Search Results (457)

The COVID-19 pandemic led to a dramatic increase in healthcare-associated infections and antimicrobial resistance, particularly in intensive care units (ICUs). The aim of this study was to provide a comprehensive genomic characterisation of all clinically significant opportunistic pathogens (OPs) isolated from patients and the hospital environment in COVID-19 ICUs, and to use these data to reconstruct transmission pathways, identify reservoirs, and assess the molecular mechanisms of antimicrobial resistance and virulence. Whole-genome sequencing (WGS) was performed on 175 isolates isolated from patients and the hospital environment (including personal protective equipment, PPE) between 2021 and 2023. The species collection included nine OP species. Bioinformatic analysis included multilocus sequence typing, core genome single-nucleotide polymorphism analysis, phylogenetic reconstruction, and in silico detection of resistance and virulence genes and plasmid replicons. High-risk multidrug-resistant (MDR) clones were identified among Klebsiella pneumoniae, Acinetobacter baumannii, Escherichia coli, and Staphylococcus aureus. Core genome SNP analysis confirmed direct transmission of K. pneumoniae between patients and healthcare worker medical gloves. PPE was identified as a major reservoir, accounting for 68.4% of environmental isolates. The study demonstrates the power of WGS for high-resolution epidemiological surveillance, confirms the critical role of contaminated PPE in nosocomial transmission, and highlights the dominance of internationally spreading MDR clones in COVID-19 ICUs. Full article

Background/Objectives: This study aimed to evaluate radiation safety knowledge, perceptions, and self-reported protective practices among healthcare workers (HCWs) working in radiology and nuclear medicine departments, with particular attention to occupational dose limits, radiation protection principles, dosimetry, and personal protective equipment use. Methods: A cross-sectional survey was conducted among 138 HCWs (25 specialist doctors, 101 technicians, 9 nurses and 3 radiophysicists) in radiology and nuclear medicine departments from May to June 2024. Data were collected using a structured 31-item survey assessing sociodemographic characteristics, perceived radiation exposure risk, knowledge of radiation protection principles and occupational dose limits, dosimeter use, personal protective equipment use, and awareness of institutional radiation safety procedures. The total knowledge score was calculated by summing correct responses to knowledge items (range: 0–10) and analyzed as a continuous outcome using multivariable linear regression with HC3 robust standard error. Because of the small and uneven distribution of some subgroups, item-level subgroup comparisons were interpreted descriptively and cautiously. Results: Although most HCWs reported receiving radiation safety information through formal education or institutional training, important knowledge and self-reported practice gaps remained. While 96.4% perceived themselves to be at high risk of radiation exposure, 61.6% reported not using any PPE in routine practice and 21.0% reported not using a dosimeter. Only 13.8% correctly identified the 5-year average permissible occupational dose, whereas 32.6% correctly identified the annual maximum dose limit. Knowledge of ionizing-radiation methods was higher among postgraduates than undergraduates (100% vs. 27.5%, p < 0.001) and among nuclear medicine staff than radiology staff (100% vs. 37.8%, p < 0.001). Knowledge of all three basic radiation protection methods was also higher among postgraduates than undergraduates (100% vs. 15.6%, p < 0.001). Because some subgroup distributions were small and uneven, these item-level subgroup findings should be interpreted descriptively and with appropriate caution. In multivariable linear regression with HC3 robust standard errors, technicians (B = −3.09, 95% CI = −3.52 to −2.67, p < 0.001) and nurses (B = −3.84, 95% CI = −5.26 to −2.43, p < 0.001) had lower total knowledge scores than specialist doctors. Nuclear medicine was associated with a higher total score than radiology (B = 2.33, 95% CI = 0.81 to 3.85, p = 0.003), whereas >3 years of work experience was associated with a lower score than ≤3 years (B = −1.53, 95% CI = −2.40 to −0.66, p = 0.001). When postgraduate education was evaluated instead of professional role because of collinearity, postgraduate education was associated with a higher total knowledge score. Because of the cross-sectional design, these associations should not be interpreted as causal. The internal consistency of the knowledge subscale was minimally acceptable (Cronbach’s alpha = 0.694). Conclusions: Significant gaps and variations were observed in radiation safety knowledge and self-reported practices among HCWs. These patterns differed according to educational level, professional role, departmental affiliation, and experience; however, they should be interpreted in light of the cross-sectional design and the small and uneven distribution of some subgroups. These findings identify potential areas for future institutional quality-improvement efforts, including targeted education programs and review of radiation safety policies, whose effectiveness should be evaluated in future studies. Full article

Occupational health and safety (OHS) malpractices may increase the risk of occupational injuries and are a significant public health problem in the iron and steel industries, often leading to disability and death. Information on OHS practices related to occupational injuries in the iron and steel industries is limited in many countries. This study aimed to assess OHS practices in relation to occupational injuries among workers in the iron and steel industries in Tanzania. A cross-sectional study was conducted among 321 production line workers. Data were collected through interviews, using a structured OHS questionnaire and the modified International Labour Organization (ILO) injury assessment tool. A total of 209 workers had experienced an occupational injury in the past year. According to univariate regression analyses, the safety practice variables ‘safety inspections’ and ‘use of personal protective equipment’ were significantly associated with occupational injury. However, after adjusting for sociodemographic and organizational factors, including years of work experience, work section, daily working hours, and shift work, these associations were no longer statistically significant. Working in the rolling mill, having less than four years of work experience, working more than 10 h per day, and performing shift work were significant predictors of occupational injuries. These factors attenuated the associations between safety practices and occupational injuries. The severity of injuries was found to be related to the accessibility of PPE. The findings suggest that work experience and organizational characteristics play a critical role in shaping occupational injury risk, highlighting the need for multifaceted interventions that integrate effective safety practices, work experience and organizational measures to improve worker safety in Tanzania’s iron and steel industry. Full article

Personal health and safety are significant concerns across agricultural education, specifically agricultural mechanics. While hearing safety has been discussed for numerous years as a shortcoming in overall safety actions, it has been identified that attitudes and perceptions of sound and noise within agricultural settings are not aligned. This research continues work to focus on students’ understanding of and application of safety culture within an agricultural mechanics environment. Through direct and indirect exposure to noise levels, students reflected on and identified their use and intended use of hearing personal protective equipment (PPE). Pre- and post-instructional data aided in establishing students’ thresholds to use proper personal protective equipment and identify their perceptions of the decibel (dB) outputs for commonly used power tools in an agricultural laboratory setting. Course reflections alarmingly show a disconnect between intention and practice as many students do not utilize hearing PPE. While indicated threshold values and tool-specific PPE use align with the National Institute for Occupational Safety and Health’s recommended hearing PPE guidelines, the self-reported hearing PPE use results are concerning. While knowledge and application gaps still need to be addressed, based on this exploratory study, bounded in a single instructional context, continued exposure through direct and indirect instruction leads to increased knowledge of sound levels. Full article

Firefighters often perform multiple consecutive bouts of high-intensity work in hot environments, which can lead to physiological fatigue and increased health risks. This study examined changes in core temperature, skin temperature, and heart rate during recovery periods following repeated bouts of work in recruit firefighters (n = 10) across a full day of outdoor training. Participants completed four work–rest cycles consisting of firefighting drills performed in full personal protective equipment (PPE), followed by passive recovery after PPE removal. Physiological measurements were recorded one minute prior to recovery and then at 5, 10, and 20 min throughout recovery. Skin temperature and heart rate decreased significantly (p < 0.05) within 5–10 min of recovery in most rounds. However, core temperature required at least 20 min to significantly decline (p < 0.05). These findings suggest that shorter recovery periods may be sufficient for heart rate and skin temperature to return to baseline, whereas longer recovery periods are needed for heat to dissipate from the core, especially as work intensity increases. Thus, standard rehabilitation protocols may be insufficient under more extreme working conditions and should be adjusted accordingly to ensure firefighter safety. Full article

Workers in dry-cleaning and laundry shops routinely handle large volumes of synthetic garments that shed airborne microplastics, potentially creating an underrecognized occupational exposure in this small-business sector. Despite growing concern about microplastics in environmental health research, little is known about their recognition as an occupational hazard among service-sector workers. This pilot study assessed awareness and knowledge of microplastics among dry-cleaning and laundry workers in Philadelphia and examined their associations with workplace protective practices. We collected information on workplace characteristics, microplastics awareness, knowledge, and personal protective equipment (PPE) use from 34 self-employed workers. Approximately one-third of participants had heard of microplastics, and those who were aware demonstrated higher knowledge scores (median: 71) than those who were unaware (median: 27). However, neither awareness nor knowledge was associated with PPE use. These findings suggest that microplastics remain an overlooked occupational hazard and underscore the need for enhanced occupational health education and worker protection efforts. Full article

Automated vision-based sensing for personal protective equipment (PPE) compliance in high-formwork support system (HFSS) construction environments faces three compounding challenges: extreme within-image scale variation, dense scaffold occlusions, and small safety hook targets prone to missed detection. Existing sensing systems address only binary presence detection and cannot assess whether safety harnesses are anchored in compliance with regulatory requirements. This paper proposes YOLO-ILB, a lightweight task-specific object detector built on YOLO11n with three targeted improvements. The C3k2_IDWC module replaces standard convolutions with multi-branch Inception depthwise convolutions, improving multi-scale feature discrimination at reduced computational cost. The SPPF_LSKA module embeds large separable kernel attention into the SPPF aggregation path, strengthening global context awareness to suppress scaffold background interference. A BiFPN neck replaces the original PAN structure, enabling bidirectional cross-scale weighted feature fusion to balance detection of small hooks and large harnesses within a sin gle image. A UAV-based sensing dataset was constructed using a DJI Mini 3 Pro (4032 × 3024 px) across 17 real construction sites under varied altitudes, viewing angles, and illumination conditions, yielding 2700 annotated images across five object categories. YOLO-ILB achieves mAP50 = 0.939 with only 1.923 M parameters and 5.7 G FLOPs at 262.3 FPS, outperforming eight mainstream YOLO baselines while remaining deployable on resource-constrained edge computing nodes. A geometry-based compliance algorithm further classifies three harness anchoring states—correct high anchoring, incorrect low anchoring, and unclipped or excessively distant hook—without additional sensors or annotations, achieving 90.82% overall accuracy on 305 field instances and extending the sensing system from presence detection to regulatory compliance assessment. Full article

Personal Protective Equipment (PPE) compliance is critical in powerline and renewable energy construction projects, yet non-adherence remains common and difficult to monitor manually. This paper presents an automated PPE detection system using an Artificial Intelligence based object detection model applied to actual site overhead drone imagery. The aim was to identify key non-compliance categories such as the non-use of hardhats, reflective vests, long pants, T-shirts and long sleeve shirts. A custom dataset was developed from aerial and ground footage and enhanced through standard annotation and augmentation techniques. Model performance was evaluated using mAP, precision, recall, and confidence-based metrics, demonstrating reliable detection across most PPE classes despite environmental and distance-related challenges. The study shows the potential of AI-assisted, drone-based monitoring to enhance safety oversight on powerline and renewable energy construction sites. It further outlines future work to improve dataset diversity, resolution, and real-time deployment. Full article

Adverse imaging conditions such as fog, rain, and low light degrade the reliability of vision-based Personal Protective Equipment (PPE) detection systems on construction sites, yet most existing models are trained under clear-weather assumptions. This paper introduces a physics-based weather augmentation framework integrated with the YOLOv8n architecture to improve PPE detection robustness under adverse environmental conditions. The original Color Helmet and Vest (CHV) dataset was expanded from 1330 clear-weather images to 6650 images across five conditions using four physically grounded augmentation models: the Koschmieder atmospheric scattering model for fog, the Garg–Nayar streak model for rain, gamma-corrected attenuation with Poisson–Gaussian noise for low light, and a PSF-based glare model for bright sunlight. The weather-resistant model, a clear-weather baseline, and an augmented baseline were evaluated on the same 665-image weather-augmented test set. The weather-resistant model achieves 89.2% mAP50, a 5.7 percentage-point improvement over the clear-weather baseline (83.5%), with a nearly four-fold improvement in cross-condition stability (standard deviation 1.5% vs. 5.7%). Under matched training-data volume, the weather-resistant model still outperforms a conventionally augmented baseline across all five simulated conditions, indicating that these gains stem from physics-based modeling rather than larger training-data volume. The largest gain occurs under low light, where mAP50 improves from 73.4% to 87.9%. Gradient-weighted Class Activation Mapping (Grad-CAM) analysis confirms that the weather-resistant model directs more attention toward PPE regions across all conditions, with the largest improvement under low light (+10.0 percentage points). The lightweight design (3.0 M parameters) and quantitative and qualitative validation on 205 annotated real-world construction site images under normal and low-light conditions provide preliminary evidence of practical applicability. Full article

This study investigates the impact of different types of personal protective equipment (PPE), specifically Powered Air-Purifying Respirators (PAPRs) and traditional N95 masks with face shields, on the physiological stress responses of healthcare workers (HWs) during the COVID-19 pandemic. Utilizing an interventional randomized crossover trial design, the research encompasses a simulation phase with ten participants followed by field testing involving thirty frontline healthcare professionals in a tertiary-care hospital setting. Heart rate (HR) and movement data were collected through smartwatches, while trained observers recorded the duration and nature of various activities undertaken during simulations. Data analysis employed statistical techniques, including Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE), to explore potential correlations between PPE type, HR, and movement. Clustering validation measures such as the Calinski–Harabasz, Davies–Bouldin, and Silhouette scores were applied to evaluate the difference between each type of PPE. The results indicated no significant differentiation in HR responses between the two PPE types. However, because HR may lack the sensitivity to fully capture variations in cognitive load or stress, these findings should be interpreted as an exploratory baseline. Additionally, no clear distinctions were observed regarding individual user responses or the activities performed, even when considering movement data. Although the findings imply non-inferiority of the examined PPE, future research including heart rate variability as a more comprehensive indicator of stress would be informative. This research contributes valuable insights into PPE selection and its implications for healthcare worker performance and well-being in high-stress environments, ultimately aiming to inform guidelines and training programs to enhance healthcare delivery during infectious disease outbreaks. Full article

Background/Objectives: Healthcare workers (HCWs) face occupational hazards that increase their risk of Coronavirus Disease of 2019 (COVID-19). This study aims to evaluate HCWs’ perceptions of the effectiveness of Personal Protective Equipment (PPE) in preventing COVID-19 infection and to identify risk factors associated with HCW infection. Methods: A cross-sectional study design was used, with a structured, self-administered, closed-ended questionnaire to collect retrospective data for the period 2020 to 2022 at a tertiary hospital in Johannesburg, South Africa. Results: PPE was effective in reducing COVID-19 infection, according to 230 (57.07%) participants, while 173 (42.93%) disagreed. A significant association (p = 0.034) with a small effect size (Cramer’s V = 0.161) was found between the number of HCWs infected with COVID-19 and their perceptions of PPE’s effectiveness. White HCWs were more likely to perceive PPE as effective than Black HCWs (AOR = 3.82, p = 0.046). Support and clerical staff reported higher perceived effectiveness of PPE (AOR = 2.98, p = 0.040). Conclusions: HCWs encountered COVID-19 infections and various challenges that necessitate interventions and policies to safeguard them in hospital settings and ensure prompt virus management, including ensuring sufficient PPE supplies. The perceptions of PPE effectiveness among HCWs are shaped by an interplay of institutional practices, personal beliefs, and structural factors. These perceptions are closely tied to essential elements such as training, reliable PPE availability, and regular hand hygiene practices, underscoring the need to address both systemic and behavioral dimensions. Full article

Vision-based monitoring of personal protective equipment (PPE) is central to construction safety, yet robust detectors remain limited by scarce, privacy-constrained site imagery. Digital twin simulation can generate labeled synthetic data at scale, but Sim-to-Real gaps make the effective use of synthetic data under a fixed training budget unclear. We benchmark YOLOv11s, Faster R-CNN, and RT-DETR-L using a controlled real–synthetic mixing protocol comprising a fixed real-only test set (400 images), separate sampling pools (5760 real and 4000 synthetic images), and eleven training configurations of approximately constant size (∼1450 images before the validation split) with real fractions ranging from 0% to 100%. Using average recall (AR@100) as the primary safety-oriented metric, the original single-run benchmark shows non-linear architecture-dependent responses to data mixing: YOLOv11s and RT-DETR-L achieve their single-run peaks at G9 (90% real/10% synthetic), whereas Faster R-CNN performs best at G10 (100% real). To assess robustness for the most central YOLOv11s comparison, we further conduct a targeted supplementary repeated-seed analysis for G9 and G10 and re-evaluate all resulting checkpoints on the same fixed real-only test set. This supplementary analysis shows that G10 achieves higher mean performance and lower variance than G9 for YOLOv11s, indicating that the apparent single-run advantage of limited synthetic supplementation is not stable across reruns. However, this robustness check is limited to the central YOLOv11s G9-versus-G10 case and should not be interpreted as a comprehensive robustness validation across all configurations and detector families. Persistent errors on safety vests further indicate a materiality gap for deformable PPE. Overall, these findings suggest that synthetic supplementation can be useful in some settings, but its value is architecture-dependent, evaluation setting-sensitive, and should be interpreted cautiously under robustness-oriented evaluation. Full article

This study aims to identify key health and safety challenges and examine root causes while developing a conceptual framework to improve safety. Results of the study will be useful for policy makers, regulatory authorities, construction managers, safety professionals and researchers to improve regulations, safety practices, training programs and policy development. The emerging construction industry in Sri Lanka is facing significant safety challenges for workers, including poor practices, inappropriate conduct, and negative attitudes. The construction industry was selected for this study due to its labor-intensive nature and its consistently high exposure to occupational hazards compared to other industrial sectors. The underlying root causes of these health and safety challenges remain unclear, primarily due to a lack of comprehensive government regulations, which are currently limited to the outdated Factories Ordinance of 1942. Sri Lanka was chosen as the focus of this study because of its rapidly expanding construction sector and outdated regulatory framework; it is also a representative of underdeveloped countries. Several studies have identified contributing factors such as outdated legislation, a shortage of qualified officers, poor attitudes, lack of funding, negligence, and limited awareness. To address this research gap, the safety aspects of the Sri Lankan construction industry have been examined, revealing emerging challenges such as poor safety practices, the presence of foreign workers, and the inadequate use of personal protective equipment (PPE) by staff. A deeper examination of these challenges indicates that sufficient safety budgets reflect leadership attitudes toward preventing injuries, and that targeted safety training for different roles can help mitigate these issues. Accordingly, a conceptual safety framework has been developed. A qualitative, semi-structured interview comprising both open- and closed-ended questions was conducted to gain insights from 26 experts (including engineers, architects, human resource personnel, safety officers, and managers) regarding workplace safety challenges. The interview data was thematically categorized based on the identified safety challenges using NVivo analysis, to determine their root causes and develop strategies to improve workplace safety. To evaluate the emotional tone of participants’ response, sentiment analysis was conducted. Results highlighted participants’ optimism when discussing proactive or successful safety measures, neutrality in objective assessments, and concern or dissatisfaction when addressing safety challenges and organizational shortcomings. Experts recommended that safety education should be introduced in universities and vocational institutes. Firms can incorporate safety training through toolbox talks and induction sessions, and they can allocate a safety budget in their contracts. The study suggests developing a certificate-level safety training module for the construction industry and provides fresh insights into the underlying causes of safety issues in the Sri Lankan construction sector. Furthermore, the study has implications for delivering a health and safety framework for project risk management in developing countries that face budget constraints and limited training and development opportunities for enhancing construction skill sets. Full article

Industrial sites pose numerous hazards where unexpected accidents can occur at any time, and personal protective equipment (PPE) is a primary safeguard for worker safety. In this study, PPE specifically refers to safety helmets, safety shoes, and safety gloves. Manual verification of PPE usage is infeasible in environments with many workers, motivating automated detection. This study proposes a method that integrates the Convolutional Block Attention Module (CBAM) exclusively into the training-only auxiliary reversible branch of YOLOv9’s Programmable Gradient Information (PGI) architecture. The proposed CBAMLinear module enhances gradient information during training while introducing zero additional computational overhead at inference, as the entire auxiliary branch is removed. The proposed YOLOv9 with CBAMLinear achieved consistent mAP@0.5:0.95 gains of 0.005–0.007 over the baseline for the three larger model variants, while maintaining identical inference-time parameters and FLOPs. In industrial safety, even modest performance gains can directly contribute to accident prevention by reducing false positives and false negatives, making this approach well suited for real-time safety management systems in industrial settings. Full article

Background: The use of personal protective equipment (PPE) is essential to ensure infection prevention, healthcare worker safety, and reduce healthcare-associated infections in clinical settings. Innovative training approaches, such as virtual reality (VR), may enhance competency and clinical preparedness compared with traditional video-based instruction, supporting safer patient care practices. Methods: Participants were 84 students, with 42 participants in each group. The study was conducted at a public university in Saudi Arabia. The video-based group viewed a standardized educational video on PPE procedures, whereas the VR group engaged in a 13-min immersive 360° training module. Both groups completed pre- and post-intervention assessments to evaluate PPE competency. Primary outcomes included the PPE Knowledge Questionnaire and the Satisfaction and Self-Confidence in Learning Scale scores. Statistical analyses were conducted using SPSS. Results: Both instructional approaches significantly improved PPE-related competency, supporting infection prevention in clinical settings. The VR group demonstrated slightly higher post-intervention scores than the video-based group (p < 0.001). The magnitude of this difference was large (Cohen’s d ≈ 0.87; partial η² = 0.163), indicating a practical advantage of VR-based instruction over video-based learning. High satisfaction and self-confidence were reported among VR participants, indicating positive perceptions of clinical preparedness, although these were not significantly associated with competency gains. Conclusions: Both VR- and video-based training significantly enhanced PPE competency, supporting improved infection prevention practices. VR demonstrated a marginal advantage and was associated with high levels of satisfaction and confidence, highlighting its value as an effective training approach to strengthen healthcare workforce preparedness and patient safety. Full article