Search Results (2,014)

The prevalence and incidence of prediabetes in children and youth continue to increase in parallel with the obesity epidemic. While prediabetes is defined by elevated HbA1c and/or impaired glucose tolerance (IGT) and/or impaired fasting glucose (IFG), the risk of clinical disease is a continuum. Individuals with prediabetes are at a higher risk of developing youth-onset type 2 diabetes, which is considered a more aggressive form of the disease. This condition is associated with increased cardiovascular and metabolic risks and leads to an earlier onset of complications compared to adults with type 2 diabetes. Additionally, significant damage to beta cells may occur even before dysglycemia develops. Recent data indicate that mortality rates are higher in youths with type 2 diabetes compared to those with type 1 diabetes. Childhood prediabetes and cardiovascular complications associated with it are a significant health concern. This review provides the latest insights into this complex issue. We will present an overview of pathophysiology, screening methods, and therapeutic options to prevent the progression from prediabetes to type 2 diabetes in children. In summary, it is crucial to identify prediabetes in children, as this underscores the importance of appropriate screening and timely intervention. Full article

Mathematical models for infectious diseases, particularly autonomous ODE models, are generally known to possess simple dynamics, often converging to stable disease-free or endemic equilibria. This paper investigates the dynamic consequences of a crucial, yet often overlooked, component of pandemic response: the saturation of public health testing. We extend the standard SIR model to include compartments for ‘Confirmed’ (C) and ‘Monitored’ (M) individuals, resulting in a new SICMR model. By fitting the model to U.S. COVID-19 pandemic data (specifically the Omicron wave of late 2021), we demonstrate that capacity constraints in testing destabilize the testing-free endemic equilibrium ($E_1$). This equilibrium becomes an unstable saddle-focus. The instability is driven by a sociological feedback loop, where the rise in confirmed cases drive testing effort, modeled by a nonlinear Holling Type II functional response. We explicitly verify that the eigenvalues for the best-fit model satisfy the Shilnikov condition (${\lambda }_u>{\lambda }_s$), demonstrating the system possesses the necessary ingredients for complex, chaotic-like dynamics. Furthermore, we employ Stochastic Differential Equations (SDEs) to show that intrinsic noise interacts with this instability to generate ’noise-induced bursting,’ replicating the complex wave-like patterns observed in empirical data. Our results suggest that public health interventions, such as testing, are not merely passive controls but active dynamical variables that can fundamentally alter the qualitative stability of an epidemic. Full article

Introduction: The sustained global epidemic of Human Immunodeficiency Virus (HIV) necessitates comprehensive, region-specific surveillance to inform public health policy. This 30-year retrospective observational cohort study delineated the epidemiological patterns, transmission dynamics, treatment efficacy, and long-term clinical outcomes of HIV infection in Oman to strategically align preventative and therapeutic programs with Oman’s Vision 2040 framework. Methods: We analyzed the clinical and epidemiological data of 429 confirmed HIV-positive patients with a minimum follow-up period of six months, registered at a secondary care facility in North Batinah, Oman, between January 1995 and December 2024. Predictors of mortality were rigorously assessed utilizing Kaplan–Meier survival analysis and Cox proportional hazards regression models. Continuous variables were evaluated using independent sample t-tests or Mann–Whitney U tests, while categorical variables employed chi-square or Fisher’s exact tests. Results: The cohort exhibited a male predominance (70.6%) with a mean age at diagnosis of 32.8 years (SD ± 12.17). Heterosexual contact constituted the predominant mode of acquisition (56%), followed by bisexual (17%) and homosexual (12%) contacts. Although 67.1% of patients presented with early, asymptomatic disease (WHO Stage 1), opportunistic infections were evident in 28.1% of the cohort, with recurrent sepsis (8.4%) and bacterial pneumonia (3.5%) being the most frequent complications. The WHO clinical stage at presentation was confirmed as a highly significant predictor of survival (p < 0.0001). Stage 1 patients achieved excellent long-term prognosis (approximately 75% survival beyond 30 years), markedly contrasting with Stage 4 patients, whose survival declined sharply (median survival of approximately 8 years, and only 10–15% surviving past 20 years). The tenofovir/emtricitabine/efavirenz regimen showed superior efficacy, achieving 75% survival at 30 years, relative to zidovudine-based regimens, which showed significantly poorer performance (15–20% survival at 20 years). Conclusions: This investigation substantiates the shift toward predominant heterosexual transmission and emphasizes the critical prognostic significance of the clinical stage at diagnosis. Optimal long-term survival mandates prompt diagnosis, timely initiation of contemporary antiretroviral therapies, and sustained viral suppression. These findings offer crucial evidence to strengthen HIV prevention and treatment programs within Oman. Full article

The One Health framework highlights the interconnectedness of human, animal, and environmental health, requiring interdisciplinary and multisectoral collaboration to address complex global health challenges. This scoping review protocol aims to guide the systematic mapping on how studies and policy initiatives have incorporated socioecological interconnections within the One Health paradigm, following the Joanna Briggs Institute guidance and the PRISMA Scr checklist. The experimental design includes searches in PubMed, Scopus, Web of Science, LILACS, Health Systems Evidence, Social Systems Evidence, and Google Scholar for the period from 2004 to 2025. The strategy, developed with librarian support and peer reviewed, includes terms in English, Portuguese, and Spanish. Pilot searches retrieved 5333 PubMed and 470 LILACS records. Eligible documents must explicitly present two or more of the six One Health dimensions: policies to strengthen health systems; antimicrobial resistance; food safety; environmental health; emerging and re-emerging zoonotic epidemics and pandemics; endemic zoonotic, neglected tropical and vector-borne diseases. A standardized tool was developed for data extraction, synthesizing in narrative, tabular, and graphical formats. The protocol’s utilization will provide comprehensive mapping of practices and policies, identifying achievements, barriers, and knowledge gaps to inform future strategies and strengthen global health governance. Full article

We present several remarks on the spread of the COVID-19 epidemics in Bulgaria. The remarks are based on the hypothesis that the spread of the infection exhibits scaling properties similar to the scaling in urban dynamics. The corresponding mathematical theory leads us to a relationship for a power-law dependence of the number of infected in a certain region on the corresponding homochrony number. We prove the correctness of the mathematical theory on the basis of data for several Bulgarian regions for the first large COVID-19 wave in 2020. We observe a collapse of the real data along a single straight line. Full article

Background/Objectives: Despite large-scale measles and rubella (MR) vaccination campaigns in West Africa, measles outbreaks persist, raising concerns about campaign effectiveness, coverage, and underlying determinants. This study assesses the impact of MR follow-up campaigns in 12 of 17 West African countries (2024–2025) and examines the factors contributing to post-campaign outbreaks. The main objective of this study is to evaluate the impact of MR campaigns on measles transmission, identify the characteristics of post-campaign outbreaks, and propose strategies to improve campaign effectiveness and accelerate progress toward measles elimination in West Africa. Methods: We conducted a cross-sectional and ecological analytical study to examine spatial and temporal variations based on measles surveillance data from 2024 to 2025, post-campaign coverage surveys (PCCS), district-level outbreak reports, and administrative coverage reports. Trends in measles cases before and after the MMR campaigns were assessed, along with demographic characteristics and spatial analyses of confirmed cases. Results: In 2024, 70.5% (12/17) of countries conducted measles vaccination campaigns, but measles outbreaks increased in 2025 (64 districts in 2024 versus 383 in 2025). Children under five remained the most affected (54%), with 85% of cases being either unvaccinated (57%) or of unknown status (28%). Administrative coverage exceeded 95% in most countries, but measles PCCS revealed gaps, with only Senegal (93%) and Guinea-Bissau (94%) achieving high verified coverage. No country achieved 95% national MPCC. Conclusions: Suboptimal campaign quality, gaps in immunity beyond target age groups, and unreliable administrative data contributed to the persistence of outbreaks. Recommendations include extending Measles vaccination campaigns to older children (5–14 years), improving preparedness by drawing on experiences from other programs such as polio, standardizing PCCS data survey and analysis methodologies across all countries, and integrating Measles vaccination campaigns with other services such as nutrition. Full article

Following the normalization of the COVID-19 pandemic, the focus of wastewater-based epidemiology (WBE) must be broadened from SARS-CoV-2 to encompass surveillance of other major infectious diseases, particularly for pathogens where conventional clinical monitoring systems exhibit inherent surveillance gaps. In this study, we conducted a continuous two-year WBE study (January 2023 to December 2024) across three high-population-density cities in Guangdong, China to establish epidemiological baselines for enteric diarrheal viruses. We analyzed monthly raw wastewater samples from major treatment plants using advanced molecular methods, including digital PCR (ddPCR) for viral load quantification and targeted high-throughput sequencing (tNGS) for genotypic analysis. Our findings revealed diverse circulation patterns among the monitored enteric viruses. Astrovirus (AstV) had the highest detection rate (100%), reflecting its broad endemic distribution, while Norovirus genogroup II (NoV GII) exhibited relatively high viral loads (median 4 × 10⁴ copies/mL) and presented explosive seasonal peaks (significant upward trend in spring.), highlighting its epidemic potential. Furthermore, distinct spatiotemporal patterns were observed, with Sapovirus showing a significant summer peak in Foshan city, contrasting with the winter/spring peaks in the other cities. The tNGS results demonstrated similar sensitivity to RT-PCR in virus detection, and sequencing analyses uncovered the co-circulation and periodic shifts in dominant viral genotypes, such as the emergence of multiple NoV and AstV lineages. This longitudinal WBE surveillance successfully established critical baseline data and demonstrated significant regional heterogeneity in viral circulation, providing essential, complementary data to inform public health strategies for preventing diarrheal outbreaks in urban settings. Full article

In light of the current advances in computational epidemics and the need for improved epidemic governance strategies, we propose a novel meta-agent-based model (meta-ABM) constructed using the global airline complex network, using data from openflights.org, to establish a configurable framework for monitoring epidemic dynamics. By integrating our validated SICARQD complex epidemic model with global flights and airport information, we simulate the progression of an airborne epidemic, specifically reproducing the resurgence of COVID-19. In terms of originality, our meta-ABM considers each airport node (i.e., city) as an individual agent-based model assigned to its own independent SICARQD epidemic model. Agents within each airport node engage in probabilistic travel along established flight routes, mirroring real-world mobility patterns. This paper focuses primarily on investigating the effect of mobility restrictions by measuring the total number of cases, the peak infected ratio, and mortality caused by an epidemic outbreak. We analyze the impact of four key restriction policies imposed on the airline network, as follows: no restrictions, reducing flight frequencies, limiting flight distances, and a hybrid policy. Through simulations on scaled population systems of up to 1.36 million agents, our findings indicate that reducing the number of flights leads to a faster and earlier decrease in total infection cases, while restricting maximum flight distances results in a slower and much later decrease, effective only after canceling over 80% of flights. Notably, for practical travel restriction policies (e.g., 25–75% of flights canceled), epidemic control is significantly more effective when limiting flight frequency. This study shows the critical role of reducing global flight frequency as a public health policy to control epidemic spreading in our highly interconnected world. Full article

Enteric infections remain a major health and economic challenge in swine production, with outcomes determined not only by pathogen virulence but also by the complex interplay between host genetics, immune competence, and the intestinal microbiota. This review synthesises current knowledge on host–pathogen genomic interactions in pigs, with a focus on resilience mechanisms against enteric diseases in swine. For this purpose, 103 articles were used as information sources, retrieved through structured keyword searches in PubMed. The review first addresses host genetic factors, highlighting genomic variants and quantitative trait loci associated with resistance or resilience to viral and bacterial pathogens such as porcine epidemic diarrhoea virus (PEDV) or Escherichia coli. Next, the key factors of the immune system to confer protection are also reviewed, emphasising the role of innate and adaptive responses in controlling each pathogen and disclosing the contribution of regulatory networks that balance pathogen clearance. Finally, the last section of the review is devoted to exploring current knowledge in the involvement of the microbiota in resilience against enteric pathogens, mostly, but not exclusively, enteric bacteria. In this sense, competitive exclusion is a concept which has gained attention in recent years. The review pinpoints and discusses the state of the art about how the microbial community provides colonisation resistance, shapes immune development, and influences pathogen fitness within the intestinal niche. As final perspectives, the review explores future drivers in the genetic immune and microbiota resistance. By bridging host genomic data with functional insights into immunity and microbial ecology, this review underscores the potential of multi-omics approaches to enhance resilience against enteric infections in pigs and advance sustainable swine health management. Full article

In recent years, the complexity and suddenness of infectious disease transmission have posed significant limitations for traditional time-series forecasting methods when dealing with the nonlinearity, non-stationarity, and multi-peak distributions of epidemic scale variations. To address this challenge, this paper proposes a forecasting framework based on diffusion models, called CNL-Diff, aimed at tackling the prediction challenges in complex dynamics, nonlinearity, and non-stationary distributions. Traditional epidemic forecasting models often rely on fixed linear assumptions, which limit their ability to accurately predict the incidence scale of infectious diseases. The CNL-Diff framework integrates a forward–backward consistent conditioning mechanism and nonlinear data transformations, enabling it to capture the intricate temporal and feature dependencies inherent in epidemic data. The results show that this method outperforms baseline models in metrics such as Mean Absolute Error (MAE), Continuous Ranked Probability Score (CRPS), and Prediction Interval Coverage Probability (PICP). This study demonstrates the potential of diffusion models in complex-distribution time-series modeling, providing a more reliable probabilistic forecasting tool for public health monitoring, epidemic early warning, and risk decision making. Full article

Background: Obesity is a major health concern worldwide and the World Health Organization (WHO) has declared it a global epidemic. We aimed to analyze temporal trends of obesity prevalence worldwide. Methods: We used data of “The Global Health Observatory” of the WHO and analyzed data from the Global Burden of Disease (GBD) Study 2023. Obesity prevalence (crude estimates) among adults in different worldwide WHO regions and temporal trends from 1976 and 2016 were analyzed. Results: Obesity prevalence showed large regional differences. In 2016, obesity prevalence was highest in the WHO European region and the region of the Americas, at more than 20%, whereas prevalence was lower in the WHO African region, the WHO Western Pacific region and the WHO South-East Asia region, at less than 10%. The absolute increase from 1976 to 2016 comprised an increase of 19.7% in the region of the Americas, of 14.8% and 14.2% in the WHO European region and the WHO Eastern Mediterranean region, followed by 7.3% in the WHO African region, 6.0% in the WHO Western Pacific region, and 4.2% in the WHO South-East Asia region. We observed a substantially higher prevalence of obesity in females. High BMI has risen sharply in rank worldwide, now ranging among the top six global risk factors for death. Major BMI-related causes include ischemic heart disease, type 2 diabetes mellitus, hypertensive heart disease, and ischemic stroke. Conclusions: Obesity prevalence showed large regional differences and was highest in Europe and America. The prevalence of obesity increased worldwide between 1976 and 2016. Obesity prevalence was higher in females than in males. The importance of obesity for premature death increased between 1990 and 2023. Full article

Seasonal influenza continues to pose a substantial and recurrent public health challenge in Queensland, driven by annual variability in transmission and uncertainty in climatic, demographic, and behavioural determinants. Predictive modelling is constrained by data limitations and parameter uncertainty. In response, this study developed a Bayesian network (BN) model to estimate the probability of influenza epidemics in Queensland, Australia. The model integrated diverse inputs, including international and local influenza surveillance data, demographic health statistics, and expert and stakeholder insights to capture the complex multifactorial causal relationships underlying epidemic risk. Scenario-based simulations revealed that Southeast Asian viral origin, severe global influenza seasons, peak season timing, increasing international travel, absence of control measures, and low immunisation rates substantially elevate the likelihood of influenza epidemics. Southeast Queensland was identified as particularly vulnerable under high-risk conditions. Model evaluation demonstrated good discriminative performance (AUC = 0.6974, accuracy = 70%) with appropriate uncertainty quantification through credible intervals and sensitivity analysis. Its modular design and capacity for integrating various data sources make it a practical decision-making support tool for public health preparedness and responding to evolving climatic and epidemiological conditions. Full article

Background/Objectives: Tuberculosis (TB) remains a major global health challenge influenced by social determinants of health (SDHs) such as poverty, overcrowding, malnutrition, and limited healthcare access. Although Central Asia (CA) has achieved progress through vaccination, screening, and treatment, the region continues to face severe disease consequences, unstable incidence patterns, and an escalating challenge of TB resistant to first-line drugs. This study aimed to analyze TB incidence dynamics in Kazakhstan, Tajikistan, the Kyrgyz Republic, Turkmenistan, and Uzbekistan from 2000–2023, forecast trends to 2030, and identify key SDHs shaping the epidemic. Methods: Data on TB incidence were obtained from the World Bank DataBank for 2000–2023. Of 61 socioeconomic, environmental, and health-related indicators, 29 were included in the analysis. Statistical procedures in SPSS (v24.0) involved time-series forecasting through 2030, calculation of average annual percentage change (AAPC), correlation testing, and linear regression, with significance set at p < 0.05. Results: TB incidence generally declined across CA during 2000–2023, though trends varied by country. Forecasts suggest continued decreases in Turkmenistan and Uzbekistan, while Kazakhstan, Tajikistan, and the Kyrgyz Republic display fluctuating or nonsignificant patterns, likely influenced by SDHs. Regression analyses indicated that anemia, undernourishment, and population density showed a positive relationship with TB incidence, while clean fuel access, physician density, and Gross Domestic Product per capita (GDP) were inversely related. Conclusions: The findings highlight the heterogeneous nature of TB dynamics in CA and the possible role of SDHs. Enhanced surveillance, nutritional and social interventions are required to sustain progress toward End TB targets. Full article

Background: Type 2 diabetes mellitus (T2DM) is a global epidemic in which gut microbiota dysbiosis contributes to impaired glucose homeostasis and chronic inflammation. Intermittent fasting (IF) and probiotic supplementation have independently demonstrated glycemic benefits in T2DM, largely through microbiota remodeling. This narrative review synthesizes evidence up to October 2025 to clarify the microbiota-dependent mechanisms of IF and probiotics, and to evaluate the biological plausibility and preliminary clinical data for their combined application in T2DM management. Methods: We conducted a comprehensive literature review of preclinical and clinical studies (PubMed, Embase, Web of Science, and Cochrane Library) examining IF regimens (primarily time-restricted feeding and 5:2 protocols) and multi-strain probiotics containing Lactobacillus and Bifidobacterium species in T2DM or relevant models. Mechanistic pathways, microbial compositional shifts, and metabolic outcomes were qualitatively synthesized, with emphasis on overlapping signaling (short-chain fatty acids, bile acids, GLP-1, and barrier function). Results: IF consistently increases Akkermansia muciniphila and, variably, Faecalibacterium prausnitzii abundance, restores microbial circadian rhythmicity, and enhances SCFA and secondary bile acid production. Multi-strain probiotics modestly reduce HbA1c (–0.3% to –0.6%) and fasting glucose, outperforming single-strain preparations. Both interventions converge on reduced endotoxaemia and improved intestinal integrity. Preclinical models indicate potential synergy, whereas the only direct human trial to date showed neutral results. Conclusions: IF and probiotics engage overlapping microbiota-mediated pathways, supporting their combined use as an adjunctive strategy in T2DM. Adequately powered randomized trials incorporating deep metagenomics, metabolomics, and hard clinical endpoints are now required to confirm additive or synergistic efficacy. Full article

Background: Measles re-emergence has been reported across Europe, with Romania being among the most affected countries in 2023–2024. Although ocular manifestations are recognized in measles, their frequency and inflammatory correlates in hospitalized adults have not been well characterized. Methods: This study retrospectively analyzed the medical records of adults treated for laboratory-confirmed measles at a Bucharest hospital between July 2023 and July 2024. Data from specialist eye examinations were used to compare patients with keratitis against those with other ocular issues. Results: A total of 250 adult patients were included. Of the 88 patients referred for ophthalmologic examination, 93.2% showed ocular lesions. Keratitis was the primary form, identified in 64.6% of these cases. Patients with keratitis had blood markers indicating a more activated inflammatory profile (higher neutrophile-to-lymphocytes ratio). Pneumonia and respiratory failure were not associated with ocular lesion status; inflammatory markers were more strongly linked to respiratory failure than to ocular involvement. Conclusions: Ocular lesions were highly prevalent in hospitalized adult measles cases during the 2023–2024 Romanian epidemic wave, and keratitis was common. Ocular involvement correlated with mucosal disease expression and systemic inflammatory activation. Systematic ophthalmologic assessment should be considered during measles epidemic peaks to improve early identification of clinically relevant ocular complications. Full article