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Background Inflammatory bowel disease (IBD) is a global health concern with varying levels and trends across countries and regions. Understanding these differences is crucial for effective prevention and treatment strategies. Methods Using data from the 2019 Global Burden of Disease study, we examine IBD incidence, mortality, and disability-adjusted life years (DALYs) rates in 198 countries from 1990 to 2019. To assess changes in the burden of IBD, estimated annual percentage changes (EAPC) were calculated, and a Bayesian age-period-cohort model was used to predict the future 30-year trends of IBD. Results In 2019, there were 405,000 new IBD cases globally (95% uncertainty interval (UI) 361,000 to 457,000), with 41,000 deaths (95% UI 35,000 to 45,000) and 1.62million DALYs (95% UI 1.36–1.92million). The global age-standardized incidence rate in 2019 was 4.97 per 100,000 person-years (95% UI 4.43 to 5.59), with a mortality rate of 0.54 (95% UI 0.46 to 0.59) and DALYs rate of 20.15 (95% UI 16.86 to 23.71). From 1990 to 2019, EAPC values for incidence, mortality, and DALYs rates were − 0.60 (95% UI − 0.73 to − 0.48), − 0.69 (95% UI − 0.81 to − 0.57), and − 1.04 (95% UI − 1.06 to − 1.01), respectively. Overall, the burden of IBD has shown a slow decline in recent years. In SDI stratification, regions with higher initial SDI (high-income North America and Central Europe) witnessed decreasing incidence and mortality rates with increasing SDI, while regions with lower initial SDI (South Asia, Oceania, and Latin America) experienced a rapid rise in incidence but a decrease in mortality with increasing SDI. Predictions using a Bayesian model showed lower new cases and deaths from 2020 to 2050 than reference values, while the slope of the predicted incidence-time curve closely paralleled that of the 2019 data. Conclusion Increasing cases, deaths, and DALYs highlight the sustained burden of IBD on public health. Developed countries have stabilized or declining incidence rates but face high prevalence and societal burden. Emerging and developing countries experience rising incidence. Understanding these changes aids policymakers in effectively addressing IBD challenges in different regions and economic contexts.

Emerging zoonotic diseases represent a significant threat to global health. While machine learning (ML) holds promise for their management, a comprehensive understanding of how these technologies are applied across the entire animal‐to‐human transmission pathway is lacking. This scoping review systematically maps ML applications in zoonotic disease management to identify research trends, methodological approaches, and critical gaps across different epidemiological stages and functional domains. We organize the literature along two dimensions: epidemiological stages, from animal hosts to human populations, and functional domain, including diagnosis, epidemiology, and intervention. We searched PubMed and Web of Science for studies on 14 preselected high‐priority zoonotic diseases. The search string combined keywords for the selected diseases, ML techniques, and functional applications (diagnosis, epidemiology, and intervention). A total of 966 studies were included in the final analysis, of which 72.8% focused on COVID‐19. Our analysis shows robust ML performance in clinical diagnostics, epidemic forecasting, and intervention optimization within human populations. However, critical gaps persist, only 1.96% of studies examined the animal–human interface, no ML models explicitly targeted spillover prevention, and studies on animal‐reservoir surveillance remain limited. All spillover studies originated from high‐income or upper‐middle‐income countries (UMICs), in contrast with low‐ and lower‐middle‐income countries (LMICs) contributing 21.4% of human‐stage studies. These findings reveal a pronounced mismatch between research investment and spillover risk and highlight the need for greater emphasis on spillover mechanisms, enhanced integration of cross‐species transmission dynamics, and methods suitable for surveillance in resource‐limited settings. Addressing these imbalances is essential for advancing a shift from reactive outbreak response to proactive spillover prevention within a One Health framework.

Key Points Diffuse idiopathic skeletal hyperostosis (DISH) is characterized by entheseal ossification and/or calcification involving mainly the thoracic spine Peripheral joints and adjacent entheses can also be involved The pathogenesis of DISH is not clear, but several factors may promote the differentiation of mesenchymal cells into bone-forming cells DISH is often associated with a variety of metabolic derangements, which may increase cardiovascular morbidity Patients with DISH also have an increased risk of complicated spinal fractures, with associated morbidities Diffuse idiopathic skeletal hyperostosis (DISH) is a poorly understood condition characterized by ossification of ligaments and entheses. This comprehensive Review explains the epidemiology and clinical manifestations of DISH, as well as highlighting the latest insights into pathogenic mechanisms. The authors also argue for the development of new classification criteria that can identify early disease. Diffuse idiopathic skeletal hyperostosis (DISH) is a systemic condition characterized by the ossification and calcification of ligaments and entheses. DISH is observed on all continents and in all races, but most commonly in men over 50 years of age. Although DISH is asymptomatic in most individuals, the condition is often an indicator of underlying metabolic disease, and the presence of spinal or extraspinal ossifications can sometimes lead to symptoms including pain, stiffness, a reduced range of articular motion, and dysphagia, as well as increasing the risk of unstable spinal fractures. The aetiology of DISH is poorly understood, and the roles of the many factors that might be involved in the development of excess bone are not well delineated. The study of pathophysiological aspects of DISH is made difficult by the formal diagnosis requiring the presence of multiple contiguous fully formed bridging ossifications, which probably represent advanced stages of DISH. In this Review, the reader is provided with an up-to-date discussion of the epidemiological, aetiological and clinical aspects of DISH. Existing classification criteria (which, in the absence of diagnostic criteria, are used to establish a diagnosis of DISH) are also considered, together with the need for modified criteria that enable timely identification of early phases in the development of DISH.

This chapter contains sections titled: Advantages of an epidemiological approach Epidemiological studies are not always the best approach Stages in an epidemiological study Epidemiological findings in child and adolescent psychiatry Subject review Further reading

Host–parasite systems have intricately coupled life cycles, but each interactor can respond differently to changes in environmental variables like temperature. Although vital to predicting how parasitism will respond to climate change, thermal responses of both host and parasite in key traits affecting infection dynamics have rarely been quantified. Through temperature-controlled experiments on an ectothermic host–parasite system, we demonstrate an offset in the thermal optima for survival of infected and uninfected hosts and parasite production. We combine experimentally derived thermal performance curves with field data on seasonal host abundance and parasite prevalence to parameterize an epidemiological model and forecast the dynamical responses to plausible future climate-warming scenarios. In warming scenarios within the coastal southeastern United States, the model predicts sharp declines in parasite prevalence, with local parasite extinction occurring with as little as 2 °C warming. The northern portion of the parasite’s current range could experience local increases in transmission, but assuming no thermal adaptation of the parasite, we find no evidence that the parasite will expand its range northward under warming. This work exemplifies that some host populations may experience reduced parasitism in a warming world and highlights the need to measure host and parasite thermal performance to predict infection responses to climate change.

Key features of P. vivax confounding its control and elimination include the parasite’s ability to form dormant liver stages (hypnozoites) that can cause relapse weeks to months after an initial infection, the ability to circulate at low peripheral parasite densities while remaining transmissible to the mosquito vector, and the early production of sexual stages (gametocytes) that allow the parasite to transmit prior to clinical presentation and gametocytocidal treatment. The frequency and timing of these relapses vary considerably with geographical region, host immunity, and the number of sporozoites inoculated by the mosquito the absolute risk over 12 months ranging from less than 10% in temperate areas to more than 80% in tropical climates [5]. [...]recurrent P. vivax infections in early life result in a faster acquisition of immunity than that following P. falciparum, non-sterilising immunity suppressing clinical disease, and a lower risk of illness in older individuals [8]. Monitoring the impact of public health interventions Conventionally, the surveillance of P. vivax malaria has relied upon reporting of the prevalence and incidence of P. vivax infection, identified by light microscopy (LM) or rapid diagnostic tests (RDTs).

Participants in epidemiologic and genetic studies are rarely true random samples of the populations they are intended to represent, and both known and unknown factors can influence participation in a study (known as selection into a study). The circumstances in which selection causes bias in an instrumental variable (IV) analysis are not widely understood by practitioners of IV analyses. We use directed acyclic graphs (DAGs) to depict assumptions about the selection mechanism (factors affecting selection) and show how DAGs can be used to determine when a two-stage least squares IV analysis is biased by different selection mechanisms. Through simulations, we show that selection can result in a biased IV estimate with substantial confidence interval (CI) undercoverage, and the level of bias can differ between instrument strengths, a linear and nonlinear exposure–instrument association, and a causal and noncausal exposure effect. We present an application from the UK Biobank study, which is known to be a selected sample of the general population. Of interest was the causal effect of staying in school at least 1 extra year on the decision to smoke. Based on 22,138 participants, the two-stage least squares exposure estimates were very different between the IV analysis ignoring selection and the IV analysis which adjusted for selection (e.g., risk differences, 1.8% [95% CI, −1.5%, 5.0%] and −4.5% [95% CI, −6.6%, −2.4%], respectively). We conclude that selection bias can have a major effect on an IV analysis, and further research is needed on how to conduct sensitivity analyses when selection depends on unmeasured data.

The reproductive life span in women starts at puberty and ends at menopause, following the exhaustion of the follicle stockpile termed the ovarian reserve. Increasing data from experimental animal models and epidemiological studies indicate that exposure to a number of ubiquitously distributed reproductively toxic environmental chemicals (RTECs) can contribute to earlier menopause and even premature ovarian failure. However, the causative relationship between environmental chemical exposure and earlier menopause in women remains poorly understood. The present work, is an attempt to review the current evidence regarding the effects of RTECs on the main ovarian activities in mammals, focusing on how such compounds can affect the ovarian reserve at any stages of ovarian development. We found that in rodents, strong evidence exists that in utero, neonatal, prepubescent and even adult exposure to RTECs leads to impaired functioning of the ovary and a shortening of the reproductive lifespan. Regarding human, data from cross-sectional surveys suggest that human exposure to certain environmental chemicals can compromise a woman’s reproductive health and in some cases, correlate with earlier menopause. In conclusion, evidences exist that exposure to RTECs can compromise a woman’s reproductive health. However, human exposures may date back to the developmental stage, while the adverse effects are usually diagnosed decades later, thus making it difficult to determine the association between RTECs exposure and human reproductive health. Therefore, epidemiological surveys and more experimental investigation on humans, or alternatively primates, are needed to determine the direct and indirect effects caused by RTECs exposure on the ovary function, and to characterize their action mechanisms.

ObjectivesA prospective randomised trial to compare two different durations of maintenance immunosuppressive therapy for the prevention of relapse in anti-neutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV).MethodsPatients with AAV were recruited 18–24 months after diagnosis if they were in stable remission after cyclophosphamide/prednisolone-based induction followed by azathioprine/prednisolone maintenance therapy. They were randomised (1:1) to receive continued azathioprine/prednisolone to 48 months from diagnosis (continuation group) or to withdraw azathioprine/prednisolone by 24 months (withdrawal group). The primary endpoint was the relapse risk, from randomisation to 48 months from diagnosis.ResultsOne hundred and seventeen patients were randomised and 110 remained to the trial end. At entry, median serum creatinine was 116 μmol/L (range 58–372), 53% were ANCA positive. The percentage of patients presenting with relapse was higher in the withdrawal than in the continuation treatment group (63% vs 22%, p<0.0001, OR 5.96, 95% CI 2.58 to 13.77). ANCA positivity at randomisation was associated with relapse risk (51% vs 29%, p=0.017, OR 2.57, 95% CI 1.16 to 5.68). Renal function, ANCA specificity, vasculitis type and age were not predictive of relapse. Severe adverse events were more frequent in the continuation than withdrawal groups (nine vs three events), but the continuation group had better renal outcome (0 vs 4 cases of end-stage renal disease), with no difference in patient survival.ConclusionsProlonged remission maintenance therapy with azathioprine/prednisolone, beyond 24 months after diagnosis reduces relapse risk out to 48 months and improves renal survival in AAV.Trial registration numberISRCTN13739474

Background The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for investigating simultaneously non-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimates of multi-parameter associations. However, the application of both methods in two-stage analyses is prevented by the high-dimensional definition of DLNMs. Methods In this contribution we propose a method to synthesize DLNMs to simpler summaries, expressed by a reduced set of parameters of one-dimensional functions, which are compatible with current multivariate meta-analytical techniques. The methodology and modelling framework are implemented in R through the packages dlnm and mvmeta . Results As an illustrative application, the method is adopted for the two-stage time series analysis of temperature-mortality associations using data from 10 regions in England and Wales. R code and data are available as supplementary online material. Discussion and Conclusions The methodology proposed here extends the use of DLNMs in two-stage analyses, obtaining meta-analytical estimates of easily interpretable summaries from complex non-linear and delayed associations. The approach relaxes the assumptions and avoids simplifications required by simpler modelling approaches.