Hospital surge capacity is pivotal for disaster response, yet the effectiveness of assessment and planning tools remains underexplored.

This systematic review evaluates the reliability, validity, and applicability of surge capacity tools across disaster scenarios.

Following PRISMA guidelines, we analyzed 24 Q1 studies (PubMed, Scopus) using the PICO framework. Risk of bias was assessed via ROBINS-E, and meta-analysis (random-effects model) quantified pooled effect sizes (ES). Subgroup analyses compared simulation tools, surveys, and resource strategies.

The combined ES was 0.74 (95% CI: 0.67–0.82), indicating moderate improvement in preparedness. Simulation tools (Group A) showed the highest consistency (ES = 0.81, I2 = 0%), while resource strategies (Group C) had wider variability (ES = 0.71, I2 = 74.42%). Egger’s regression revealed publication bias (P = 0.004), and heterogeneity was substantial (I2 = 76.70%).

Simulation-based tools are most effective for surge capacity, whereas resource strategies require contextual adaptation. Policymakers should prioritize standardized benchmarks and DSS integration, with future research addressing equity and real-world implementation gaps.

The COVID-19 pandemic disrupted education and training which led academia to revise well-established instructional content and strategies. This report described and evaluated the curricular response of public health preparedness at Penn State to the COVID-19 pandemic.

We describe an online, hybrid course focused on the development, approval, and dissemination of the SARS-CoV-2 vaccines. The course was offered in the spring of 2021 and covered real-time laboratory, public health, emergency management, homeland security, medical, and policy aspects of the vaccines. Additionally, we report the student evaluation results of those who completed the course.

The median and mode scores for student evaluations were 7, on a scale of 1 (lowest) to 7 (highest). Students enjoyed the instructors because they were employed in strategic positions and explained real-world challenges. Students reported the course as “timely” and “breaking down complex concepts into simple understanding.”

Penn State responded to the COVID-19 pandemic with an innovative course that developed students’ real-time understanding of pandemic response. Students gained knowledge and skills relevant to the practice of public health. Based on the positive student feedback, the course will serve as a model for future classes on public health and emergency management.

Natural disasters often require the rapid deployment of onsite medical team, such as World Health Organization (WHO) certified Emergency Medical Team (EMT) 2. This work analyzes the recent experience of the French EMT-2 Civil Security’s projectable surgical field hospital, with a specific attention to its deployment.

Retrospective review of mission reports, theatre logbooks with additional staff interviews were studied to analyze the deployment of a projectable surgical field hospital from beginning of catastrophe to first surgery.

Since its EMT-2 qualification, the EMT-2 was deployed 3 times, in 2023 at Gölbasi (Adiyaman, Turkey), in 2023 at Derna (Cyrenaica, Libya) and in 2024 at Mamoudzou (Mayotte, France) showing its ability to fulfill its surgical mission in various situations. Nonetheless, the deployment of the surgical field hospital is frequently delayed due to geopolitical but mainly logistical constraints, thereby impeding the hospital’s early efficacy.

When on site, the EMT-2 facility can provide surgical care within less than 24 h. Nevertheless, reaching the deployment site is long which limits the early efficacy of the projectable surgical field hospital. This could be bypassed by the initial projection of a smaller surgical structure to which will be added the remaining of the EMT-2.

Melee-based terrorism refers to attacks involving non-projectile weapons such as knives or blunt objects. This study analyzes the prevalence, injury patterns, and mortality associated with melee-based terrorist attacks.

A retrospective analysis was conducted using the Global Terrorism Database from 1970 to 2020 to identify and characterize melee-related terrorist attacks worldwide. Incidents were included if melee weapons were the primary mode of assault and included injuries or death. Descriptive statistics were used to summarize attack characteristics and casualties, and negative binomial regression was performed to identify predictors of mortality outcomes.

A total of 1,505 melee-related terrorist attacks were identified, resulting in 5,528 injuries and 5,110 fatalities. Each incident caused an average of 3.40 deaths and 3.67 injuries. European Region accounted for the largest proportion of attacks (25.65%), while African Region exhibited the highest death ratio, with mean number of deaths per attack at 14.54, demonstrating significantly greater rate ratio of deadly attacks (IRR = 18.33; 95% CI 10.18–33.01). Knives and sharp objects were the predominant weapons (58.63%), with the greatest rate ratio of death (IRR = 10.32, 95% CI 6.07–17.54).

Melee-related terrorist attacks represent a persistent and escalating global threat with substantial mortality and injury burden.

The aim of this study is to develop disaster specific classification model specific to India, that extracts population emotional states during disasters from geo-referenced social media data. The developed model is also examined considering the case of Chennai floods 2015.

Using tweets from various disaster situations in India, a domain-specific training corpus was created. After training and testing different machine learning models, the top-performing model was used to classify emotions from tweets collected between November and December 2015 from Chennai. Using QGIS and Z-proportional testing, the spatial and temporal variations of negative emotions were further investigated.

Emotions were extracted from geo-tagged tweets that were posted during the 2015 Chennai floods using the SVM classifier (accuracy: 0.84). The findings revealed that, in comparison to before the flood, there was a significant increase in sadness (23%) and fear (6%) during the disaster. Sadness and disgust decreased in post flood period. Distinct spatiotemporal patterns of emotional expression were identified, which showed clusters of anger in Perungudi, fear in Adyar, and grief and disgust in Teynampet and Sholinganallur zones.

This study remains a proof-of-concept confirming the importance of social media analytics during disasters for directing focused response and recovery activities.

To assess the current levels of knowledge, attitudes, practices (KAP), and institutional support regarding Chemical, Biological, Radiological, and Nuclear (CBRN) disaster preparedness among anesthesia professionals in India, and to identify predictors and barriers to effective readiness.

A cross-sectional, web-based survey was conducted among 294 anesthesia professionals across India. The validated questionnaire assessed 4 domains: knowledge (11 items), attitude (6 items), practice (8 items), and institutional support (9 items). Descriptive statistics, multivariable linear regression, and non-parametric group comparisons were performed. Thematic analysis was applied to open-ended responses.

Only 10.9% of respondents reported prior CBRN training, and 8.2% had participated in drills. Trained participants demonstrated significantly higher knowledge scores (9.66 ± 1.32 vs. 7.51 ± 1.31; P < 0.001). CBRN training and trauma network affiliation independently predicted knowledge. Attitude, practice, and institutional scores showed no significant association with training status, designation, or institution type. Barriers included lack of formal training (n = 224), inadequate PPE (n = 183), and absence of SOPs (n = 177). Thematic analysis revealed five key themes, emphasizing the need for structured training and role clarity.

CBRN preparedness among Indian anesthesiologists remains suboptimal. Cognitive gains from training are evident, but broader institutional and behavioral readiness requires systemic reforms, stakeholder engagement, and simulation-integrated curricula.

When large-scale disasters exhaust civilian federal agencies’ assets, the U.S. Federal Emergency Management Agency (FEMA) can issue mission assignments to the Department of War (DoW) to leverage its unique, self-sustaining logistical and operational capabilities.

This study characterized DoW contributions to U.S. disaster response by analyzing 4,065 FEMA mission assignments issued between 2012 and 2024. Mission assignments were analyzed by geographic location, disaster type, event timing, personnel types deployed, and associated Emergency Support Function.

The DoW supported 37% of all original FEMA mission assignments during the study period. Activity peaked during the 2017 hurricane season and the COVID-19 pandemic. Tropical cyclones and hurricanes in low-lying coastal states and island territories, and biological incidents in densely populated areas, were the primary drivers for DoW assistance. The DoW primarily supported Emergency Support Functions relating to Public Works and Engineering, Logistics, and Information and Planning activities.

As an essential federal partner in managing increasingly complex, large-scale disasters, a data-informed picture of the DoW’s contributions is vital for strategically optimizing operational planning and resource deployments to protect the health and well-being of the American public.

As disasters intensify alongside population aging, Japan has introduced welfare evacuation shelters for individuals requiring care. Following the 2024 Noto Peninsula Earthquake, Umyu-dosora was designated as one such shelter; however, data on its actual use remain limited. This study aimed to assess demand for welfare evacuation shelters by examining temporal trends in resident numbers after the disaster.

Data on evacuees’ admission and discharge dates at Umyu-dosora were extracted from a cloud-based Kintone database, covering January-March 2024. Records with missing admission or discharge dates were excluded.

Among the 83 evacuees with identifiable records, the most common age group for both sexes was 70-79 years. Age or sex data were unavailable for 22 individuals. The shelter began operating on January 8, 2024. Resident numbers peaked at over 40 in late January, stabilized at approximately 30 throughout February, and gradually declined by late March. The facility continued to accommodate some evacuees even after assuming its original function as a group home for individuals with mental illness.

The high demand for evacuation support for individuals requiring long-term care during the first month after the Noto Peninsula Earthquake underscores the need for the planned establishment of welfare shelters.

This study examined the relationship between climate change awareness and belief in disaster preparedness among university students and explored the mediating role of social media use purposes.

A cross-sectional survey was conducted with 418 university students. Data were collected using validated scales measuring climate change awareness, disaster preparedness belief, and social media use purposes. Pearson correlation, multiple linear regression, and bootstrap-based mediation analysis (PROCESS Macro Model 4) were performed.

Climate change awareness was positively associated with both social media use purposes (r = .322, P < 0.001) and disaster preparedness belief (r = .307, P < 0.001). Regression analysis showed that climate change awareness (B = 0.185, P < 0.001) and social media use purposes (B = 0.243, P < 0.001) significantly predicted disaster preparedness belief. Mediation analysis indicated that social media use purposes partially mediated the relationship between climate change awareness and preparedness belief.

Higher climate change awareness was associated with stronger disaster preparedness beliefs among university students. Social media use purposes partially mediate this relationship and function as a complementary digital mechanism linking climate awareness to preparedness beliefs

To evaluate the relative effectiveness of voluntary social distancing appeals versus mandated lockdowns in reducing population mobility during the COVID-19 pandemic, using India as a developing country case study.

This study analyzed daily mobility data from Google’s Community Mobility Reports across six location categories between February 16 and May 31, 2020. A geographic-level regression model was employed to isolate voluntary mobility changes during India’s 14-hour voluntary Janta Curfew prior to the mandatory nationwide lockdown. The model controlled for pandemic severity, health infrastructure, and socioeconomic factors.

Conservative estimates indicate that voluntary measures accounted for a substantial proportion of overall mobility declines, ranging from 27% to 71% depending on the location. The most pronounced voluntary reductions occurred in retail and recreational centers, parks, and transit stations.

Timely and targeted non-mandated appeals can achieve meaningful behavioral change, complementing formal restrictions. These findings offer critical guidance for health promotion policy, demonstrating that voluntary public compliance can be a viable, flexible strategy for pandemic management, particularly in resource-limited settings where strict mandates may cause severe socioeconomic strain.

This study examines factors influencing the development of disaster meal provision manuals in food service facilities in earthquake-prone regions of Japan. Given the increasing frequency of natural disasters, ensuring meal service facilities’ preparedness is crucial to safeguarding vulnerable populations, including infants, pregnant women, the elderly, and individuals with chronic conditions.

A survey of 866 meal service facilities in Mie Prefecture, Japan, was conducted to assess disaster preparedness measures. Key factors analyzed included the presence of registered dietitians, disaster preparedness drills, and stockpiling of balanced emergency food supplies. Logistic regression analysis was used to identify predictors of manual development.

The presence of registered dietitians (OR = 2.82, 95% CI: 1.95-4.08), disaster preparedness training (OR = 3.15, 95% CI: 2.18-4.57), and balanced emergency food stockpiles (OR = 2.52, 95% CI: 1.66-3.83) were significant predictors of disaster meal provision manual development.

Findings underscore the essential role of dietitians in disaster nutrition planning and highlight the need for proactive preparedness strategies to enhance food security and facility resilience. These insights can inform policy recommendations in Japan and other disaster-prone regions facing similar challenges.

A nuclear detonation will result in thousands of casualties who will need to be monitored for the occurrence of delayed complications from their exposure to radiation. The National Academies of Sciences have published a report on the key elements of the long-term health monitoring of populations after an improvised nuclear device (IND) detonation incident.

We describe the results of a modified Delphi study where we sought consensus among a group of experts on the importance and difficulty of achieving the items in a list of key elements they were presented with.

The expert consensus meeting included 27 experts from relevant disciplines and agencies. Consensus was reached in round 3 of the Delphi process on the initial list of 79 items that were generated during the first 2 rounds. Consensus was reached on 59 items regarding the level of importance and on 13 items regarding the difficulty of achieving the element in the design of a long-term health study.

The items identified in this study, including those where consensus was met among the experts, can guide emergency and public health planners in preparing for a long-term population health program after an IND incident.