Search Results (2,783)

Limited molecular data exist on zoonotic parasites Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi in Angus calves from Guizhou, China. This study constitutes the first molecular epidemiological survey of these pathogens in this region. 817 fecal samples from Angus calves across 7 intensive beef farms (Bijie City). Nested PCR methods targeting SSU rRNA (Cryptosporidium spp.), gp60 (Cryptosporidium bovis subtyping), bg/gdh/tpi (G. duodenalis), and ITS (E. bieneusi) coupled with DNA sequencing were employed. DNA sequences were analyzed against the NCBI. database. Statistical differences were assessed via a generalized linear mixed-effects model. Cryptosporidium spp. prevalence 23.5% (192/817; 95% CI 28.1–34.6%), with C. bovis predominating 89.6% (172/192; 95% CI 84.4–93.5%) and six subtypes (XXVIa-XXVIf). Highest infection in 4–8-week-olds 29.9% (143/479; 95% CI 25.8–34.1%) (p < 0.01). G. duodenalis: 31.3% (256/817; 95% CI 28.1–34.6%) positive, overwhelmingly assemblage E 97.6% (6/256; 95% CI 0.9–5.0%), zoonotic assemblage A was marginal 0.7% (6/817; 95% CI 0.3–1.6%). Farm-level variation exceeded 10-fold (e.g., Gantang: 55.0% (55/100; 95% CI 44.7–65.0%) vs. Tieshi: 4.9% (5/102; 95% CI 1.6–11.1%). E. bieneusi: prevalence 19.7% (161/817; 95% CI 17.0–22.6%), exclusively zoonotic genotypes BEB4: 49.7% (80/161; 95% CI 41.7–57.7%); I: 40.4% (65/161; 95% CI 32.7–48.4%). Strong diarrhea association (p < 0.01) and site-specific patterns (e.g., Guanyindong: 39.2%). While Giardia exhibited the highest prevalence (31.3%) with minimal zoonotic risk, Enterocytozoon—despite lower prevalence (19.7%)—posed the greatest public health threat due to exclusive circulation of human-pathogenic genotypes (BEB4/I) and significant diarrhea association, highlighting divergent control priorities for these enteric parasites in Guizhou calves. Management/Public health impact: Dominant zoonotic E. bieneusi genotypes (BEB4/I) necessitate: 1. Targeted treatment of 4–8-week-old Angus calves. 2. Manure biofermentation (≥55 °C, 3 days), and 3. UV-disinfection (≥1 mJ/cm²) for karst water to disrupt transmission in this high-humidity region. Full article

Background: Epidemiological studies have reported an inverse association between smoking and Parkinson’s disease (PD) risk, prompting interest in nicotine as a potential therapeutic agent. The present meta-analysis evaluated the efficacy of nicotine therapy in improving motor symptoms and activities of daily living in patients with PD. Methods: PubMed, Embase, and Cochrane Library were systematically searched to identify randomized controlled trials (RCTs) assessing nicotine therapy in PD. Clinical RCTs administering interventions extending beyond 1 week and reporting motor or nonmotor outcomes were included. Random-effects models were used to analyze short-term (<6 months) and long-term (≥6 months) outcomes by using standardized mean differences (SMDs). Results: This meta-analysis included five RCTs (346 participants). Nicotine therapy led to no significant improvement in motor outcomes in the short term (pooled SMD: −0.452, 95% confidence interval: −1.612 to 0.708) or long term (pooled SMD: 0.174, 95% confidence interval: −0.438 to 0.787). Considerable interstudy heterogeneity was noted. Furthermore, short-term nicotine therapy resulted in no significant improvement in daily functioning, cognition, or quality of life. Conclusions: This meta-analysis revealed a lack of compelling evidence suggesting that nicotine-based therapies improve motor or nonmotor outcomes in PD. The findings highlight a disconnect between epidemiological associations and clinical efficacy. Given the prodromal nature of PD pathology and the challenges of early diagnosis, future preventive strategies should be implemented before symptom onset in high-risk individuals identified using advanced biomarker panels. Full article

In this paper, the authors introduce the transmuted geometric integer-valued autoregressive model with periodicity, designed specifically to analyze epidemiological and public health time series data. The model uses a transmuted geometric distribution as a marginal distribution of the process. It also captures varying tail behaviors seen in disease case counts and health data. Key statistical properties of the process, such as conditional mean, conditional variance, etc., are derived, along with estimation techniques like conditional least squares and conditional maximum likelihood. The ability to provide k-step-ahead forecasts makes this approach valuable for identifying disease trends and planning interventions. Monte Carlo simulation studies confirm the accuracy and reliability of the estimation methods. The effectiveness of the proposed model is analyzed using three real-world public health datasets: weekly reported cases of Legionnaires’ disease, syphilis, and dengue fever. Full article

Previous studies reported the links between the COVID-19 incidence and weather factors, but few investigated their impact and timing on mortality, at a continental scale. We systematically investigated the temporal relationship of COVID-19 mortality in the European countries in the 1st year of pandemic (March–December 2020) with (i) solar insolation (W/${\mathrm{m}}^2$) at the ground level and (ii) objective sky cloudiness (as decimal cloud fraction), both derived from satellite measurements. We checked the correlations of these factors within a sliding window of two months for the whole period. Linear-mixed effect modeling revealed that overall, for the European countries (adjusted for latitude), COVID-19 mortality was substantially negatively correlated with solar insolation in the previous month (std. beta −0.69). Separately, mortality was significantly correlated with the cloudiness in both the previous month (std. beta +0.14) and the respective month (std. beta +0.32). This time gap of ∼1 month between the COVID-19 mortality and correlated weather factors was previously unreported. The long-term monitoring of these factors might be important for epidemiological policy decisions especially in the initial period of potential future pandemics when effective medical treatment might not yet be available. Full article

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, is increasingly recognized as a systemic condition with cardiovascular implications. Among these, heart failure has emerged as a significant complication. The aim of this narrative review was to explore the cellular and molecular pathways that link IBD and heart failure. Drawing upon findings from epidemiologic studies, experimental models, and clinical research, we examined the pathways through which IBD may promote cardiac dysfunction. Chronic systemic inflammation in IBD, driven by cytokines such as TNF-α and IL-1β, can impair myocardial structure and function. Furthermore, intestinal barrier dysfunction and gut dysbiosis can facilitate the translocation of proinflammatory microbial metabolites, including lipopolysaccharide and phenylacetylglutamine, and deplete cardioprotective metabolites like short-chain fatty acids, thereby exacerbating heart failure risk. Additional contributing factors include endothelial and microvascular dysfunction, autonomic dysregulation, nutritional deficiencies, shared genetic susceptibility, and adverse pharmacologic effects. IBD contributes to heart failure pathogenesis through multifactorial and interrelated mechanisms. Recognizing the role of the gut–heart axis in IBD is crucial for the early identification of cardiovascular risk, providing guidance for integrating care and developing targeted therapies to reduce the risk of heart failure in this vulnerable population. Full article

Background: This study aims to evaluate the cost-effectiveness of providing the 23-valent pneumococcal polysaccharide vaccine (PPV23) free of charge versus self-paying vaccination among adults aged 60 years and older in Nanning, Guangxi, China. Methods: A decision tree–Markov model was developed to compare three strategies (government-funded free vaccination, self-funded vaccination, and no vaccination) over a 5-year time horizon. The model incorporated local epidemiological data and cost parameters, applying a 3% discount rate. Sensitivity analyses were conducted on key parameters, including vaccine effectiveness against pneumonia and pneumonia treatment costs. Results: The benefit–cost ratios for free and self-funded vaccination were 0.075 and 0.015, respectively, both below the cost-effectiveness threshold of 1. However, the free vaccination strategy resulted in a higher net benefit (USD 399,651.32) compared to the self-funded strategy (USD 222,594.14), along with a lower Incremental Cost-Effectiveness Ratio (ICER) (USD 1.47 per USD 0.14 of avoided disease cost). Although both strategies yielded benefit–cost ratios far below the conventional threshold of 1, the free strategy demonstrated relatively greater economic efficiency. Sensitivity analyses confirmed that vaccine effectiveness against pneumonia and treatment costs were key drivers of economic outcomes. Conclusions: While neither vaccination strategy achieved conventional cost-effectiveness benchmarks in this setting, the free PPV23 vaccination program demonstrated relatively greater economic efficiency compared to the self-funded approach; although neither strategy met the conventional cost-effectiveness thresholds, they should be considered for inclusion in regional health policy for older adults. Full article

Objectives: Shoulder injury prevalence appears to be the highest among all injuries in CrossFit (CF) athletes. Nevertheless, there is no evidence deriving from prospective studies to explain this phenomenon. The purpose of this study was to document shoulder injury incidence in CF participants over a 12-month period and prospectively investigate the risk factors associated with their demographic, epidemiological, and functional characteristics. Methods: The sample comprised 109 CF athletes in various levels. Participants’ data were collected during the baseline assessment, using a specially designed questionnaire, as well as active range of motion, muscle strength, muscle endurance, and sport-specific tests. Non-parametric statistical tests and inferential statistics were employed, and in addition, linear and regression models were created. Logistic regression models incorporating the study’s continuous predictors to classify injury occurrence in CF athletes were developed and evaluated using the Area Under the ROC Curve (AUC) as the performance metric. Results: A shoulder injury incidence rate of 0.79 per 1000 training hours was recorded. Olympic weightlifting (45%) and gymnastics (35%) exercises were associated with shoulder injury occurrence. The most frequent injury concerned rotator cuff tendons (45%), including lesions and tendinopathies, exhibiting various severity levels. None of the examined variables individually showed a statistically significant correlation with shoulder injuries. Conclusions: This is the first study that has investigated prospectively shoulder injuries in CrossFit, creating a realistic profile of these athletes. Despite the broad spectrum of collected data, the traditional statistical approach failed to identify shoulder injury predictors. This indicates the necessity to explore this topic using more sophisticated techniques, such as advanced machine learning approaches. Full article

Staphylococcus saprophyticus (S. saprophyticus) is an opportunistic coagulase-negative staphylococcus (CoNS) known to cause urinary tract infections in humans and is increasingly recognized in veterinary medicine. The aim of this study was to provide an epidemiological characterization of S. saprophyticus strains and to identify potential virulence factors that may contribute to interspecies transmission. This research is particularly important, as companion animals represent an understudied reservoir of this microorganism, and their role in the spread of resistant pathogens remains insufficiently understood. A total of 61 S. saprophyticus strains isolated from humans, dogs, and cats were analyzed. Identification was performed using MALDI-TOF MS and confirmed by PCR targeting the hrcA gene. Antimicrobial susceptibility was assessed using the disk diffusion and broth microdilution methods, while resistance genes were detected by PCR. The blaZ and mecA genes were present in all strains; additionally, the majority harbored the resistance genes ermA, ermB, tetM, and tetK. Multidrug resistance (MDR) was identified in 21/61 strains (34.4%). Biofilm-forming capacity was temperature-dependent, with the strongest biofilm production observed at 37 °C (70.5%). At 38 °C and 39 °C, the proportion of strong biofilm producers decreased to 50.8% and 52.5%, respectively. All tested strains demonstrated pathogenic potential in the Galleria mellonella larvae infection model, with the highest mortality recorded for selected feline and canine strains. These findings indicate that S. saprophyticus strains from both humans and companion animals possess notable virulence and multidrug resistance. The detection of genotypically and phenotypically resistant strains in animals highlights their potential role as reservoir for zoonotic transmission. Full article

Background: Post-concussion syndrome (PCS) and Functional Neurological Disorder (FND), including Functional Cognitive Disorder (FCD), are two frequently encountered but diagnostically complex conditions. While PCS is conceptualized as a sequela of mild traumatic brain injury (mTBI), FND/FCD encompasses symptoms incompatible with recognized neurological disease, often arising in the absence of structural brain damage. Yet, both conditions exhibit considerable clinical overlap—particularly in the domains of cognitive dysfunction, emotional dysregulation, and symptom persistence despite negative investigations. Objective: This review critically examines the shared and divergent features of PCS and FND/FCD. We explore their respective epidemiology, diagnostic criteria, and risk factors—including personality traits and trauma exposure—as well as emerging insights from neuroimaging and biomarkers. We propose the “Functional Overlay Model” as a clinical tool for navigating diagnostic ambiguity in patients with persistent post-injury symptoms. Results: PCS and FND/FCD frequently share features such as subjective cognitive complaints, fatigue, anxiety, and heightened somatic vigilance. High neuroticism, maladaptive coping, prior psychiatric history, and trauma exposure emerge as common risk factors. Neuroimaging studies show persistent network dysfunction in both PCS and FND, with overlapping disruption in fronto-limbic and default mode systems. The Functional Overlay Model helps to identify cases where functional symptomatology coexists with or replaces an initial organic insult—particularly in patients with incongruent symptoms and normal objective testing. Conclusions: PCS and FND/FCD should be conceptualized along a continuum of brain dysfunction, shaped by injury, psychology, and contextual factors. Early recognition of functional overlays and stratified psychological interventions may improve outcomes for patients with persistent, medically unexplained symptoms after head trauma. This review introduces the Functional Overlay Model as a novel framework to enhance diagnostic clarity and therapeutic planning in patients presenting with persistent post-injury symptoms. Full article

Hepatitis C is an infectious liver disease which contributes to an estimated 400,000 deaths each year. The disease is caused by the hepatitis C virus (HCV) and is spread by direct blood contact between infected and susceptible individuals. While the magnitude of its impact on human populations has prompted a growing body of scientific work, the current epidemiological models of HCV transmission among injecting drug users treat risk behaviors as fixed parameters rather than as outcomes of a dynamic, decision-making process. Our study addresses this gap by constructing a game-theoretic model to investigate the implications of voluntary participation in clean needle exchange programs on the spread of HCV among this high-risk population. Individual drug users weigh the (perceived) cost of clean equipment usage relative to the (perceived) cost of infection, as well as the strategies adopted by the rest of the population, and look for a selfishly optimal level of protection. We find that the spread of HCV in this population can theoretically be eliminated if individuals use sterile equipment approximately two-thirds of the time. Achieving this level of compliance, however, requires that the real and perceived costs of obtaining sterile equipment are essentially zero. Our study demonstrates a robust method for integrating game theory with epidemiological models to analyze voluntary health interventions. It provides a quantitative justification for public health policies that eliminate all barriers—both monetary and social—to comprehensive harm-reduction services. Full article

Narrative review synthesizes the most current literature on the SARS-CoV-2 XEC variant, focusing on its genomic evolution, immune evasion characteristics, epidemiological dynamics, and public health implications. To achieve this, we conducted a structured search of the literature of peer-reviewed articles, preprints, and official surveillance data from 2023 to early 2025, prioritizing virological, clinical, and immunological reports related to XEC and its parent lineages. Defined by the distinctive spike protein mutations, T22N and Q493E, XEC exhibits modest reductions in neutralization in vitro, although current evidence suggests that mRNA booster vaccines, including those targeting JN.1 and KP.2, retain cross-protective efficacy against symptomatic and severe disease. The XEC strain of SARS-CoV-2 has drawn particular attention due to its increasing prevalence in multiple regions and its potential to displace other Omicron subvariants, although direct evidence of enhanced replicative fitness is currently lacking. Preliminary analyses also indicated that glycosylation changes at the N-terminal domain enhance infectivity and immunological evasion, which is expected to underpin the increasing prevalence of XEC. The XEC variant, while still emerging, is marked by a unique recombination pattern and a set of spike protein mutations (T22N and Q493E) that collectively demonstrate increased immune evasion potential and epidemiological expansion across Europe and North America. Current evidence does not conclusively associate XEC with greater disease severity, although additional research is required to determine its clinical relevance. Key knowledge gaps include the precise role of recombination events in XEC evolution and the duration of cross-protective T-cell responses. New research priorities include genomic surveillance in undersampled regions, updated vaccine formulations against novel spike epitopes, and long-term longitudinal studies to monitor post-acute sequelae. These efforts can be augmented by computational modeling and the One Health approach, which combines human and veterinary sciences. Recent computational findings (GISAID, 2024) point to the potential of XEC for further mutations in under-surveilled reservoirs, enhancing containment challenges and risks. Addressing the potential risks associated with the XEC variant is expected to benefit from interdisciplinary coordination, particularly in regions where genomic surveillance indicates a measurable increase in prevalence. Full article

Background/Objectives: Epidemiological modeling is a vital tool for managing pandemics, including SARS-CoV-2. Advances in the understanding of epidemiological dynamics and access to new data sources necessitate ongoing adjustments to modeling techniques. In this study, we present a significantly expanded and updated version of our previous SARS-CoV-2 model formulated as input–output non-linear dynamical systems (IO-NLDS). Methods: This updated framework incorporates age-dependent contact patterns, immune waning, and new data sources, including seropositivity studies, hospital dynamics, variant trends, the effects of non-pharmaceutical interventions, and the dynamics of vaccination campaigns. Results: We analyze the dynamics of various datasets spanning the entire pandemic in Germany and its 16 federal states using this model. This analysis enables us to explore the regional heterogeneity of model parameters across Germany for the first time. We enhance our estimation methodology by introducing constraints on parameter variation among federal states to achieve this. This enables us to reliably estimate thousands of parameters based on hundreds of thousands of data points. Conclusions: Our approach is adaptable to other epidemic scenarios and even different domains, contributing to broader pandemic preparedness efforts. Full article

Background and Aim: Digital surveillance, which utilizes data from social media, search engines, and other online platforms, has emerged as an innovative approach for the early detection of infectious disease outbreaks. This scoping review aimed to systematically map and characterize the methodologies, performance metrics, and limitations of digital surveillance tools compared to traditional epidemiological monitoring. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute and PRISMA-SCR guidelines. Scientific databases including PubMed, Scopus, and Web of Science were searched, incorporating both empirical studies and systematic reviews without language restrictions. Key elements analyzed included digital sources, analytical algorithms, accuracy metrics, and validation against official surveillance data. Results: The reviewed studies demonstrate that digital surveillance can provide significant lead times (from days to several weeks) compared to traditional systems. While performance varies by platform and disease, many models showed strong correlations (r > 0.8) with official case data and achieved low predictive errors, particularly for influenza and COVID-19. Google Trends and X (formerly Twitter) emerged as the most frequently used sources, often analyzed using supervised regression, Bayesian models, and ARIMA techniques. Conclusions: While digital surveillance shows strong predictive capabilities, it faces challenges related to data quality and representativeness. Key recommendations include the development of standardized reporting guidelines to improve comparability across studies, the use of statistical techniques like stratification and model weighting to mitigate demographic biases, and leveraging advanced artificial intelligence to differentiate genuine health signals from media-driven noise. These steps are crucial for enhancing the reliability and equity of digital epidemiological monitoring. Full article

In this paper, an eco-epidemiological model with a weak Allee effect and prey disease dynamics is discussed. Mathematical features such as non-negativity, boundedness of solutions, and local stability of the feasible equilibria are discussed. Additionally, the transcritical bifurcation, saddle-node bifurcation, and Hopf bifurcation are proven using Sotomayor’s theorem and Poincare–Andronov–Hopf theorems. In addition, the correctness of the theoretical analysis is verified by numerical simulation. The numerical simulation results show that the eco-epidemiological model with a weak Allee effect has complex dynamics. If the prey population is not affected by disease, the predator becomes extinct due to a lack of food. Under low infection rates, all populations are maintained in a coexistent state. The Allee effect does not influence this coexistence. At high infection rates, if the prey population is not affected by the Allee effect, the infected prey is found to coexist in an oscillatory state. The predator population and the susceptible prey population will be extinct. If the prey population is affected by the Allee effect, all species will be extinct. Full article

Background/Objectives: Cefiderocol is a novel siderophore cephalosporin with potent in vitro activity against a broad spectrum of Gram-negative bacteria, including carbapenemase-producing Enterobacterales (CPE). However, the recent emergence of resistance in clinical settings raises important concerns regarding its long-term effectiveness. This study aims to investigate the genomic determinants associated with cefiderocol resistance in CPE isolates of human origin. Methods: Comparative genomic analyses were conducted between cefiderocol-susceptible and -resistant CPE isolates recovered from human clinical and epidemiological samples at a tertiary care hospital. Whole-genome sequencing, variant annotation, structural modelling, and pangenome analysis were performed to characterize resistance mechanisms. Results: A total of 59 isolates (29 resistant and 30 susceptible) were analyzed, predominantly comprising Klebsiella pneumoniae, Escherichia coli, and Enterobacter cloacae. The most frequent carbapenemase gene among the resistant isolates was bla_NDM, which was also present in a subset of susceptible strains. The resistant isolates exhibited a significantly higher burden of non-synonymous mutations in their siderophore receptor genes, notably within fecR, fecA, fiu, and cirA. Structural modelling predicted deleterious effects for mutations such as fecR:G104S and fecA:A190T. Additionally, porin loss and loop 3 insertions (e.g., GD/TD) in OmpK36, as well as OmpK35 truncations, were more frequent in the resistant isolates, particularly in high-risk clones such as ST395 and ST512. Genes associated with toxin–antitoxin systems (chpB2, pemI) and a hypothetical metalloprotease (group_2577) were uniquely found in the resistant group. Conclusions: Cefiderocol resistance in CPE appears to be multifactorial. NDM-type metallo-β-lactamases and missense mutations in siderophore uptake systems—especially in those encoded by fec, fhu, and cir operons—play a central role. These may be further potentiated by alterations in membrane permeability, such as porin disruption and efflux deregulation. The integration of genomic and structural approaches provides valuable insights into emerging resistance mechanisms and may support the development of diagnostic tools and therapeutic strategies. Full article