Search Results (3,210)

Mining activities are characterised by a multiplicity of inherent occupational hazards. Exposure to mineral dust such as silica, asbestos, and coal dust is common in mining, leading to pneumoconiosis. Exposure to respirable silica-containing dust is one of the common respiratory hazards associated with adverse health effects such as silicosis, lung cancer, renal failure, scleroderma, systemic lupus erythematosus (SLE) and chronic obstructive pulmonary disease (COPD), to mention but just a few. In southern Africa, there is a rising epidemic of silicosis, human immunodeficiency virus (HIV) and tuberculosis (TB). Excessive exposure to silica-containing dust exacerbates the TB and silicosis epidemic in mining areas. There is poor control of dust exposure and a lack of occupational hygiene assessments of silica dust in mining in southern Africa. In southern Africa, there remains a persistent knowledge gap regarding the extent of occupational exposures to respirable chemical substances, such as silica dust. Consequently, occupational hygiene air monitoring was conducted in mining companies across four low-income Southern Africa Development Community (SADC) countries, Lesotho, Mozambique, Malawi and Zambia, to provide a baseline exposure dataset. The hazardous nature of work associated with mining activities still persists in these low-income countries, with 53% (n = 72) of quarries and 20% (n = 19) of coal mines having respirable quartz exposures exceeding the reference occupational exposure limit (OEL) of 0.1 milligrams per cubic meter (mg/m³). The highest exposure ranges for quartz were recorded in surface aggregate quarries, with the maximum concentration recorded at 2.739 mg/m³. The highest number of air samples (93%, n = 111), which were in compliance with the OEL of 3 mg/m³ for respirable dust, were recorded in the copper, diamond, ruby, cement quarry and gold mines. This exploratory study confirms the variable extent of mineworker exposure to respirable dust and corresponding quartz fractions emanating from different mining activities. The collected exposure data provides a baseline overview of exposures within the mining industry in the SADC region. It also serves as a vital input for future regional exposure surveillance databases, as well as preliminary data for directing future research towards regional exposure prevention initiatives. Full article

Background and Objectives: Romania reported the highest measles incidence in the European Union during the 2023–2024 epidemic, largely driven by declining vaccination coverage. We aimed to characterize the epidemiological, clinical, and laboratory profile of hospitalized measles patients and to identify age-related differences, with particular emphasis on systemic and hepatic involvement. Materials and Methods: We conducted a retrospective observational study including 360 consecutive patients with laboratory-confirmed measles admitted to a tertiary infectious disease hospital in northeastern Romania between 1 January and 31 December 2024. Demographic, clinical, laboratory, therapeutic, and outcome data were collected. Pediatric (<15 years) and adult patients were compared using appropriate statistical tests. Results: Children accounted for 71.4% of cases, including 16.1% infants under one year. Over 90% of patients were unvaccinated or incompletely vaccinated. Household transmission represented the most frequent identifiable source. Adults presented significantly higher inflammatory markers and more pronounced hepatic involvement than children. ALT elevation occurred in 63.1% of adults versus 34.2% of children (p < 0.001), with moderate-to-severe cytolysis predominantly observed in adults (34.9% vs. 1.9%, p < 0.001). Pulmonary complications were documented in 28% of cases, mainly viral interstitial pneumonia. Thrombocytopenia was significantly more frequent in adults (p < 0.001). Overall mortality was 0.27%, occurring in an unvaccinated infant with secondary bacterial pneumonia. Conclusions: The 2024 measles epidemic in our area was characterized by sustained transmission among unvaccinated individuals and frequent systemic involvement. Hepatic dysfunction emerged as a prominent feature in adults, suggesting a shifting clinical phenotype in contemporary outbreaks. Strengthening vaccination coverage and early recognition of systemic complications remain critical to reducing measles-related morbidity and mortality. Full article

Background: Influenza A(H3N2) viruses remain a major public health concern due to their rapid antigenic evolution and association with severe disease, particularly among high-risk populations. During the 2025–2026 influenza season, a marked epidemiological shift was observed in Europe, with the emergence and predominance of the A(H3N2) subclade K (J.2.4.1). Objectives: This narrative review aims to provide an integrated overview of the epidemiology, evolutionary dynamics, and public health implications of subclade K, with a particular focus on its impact on vaccine effectiveness, in comparison with the 2024–2025 influenza season. Methods: A non-systematic literature review was conducted using major scientific databases and official public health sources, including WHO and ECDC reports. Recent surveillance data, genomic analyses, and epidemiological updates were included. Given the rapidly evolving evidence base, selected preprint studies were also considered and interpreted with caution. Results: The 2025–2026 influenza season in Europe was characterized by a relative genetic convergence, with subclade K accounting for the majority of A(H3N2) sequences. This variant demonstrated a clear selective advantage and was associated with an earlier and more intense epidemic peak. Molecular analyses indicate the accumulation of multiple mutations in the hemagglutinin protein, particularly within key antigenic sites, contributing to immune escape. These evolutionary changes have important implications for vaccine effectiveness, with current estimates suggesting moderate protection against infection but preserved effectiveness against severe outcomes. Antigenic mismatch, manufacturing constraints, and host-related factors further contribute to reduced vaccine performance. Conclusions: The emergence and rapid spread of subclade K highlight the dynamic nature of influenza virus evolution and its impact on public health. Continuous genomic surveillance and timely vaccine updates remain essential. Despite suboptimal effectiveness against infection, influenza vaccination continues to provide significant protection against severe disease and should remain a cornerstone of prevention strategies. Full article

This study models trachoma transmission in Cameroon using a deterministic approach with integer and fractional-order derivatives, incorporating direct, fly-mediated, and environmental transmission routes. Fitting disease data from 1990–2019, the model forecasts trachoma prevalence until 2035. The research confirms the solution existence and uniqueness, calculates the basic reproduction number ${\mathcal{R}}_0^{\lambda }$ where $\lambda \in (0,1]$ represents the fractional-order parameter, and analyzes equilibrium stability. A stable trachoma-free equilibrium exists when ${\mathcal{R}}_0^{\lambda }<1$, while an endemic equilibrium is proven stable for ${\mathcal{R}}_0^{\lambda }>1$ under specific conditions. Calibration of a fractional model with Cameroon data yielded an ${\mathcal{R}}_0$ of 1.169 (indicating endemicity) and identified an optimal fractional order of $\lambda =0.98$. By calculating the strength number, we found that another epidemic wave could occur in 50 years. Global sensitivity analysis highlighted key parameters affecting trachoma dynamics. A numerical scheme of the model based on the Adams–Bashforth–Moulton method is constructed and its stability demonstrated. It is then used to perform several numerical simulations, first to validate the theoretical results obtained, and then to compare the different models (statistical and deterministic). The conclusion is reached that the disease will persist in the population (${\mathcal{R}}_0>1$), although the statistical model shows that it could disappear by 2030. This proves that, for trachoma dynamics in Cameroon, it is advisable to use a deterministic model. Full article

Bluetongue (BT) is an infectious, non-contagious, arthropod-borne viral disease of ruminants, and has a severe impact on livestock. It is caused by Bluetongue virus (BTV), a double-stranded (ds) RNA virus with a segmented genome (10 segments), belonging to the Seoreoviridae family, Orbivirus genus. Over the last 25 years, Europe has suffered multiple incursions of different BTV serotypes with serious consequences, which have mainly been controlled thanks to vaccination. In the case of Spain, from 2000 to 2023, BTV serotypes 1, 2, 4 and 8 have caused epidemics, and, sporadically, BTV-1 and -4 were detected in the same area and period. In 2024, BTV serotypes 1, 3 and 8 circulated simultaneously in the southwest of the country, causing a severe clinical impact in sheep but also in cattle and a multitude of outbreaks. Additionally, despite vaccination, serotype 4 also circulated that year, especially in areas where the other serotypes were already circulating. Whole-genome sequencing and phylogenetic analyses allowed us to confirm that serotypes 1 and 4 were homologous to viruses circulating in the country since 2000s, while serotypes 3 and 8 were homologous to BTVs recently notified in neighboring countries. In this context, many BTV co-infections of two or more different serotypes were confirmed by serotype-specific RT-PCRs, both in farms and individual animals. An epidemic caused by four serotypes coinciding in space and time had never occurred before in Spain, being a challenge for the diagnosis and control of this disease. Moreover, it could have favored the appearance of reassortant viruses with an unknown virulence, posing an additional risk. The data presented here raise the question of whether the co-circulation of different BTV strains, an exceptional situation, could become the new normal in certain areas of Europe. Full article

Pine wilt disease (PWD) is a devastating biological forest disturbance, making its large-scale and high-precision remote sensing monitoring crucial for epidemic prevention and control. However, the performance of existing deep learning methods in high-resolution imagery is often limited by the confusion of spectral features among disparate ground objects and the complexity of forest boundaries. To address these challenges, this study proposes an innovative, end-to-end deep learning architecture termed MBA-Former. Built upon the robust Swin Transformer V2 backbone, the model systematically integrates two highly adaptable functional modules: (1) a front-end intelligent fusion module designed to adaptively fuse heterogeneous features, and (2) a back-end boundary refinement module that refines segmentation contours via dual-task learning. To train and evaluate the model, fine-grained manual annotations were first performed on Gaofen-2 satellite imagery acquired from multiple typical epidemic areas across northern and southern China. Information-enhanced datasets were constructed by fusing the original spectral bands, typical vegetation indices, and texture features. A comprehensive performance evaluation was then conducted, specifically targeting typical challenging scenarios characterized by complex ground object boundaries. The experimental results demonstrate that the Multi-modal Boundary-Aware Transformer (MBA-Former) significantly outperforms current state-of-the-art models. It achieved a mean Intersection over Union (mIoU) of 81.74%, an IoU of 77.58% for the most critical infected tree category, and a Boundary F1-Score of 78.62%. Compared to the best-performing baseline model, Swin-Unet, these three metrics exhibited notable improvements of 2.88%, 3.55%, and 4.46%, respectively. These findings convincingly demonstrate that MBA-Former provides a highly accurate and robust solution for the large-scale, automated remote sensing monitoring of forest diseases, offering immense value in preventing significant economic losses and preserving forest ecosystem integrity. Full article

Background: The complex interplay between treatment interventions and asymptomatic carriers and its effect on the epidemic duration of an infectious disease is not fully understood. Methods: Here, we used Galton-Watson branching process and generating function technique to estimate the density functions of minor outbreak duration. Simulations were used to calculate the central tendency of outbreak duration and address how changing levels of treatment failure affect this estimated duration. Results:Streptococcus pyogenes infection was used as a case study. Given the existence of the threshold, the change in mean duration as the probability of treatment failure increases is shown to be similar to the pattern driven by the basic reproduction number. In a supercritical regime, the mean duration tends to decrease as the probability of treatment failure increases. The distribution changes in tail behavior, from heavy- to light-tailed, if a large fraction of long extinction times develops to a major outbreak. Conclusions: Treatment failure elevates the probability of secondary transmissions by prolonging the overall infectious period, resulting in an extended the outbreak duration. The threshold of treatment failure identifies the maximum tolerable error for medical intervention. An unusually long period implies a critical early warning signal of a potential major outbreak that was successfully contained. Full article

Marek’s disease (MD), caused by pathogenic Marek’s disease virus serotype 1 (MDV-1), is one of the most important avian immunosuppressive and neoplastic diseases and has led to huge economic losses to the poultry industry worldwide. Rapid and accurate clinical diagnosis is of great significance for efficient control of the disease. Herein, we have established a multiplex PCR (mPCR) method to simply differentiate all of the three types of MDV, using five specific primers targeting to MDV-1 oncogene meq or MDV-2 and MDV-3/HVT gB genes. Simultaneously, it can detect any type of virulent or vaccine MDV strains in one PCR reaction, with amplicons of the short (S) and long (L)-meq of MDV-1 strains, and the gB of MDV-2 and HVT vaccine strains. Non-specific amplifications of avian leukosis virus (ALV), reticuloendotheliosis virus (REV), or fowl adenovirus virus 4 (FAdV-4) were not observed, indicating a good specificity of this method. A total of 522 clinical samples of tumor-bearing or suspected diseased birds collected from 30 poultry farms were detected. The results demonstrated that the newly developed mPCR method accurately detected and differentiated epidemic MDV-1 infections and vaccine strains, and provided nearly 100% consistency for detecting clinical wild-type infections compared with conventional PCR amplification of the meq gene. Collectively, our data has provided a highly efficient method for early differential diagnosis of MD clinical cases, virus identification and future evaluation of vaccination efficacy in healthy chicken flocks, which would be meaningful for efficient control of the disease. Full article

Background and Objectives: Diabetes is one of the most common chronic non-communicable diseases and represents a major public health problem. At the global level, the epidemic character of diabetes mellitus can be attributed to an extended life expectancy but also to lifestyle. The aim of this study was to examine the sociodemographic, health, and lifestyle characteristics of adults with type 2 diabetes mellitus in Serbia. Materials and Methods: The research is part of the Serbian Population Health Survey conducted in the period from October to December 2019 by the Republic Statistical Office, in cooperation with the Institute of Public Health of Serbia “Dr Milan Jovanović Batut” and the Ministry of Health of the Republic of Serbia. The research instrument was standardized questionnaires constructed in accordance with the European Health Interview Survey (EHIS—European Health Interview Survey, wave 3) questionnaire, which were adapted to the specifics of our area. The research was conducted as a cross-sectional study on a representative sample of the adult population of Serbia. Results: Among 1138 adults with type 2 diabetes in Serbia (52.8% female; mean age 66.0 ± 11.9 years), overweight and obesity were highly prevalent (40.1% and 34.4%, respectively), with Obesity I predominating. Significant gender differences were observed: female more often reported obesity, multimorbidity, and depressive symptoms, whereas men were more physically active and more frequently overweight. Most participants were physically inactive, consumed breakfast and bread daily, and had low engagement in cycling and sports. Alcohol consumption was significantly higher in men, while dietary habits differed by gender for bread intake. These findings highlight substantial gender- and lifestyle-related disparities among adults with type 2 diabetes in Serbia. Conclusions: Targeted interventions promoting healthy lifestyle, physical activity, psychosocial support, and chronic disease management are urgently needed to address gender- and lifestyle-related disparities in adults with type 2 diabetes in Serbia. Full article

Infections caused by arboviruses, a diverse group of viral pathogens transmitted by biting arthropod vectors, mainly mosquitoes, ticks, and midges, can cause a range of illnesses in humans, from mild, influenza-like symptoms to severe neurological complications including encephalitis and viral hemorrhagic fever. According to 2024 World Health Organization statistics, vector-borne diseases collectively account for over 700,000 human deaths annually, with mosquito-borne infections such as dengue, chikungunya, Zika, and yellow fever constituting a growing and significant proportion of this burden. What was once considered a problem localized to poorly resourced settings in tropical and subtropical regions is now becoming a pervasive global challenge. This is due largely to a combination of factors including climate change, transcontinental travel, and urbanization, with the geographical spread and intensity of arboviral outbreaks reaching unprecedented levels during the current century. In much the same way that the escalating global burden of bacterial infections resistant to antibiotics has been described as a silent pandemic, the insidious rise of arboviruses begs questions regarding outbreak preparedness, prevention and control. Here, we highlight the pressing need for comprehensive strategies that incorporate various health sectors to mitigate the emergence and resurgence of arboviral diseases. Future directives that should be prioritized are outlined. As demonstrated by epidemiological trends and historical outbreak data, an orchestrated global response is critical not only for managing current threats but also for preventing future epidemics. Full article

Background: The resurgence of Mpox (formerly known as monkeypox) since the 2022 global outbreak has exposed weaknesses in surveillance, diagnosis, and public risk communication systems. Despite increased clinical understanding, limitations in knowledge, attitudes, and practices (KAP) among both healthcare workers (HCWs) and the general population continue to challenge prevention and control measures. Numerous systematic reviews have been published on KAP toward Mpox, yet their findings remain fragmented. This review aimed to consolidate the existing evidence from published systematic reviews to provide a unified understanding of global KAP levels related to Mpox. Methods: We followed the PRISMA guidelines for this systematic review of systematic reviews. The article search was conducted in PubMed, Embase, and the Cochrane Library for systematic reviews published between January 2010 and October 2025. Data was extracted on study design, population, and reported quantitative outcomes. Results: Five studies met the inclusion criteria: three focused on HCWs, while two focused on the general population. Among HCWs, knowledge ranged from 26.0% to 46.7%, and attitudes from 28.2% to 62.2%. In the general population, knowledge ranged from 33.0% to 46.6%, attitudes from 40.0% to 71.9%, and perceptions averaged around 40.0%. Across both groups, Mpox knowledge was limited, attitudes were moderately positive, and preventive behaviors remained consistently low, revealing a persistent gap between awareness and practice. Conclusions: This review highlights persistent gaps in knowledge, attitudes, and practices among HCWs and the general population. Although global attention increased substantially following the 2022 outbreak, important weaknesses remain in translating knowledge into consistent preventive behaviors. Addressing these gaps requires structured and context-specific interventions. Integrating Mpox-focused modules into mandatory Continuing Medical Education credits for HCWs could ensure sustained competency in diagnosis, infection prevention, and outbreak response beyond peak epidemic periods. For the general population, strategic risk communication campaigns should leverage trusted community leaders and social media influencers in high-risk regions to counter misinformation, reduce stigma, and promote evidence-based preventive behaviors. Embedding these targeted strategies within broader pandemic preparedness and global health security frameworks will be essential to strengthening early detection, public trust, and coordinated outbreak response in future Mpox or other emerging infectious disease events. Full article

Measles remains a significant public health threat despite widespread vaccination, with recent resurgences driven by vaccine hesitancy and coverage gaps. Existing mathematical models often fail to capture the substantial temporal heterogeneity in incubation periods, vaccine-induced protection, and recovery processes that characterize measles transmission. We develop and analyze an SVEIR epidemic model incorporating four independent distributed time delays with exponential survival factors, capturing the realistic variability in these epidemiological processes. The model features compartment-specific mortality rates, disease-induced mortality, and imperfect vaccination with failure probability $\theta$. Using next-generation matrix methods adapted for delay kernels, we derive the delay-dependent reproduction number ${\mathcal{R}}_0^d$ and prove, via systematic construction of Volterra-type Lyapunov functionals, that it constitutes a sharp threshold: the disease-free equilibrium is globally asymptotically stable when ${\mathcal{R}}_0^d\le 1$, while a unique endemic equilibrium emerges and is globally stable when ${\mathcal{R}}_0^d>1$. Normalized forward sensitivity analysis reveals that the transmission rate $\beta$ and recruitment rate $\Lambda$ exhibit maximal positive elasticity, while the vaccination rate p, vaccine failure probability $\theta$, and incubation delay ${\tau }_3$ possess the largest negative elasticities. Critically, ${\tau }_3$ exerts exponential influence via $e^{-n_3{\tau }_3}$, making interventions that delay infectiousness—such as post-exposure prophylaxis—unusually potent. We derive an explicit expression for the critical delay ${\tau }_3^{\mathrm{cr}}$ at which ${\mathcal{R}}_0^d=1$, demonstrating that prolonging the effective incubation period sufficiently can shift the system from endemic persistence to extinction. Numerical simulations using Dirac delta kernels confirm all theoretical predictions. These findings provide three actionable insights for public health: (1) maintaining high vaccination coverage among new birth cohorts remains paramount; (2) improving vaccine quality (reducing $\theta$) yields substantial returns; and (3) the incubation delay represents a quantifiable, measurable target for evaluating the population-level impact of time-sensitive interventions. The framework is broadly applicable to infectious diseases characterized by significant temporal heterogeneity. Full article

Whooping cough has re-emerged as a significant global public health concern. Hence, an SEIRS model for whooping cough transmission in Japan is proposed to capture the disease dynamics because of a strong resurgence of the epidemic. The model is analyzed mathematically, establishing the non-negativity and boundedness of its solutions and investigating both the disease-free and endemic equilibria with their local and global stability. The model is fitted to actual infection data by estimating the time-varying transmission rates using a Long Short-Term Memory (LSTM) network and calibrating vaccination and treatment rates via Latin Hypercube Sampling (LHS). Sensitivity analysis identifies the key parameters for optimal control, and results indicate that simultaneously enhancing the vaccination rate most effectively mitigates the epidemic, as supported by cost-effectiveness analysis. Full article

Dengue fever (DF) is an acute mosquito-borne infectious disease caused by dengue virus (DENV), primarily transmitted by Aedes aegypti and Aedes albopictus. Nearly 4 billion people worldwide are at risk of infection, and the 2024 epidemic reached an unprecedented scale. Severe cases can lead to hemorrhage, shock, and even death, prompting the WHO to classify it as a potential pandemic pathogen. Current prevention and control measures face prominent bottlenecks, including limited applicable populations for vaccines, lack of specific antiviral drugs, and increasing insecticide resistance in mosquito vectors. Notably, susceptible animal models serve as core tools for elucidating the pathogenic mechanisms of dengue virus, screening antiviral drugs, and evaluating vaccine protective efficacy, holding irreplaceable significance. This review systematically summarizes the characteristics, application scenarios, and research progress of mainstream and potential susceptible animal models, including non-human primates, mice, pigs, tree shrews, and bats. It covers model systems with different immune statuses, genetically modified types, and species-specific traits. Among these, mouse models are the most widely used due to their high flexibility and controllable cost, while non-human primate models have become key carriers for preclinical vaccine evaluation by virtue of their high homology with human immune responses. However, current models generally suffer from core bottlenecks, such as incomplete simulation of core severe phenotypes, insufficient restoration of immune mechanisms, unclear viral receptor mechanisms, and lack of unified standards for inoculation doses and evaluation indicators. These limitations make it difficult to accurately replicate key severe disease mechanisms, including antibody-dependent enhancement (ADE) and cytokine storms. Future model development should focus on core requirements—including intact immunity, broad-spectrum susceptibility, and accurate simulation of clinical pathological features—prioritize solving the simulation challenges of ADE and cytokine storms, and establish standardized experimental systems and evaluation criteria. By comprehensively summarizing the advantages and limitations of the existing models, this review provides a systematic reference for the optimization and upgrading of dengue virus-susceptible animal models. It also holds important guiding significance for promoting the in-depth development of basic dengue research, innovation in prevention and control technologies, and clinical transformation and application. Full article

Health emergencies linked to epidemic outbreaks in vulnerable contexts require rapid and effective architectural responses. Natural ventilation represents a key strategy for infection control and indoor comfort, yet traditional airflow calculation methods require climatic and construction data, which are often unavailable or incomplete. In emergency situations, this results in the inapplicability of such methods and creates a critical information gap. This study proposes a simplified equation to estimate airflow rate (Q) in single-sided and cross-ventilation configurations, based on openable surface area and a reference Effective Window Air Speed (EWAS). Two infectious disease treatment centers were modeled and simulated using EnergyPlus (E+) under five climatic scenarios—two real and three hypothetical—characterized by low, medium, and high wind exposure. Simulation results were compared with existing formulas and with the proposed simplified equation. Although the simplified model introduces a margin of error compared with dynamic simulations, it provides meaningful estimates, with mean deviations typically in the 20–35% range, lower in single-sided conditions and higher for cross-ventilation under medium-to-high wind exposure. The study demonstrates that an ultra-simplified approach can serve as a support tool for the design of temporary healthcare facilities in resource-limited contexts, where rapidity and data accessibility are essential. Full article