasis on evacuation guidance, communication, monitoring systems, and public awareness helped build trust and reduce disaster impacts.
A new study from UC Santa Barbara reveals that the number of roads out of a community may be one of the strongest predictors of wildfire fatalities. Communities with six or fewer exits have a sharp drop in fatalities, while additional roads offer little further protection.
A study using real-time data from the 2024 Noto Peninsula earthquake response found that unclear tasks, command structures, and lack of meal and rest breaks significantly contributed to self-reported fatigue among disaster responders. Fatigue can compromise decision-making, lead to poor care outcomes, and affect public safety.
A new open-source trajectory-planning system, MIGHTY, has been developed by researchers at MIT and the University of Pennsylvania. The system enables robots to generate smooth flight paths while reacting to obstacles in real-time, making it suitable for applications such as search-and-rescue, last-mile delivery, and industrial inspection.
A new study by Cal Poly faculty found that building density, not urban trees, was the strongest predictor of home loss in Los Angeles firestorms. The study examined 15,082 structures and 52,893 tree canopies within the Eaton and Palisades fire scars.
Researchers found two distinct growth patterns in river deltas, uniform and composite, which can help engineers estimate land build-up based on channel length. This insight will aid coastal restoration and flood protection efforts by directing limited resources to areas where they can make the most impact.
Recent studies investigate the relationship between weather conditions and extreme events like heat-related mortality, tropical cyclone hazards, and changes in precipitation patterns. Researchers also explore new modeling methods to predict visually appealing atmospheric phenomena like 'ornamental twilight'.
Researchers at the University of Houston have developed an AI-driven framework to extract and analyze historical flood insurance maps, uncovering significant changes in flood hazard areas. The study reveals that flood risks have expanded in two areas and reduced in one, with critical consequences for resilience and exposure.
Researchers from Kyoto University developed a numerical model to evaluate mangrove wave attenuation, revealing that root submersion and water depth significantly impact wave reduction. The study's findings suggest that mangroves can mitigate disasters and help communities adapt to climate change.
A University of Kansas engineer is conducting research on outdated manufactured housing wind-safety codes, which have remained unchanged since 1994. The study uses a hurricane simulator to test the structural response and failure points of manufactured homes under varying wind conditions.
Researchers use machine learning to characterize recovery processes, predict outcomes, and optimize strategies for restoring critical infrastructure systems. The review highlights the potential of reinforcement learning to identify effective repair sequences.
Researchers developed a dynamic optimization model to help NGOs in rural Africa optimize maintenance schedules, reducing downtime and logistics costs. The model achieved significant reductions in maintenance downtime, ranging from 47-62% in Ethiopia and 53% in Malawi.
Researchers have developed a new framework to detect possible damage in concealed cold-formed steel construction framing materials, utilizing ground-penetrating radar and artificial intelligence. The technology allows for rapid detection of damage, enabling inspectors to verify only flagged spots without removing walls or cladding.
Researchers developed a color-guided depth recovery method for non-repetitive LiDAR images to improve real-time crowd monitoring during disasters. The method reconstructs continuous depth structures while preventing over-smoothing and overfilling gaps, achieving improved depth accuracy and structural consistency.
Current early warning systems often fail to lead to action due to varied reactions to general messages. Researchers propose EW4All+U with personalized information based on location, mobility and circumstances. The technology exists, but challenges remain in scaling up solutions.
A Brazilian study developed a new statistical analysis method that better predicts landslide risk. The approach uses the Gaussian distribution to define the weight of each contributing factor objectively. It was validated based on an inventory of landslides in São Paulo, where 65 people were killed.
A new 3D model of the fault beneath the Marmara Sea reveals where a future major earthquake could take place, helping improve earthquake forecasts. The study uses magnetotelluric measurements to identify distinct high-resistivity and low-resistivity zones, shedding light on ongoing processes of fault mechanics.
Nature-based solutions can significantly reduce flood impacts by slowing and absorbing runoff, offering added benefits such as improved air quality and biodiversity. Public awareness and education are key to expanding support for these approaches, with communities needing clear communication about flood risks and benefits.
A newly designed mechanophore, called DAANAC, was developed to provide early warning against mechanical failure while resisting heat and UV. It features a stable and fluorescent diarylacetonitrile radical coupled to an alkoxycarbonyl radical that quenches fluorescence.
A recent study recreated the July 4 flood conditions and found multiple spots upstream where local communities could have placed water level monitors to give early warnings about rising water. The research aims to make those sensors cheap, easily accessible, and open source so anyone can use them.
A study analyzing Medicare claims data found that older adults who lived through Hurricane Harvey had a 3% elevated risk of dying within 1 year. Mortality risk was highest among those with chronic health conditions like Alzheimer's disease, and Black and Hispanic/Latino populations experienced higher mortality risks than other groups.
Researchers developed a three-stage framework to analyze uncertainties in energy transitions, focusing on climate change and institutional inefficiency. The Puerto Rico case study shows that these factors are crucial in determining total system costs.
Researchers will develop strategies to stabilize eroding channels and enhance flood-warning capabilities using artificial intelligence. The partnership aims to improve stormwater management and environmental protection in the region with forecasts suggesting population growth could double by 2050.
Research shows that flooding in delta cities like Shanghai can expand by up to 80% and be much deeper by 2100 due to extreme climate events, sea-level rise and land subsidence. A major adaptation effort is required to raise defences and construct mobile flood barriers.
A comprehensive review of 19 multi-day events found that nearly 70% of reported emergencies were infectious disease outbreaks, with influenza, measles, and meningococcal disease being the top causes. Foodborne illnesses accounted for over one in five incidents, often linked to poor food handling practices.
Researchers develop a novel integrated data model that merges construction and geospatial information standards to manage bridges' 3D geometry data and maintenance records. This framework enables accurate damage location assessment, repair prioritization, and predictive maintenance, leading to improved infrastructure safety and longevity.
The Kansas Flood Mapping Dashboard uses stream gauge data and terrain-based models to generate flood inundation maps, providing critical information for emergency management. The dashboard is a result of collaborative research efforts between KU researchers and state agencies, utilizing science and research for the benefit of the state.
Researchers propose a novel approach to ensure uniform backfilling throughout borehole depth, addressing immediate safety concerns and long-term sustainability. The circulating mixing method improves process parameters and quality control through advanced numerical simulations.
Researchers warn of structural weakening in urban areas as a result of groundwater overexploitation, posing risks to millions of people. Satellite radar data reveals nearly 1.9 million people exposed to subsidence rates greater than 4 millimeters per year.
The game, developed in partnership with Polk County Emergency Management, will force players to grapple with uncertainty and trade-offs in their actions. It aims to add intensity and engagement to traditional training methods, allowing emergency responders to make timely and relevant decisions.
Researchers analyzed power outage data and weather records to identify planning vulnerabilities and criticality as drivers of prolonged local outages. Targeted interventions, such as isolating critical nodes and improving operational flexibility, can reduce customer outages by up to 49.5%.
The CERCat consortium aims to improve the field of catastrophe modeling by uniting academic rigor with practical expertise, driving real-world solutions that enhance disaster resilience. The consortium is prioritizing projects on multihazard fragility curves, wildfire fragility curves, and AI-powered post-disaster damage assessment.
A new framework developed by Cranfield University aims to balance AI's benefits with safety and fairness concerns in disaster response. The study shows the framework outperforms human operators and conventional AI systems, providing 39% higher accuracy across various scenarios.
A team led by Joe Ripberger from the University of Oklahoma aims to create a unified national approach to wildfire warnings. The project will focus on understanding fire and atmospheric interactions, social and behavioral science questions, and building a transdisciplinary network with practitioners and researchers.
The University of Oklahoma is developing an AI-driven framework to predict tree failures before extreme weather events. The TREE-CARE project will integrate advanced technologies with local knowledge to develop solutions that directly benefit communities.
A new UC Berkeley-led study demonstrates how home hardening and defensible space can significantly reduce wildfire risk. The research found that these strategies, when combined, can double the number of homes that survive a blaze and reduce structure losses by up to 50%.
A study by University of New Hampshire researchers found that communities with higher walkability scores experienced a 4% reduction in average pandemic-related mental health deterioration. The study analyzed national census and survey data to measure the impact of walking on mental health during the pandemic.
Climate-related disasters pose significant disruptions to US drug manufacturing facilities, affecting nearly two-thirds of production sites. Researchers assessed the impact of disaster events on counties with US drug production facilities and found that nearly two-thirds were located in areas affected by at least one disaster declaration.
University of Houston researchers are developing an AI-powered dashboard for Florida food pantries, aiming to streamline stakeholder collaboration and distribute resources to families in need. The tool will enable emergency coordinators to respond quickly to spikes in demand, prioritizing the needs of vulnerable populations.
A new study by University of Virginia researchers reveals high rates of posttraumatic stress disorder (PTSD) and major depression among residents exposed to the 2023 chemical spill. The survey of 1,000 adults found elevated psychological toll with half reporting worsening physical health symptoms.
Researchers from Shibaura Institute of Technology used machine learning algorithms to predict bearing layer depth and assess liquefaction risk. The study found that random forest models outperformed others, especially with increasing spatial data density.
A Texas A&M University study reveals that community cohesion prior to a natural disaster is significantly linked to perceived resilience afterward. The research found that explicit strategies for building community trust and increasing volunteerism rates should be added to emergency preparedness programs.
A new framework developed by Northwestern University and UCLA scientists integrates various water-related processes with a machine-learning model to predict landslide threats. The framework identifies three main pathways leading to landslides: intense rainfall, rain on already saturated soils, and melting snow or ice.
The University of Tokyo researchers developed an unmanned aerial vehicle (UAV) that can withstand ocean currents and wind, enabling the acquisition of reliable seafloor measurements. The system achieved a horizontal root mean square error of approximately 1–2 cm, comparable to existing vessel-based systems.
The WUI-NITY simulator, developed by a global collaboration of researchers, visualises bushfire spread and people movement to calculate evacuation times. It has been validated in large-scale community evacuation drills and is freely available online for use by authorities and researchers.
Researchers developed a new equation to predict seismic wave propagation in magma containing crystals and bubbles, revealing how crystal content influences wave velocity and waveform properties. The analysis also showed that bubble content affects attenuation effects, with discernible differences emerging between models.
Researchers developed a new nanomaterial and fiber structure that improves power output of piezoelectric fibers, generating enough electricity to light LEDs or run small devices. The fiber sensor can detect external forces and transmit data wirelessly for real-time landslide detection systems.