Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries.Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution.Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990-2010 time period, with the greatest annualised rate of decline occurring in the 0-9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10-24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the...

Summary Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast,...

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Multiple sclerosis (MS) is an autoimmune disease characterized by recurrent episodes of demyelination and axonal lesion mediated by CD4+ T cells with a proinflammatory Th1 and Th17 phenotype, macrophages, and soluble inflammatory mediators. Identification of Th17 cells led to breaking the dichotomy of Th1/Th2 axis in immunopathogenesis of autoimmune diseases such as MS, and its experimental model, experimental autoimmune encephalomyelitis (EAE). Th17 cells are characterized by expression of retinoic acid‐related orphan receptor (ROR)γt and signal transducer and activator of transcription 3 (STAT3) factors. Th17‐produced cytokine profile including interleukin (IL)‐17, IL‐6, IL‐21, IL‐22, IL‐23 and tumour necrosis factor (TNF)‐α, which have proinflammatory functions, suggests it as an important factor in immunopathogenesis of MS, because the main feature of MS pathophysiology is the neuroinflammatory reaction. The blood brain barrier (BBB) disruption is an early and central event in MS pathogenesis. Autoreactive Th17 cells can migrate through the BBB by the production of cytokines such as IL‐17 and IL‐22, which disrupt tight junction proteins in the central nervous system (CNS) endothelial cells. Consistent with this observation and regarding the wide range production of proinflammatory cytokines and chemokines by Th17 cells, it is expected that Th17 cell to be as a potent pathogenic factor in disease immunopathophysiology. Th17‐mediated inflammation is characterized by neutrophil recruitment into the CNS and neurons killing. However, the majority of our knowledge about the role of Th17 in MS pathogenesis is resulted in investigation into EAE animal models. In this review, we intend to focus on the newest information regarding the precise role of Th17 cells in immunopathogenesis of MS, and its animal model, EAE.

In the course of the coronavirus disease 2019 (COVID‐19), raising and reducing the function of Th17 and Treg cells, respectively, elicit hyperinflammation and disease progression. The current study aimed to evaluate the responses of Th17 and Treg cells in COVID‐19 patients compared with the control group. Forty COVID‐19 intensive care unit (ICU) patients were compared with 40 healthy controls. The frequency of cells, gene expression of related factors, as well as the secretion levels of cytokines, were measured by flow cytometry, real‐time polymerase chain reaction, and enzyme‐linked immunosorbent assay techniques, respectively. The findings revealed a significant increase in the number of Th17 cells, the expression levels of related factors (RAR‐related orphan receptor gamma [RORγt], IL‐17, and IL‐23), and the secretion levels of IL‐17 and IL‐23 cytokines in COVID‐19 patients compared with controls. In contrast, patients had a remarkable reduction in the frequency of Treg cells, the expression levels of correlated factors (Forkhead box protein P3 [FoxP3], transforming growth factor‐β [TGF‐β], and IL‐10), and cytokine secretion levels (TGF‐β and IL‐10). The ratio of Th17/Treg cells, RORγt/FoxP3, and IL‐17/IL‐10 had a considerable enhancement in patients compared with the controls and also in dead patients compared with the improved cases. The findings showed that enhanced responses of Th17 cells and decreased responses of Treg cells in 2019‐n‐CoV patients compared with controls had a strong relationship with hyperinflammation, lung damage, and disease pathogenesis. Also, the high ratio of Th17/Treg cells and their associated factors in COVID‐19‐dead patients compared with improved cases indicates the critical role of inflammation in the mortality of patients.

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