Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen-drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. MethodsWe estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen-drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drugresistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. FindingsOn the basis of our predictive statistical models, there were an estimated 4•95 million (3•62-6•57) deaths associated with bacterial AMR in 2019, including 1•27 million (95% UI 0•911-1•71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27•3 deaths per 100 000 (20•9-35•3), and lowest in Australasia, at 6•5 deaths (4•3-9•4) per 100 000. Lower respiratory infections accounted for more than 1•5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000-1 270 000) deaths attributable to AMR and 3•57 million (2•62-4•78) deaths associated with AMR in 2019. One pathogen-drug combination, meticillinresistant S aureus, caused more than 100 000 deaths attributa...

IntroductionComorbidities including diabetes mellitus (DM) among people living with HIV (PLHIV) are of increasing clinical concerns in combination antiretroviral therapy (cART) era. We aimed to determine the incidence and risk factors of new‐onset DM among PLHIV in Asian settings.Methods PLHIV from a regional observational cohort without DM prior to antiretroviral therapy (ART) initiation were included in the analysis. DM was defined as having a fasting blood glucose ≥126 mg/dL, glycated haemoglobin ≥6.5%, a two‐hour plasma glucose ≥200 mg/dL, or a random plasma glucose ≥200 mg/dL. A Cox regression model, stratified by site, was used to identify risk factors associated with DM.Results and discussionOf the 1927 participants included, 127 were diagnosed with DM after ART initiation. Median follow‐up time from ART initiation to DM diagnosis was 5.9 years (interquartile range (IQR): 2.8 to 8.9 years). The crude incidence rate of DM was 1.08 per 100 person‐years (100 PYS), 95% confidence interval (CI) (0.9 to 1.3). In the multivariate analysis, later years of follow‐up (2011 to 2013: HR = 2.34, 95% CI 1.14 to 4.79, p = 0.02; and 2014 to 2017: HR = 7.20, 95% CI 3.27 to 15.87, p < 0.001) compared to <2010, older age (41 to 50 years: HR = 2.46, 95% CI 1.39 to 4.36, p  = 0.002; and >50 years: HR = 4.19, 95% CI 2.12 to 8.28, p < 0.001) compared to <30 years, body mass index (BMI) >30 kg/m2 (HR = 4.3, 95% CI 1.53 to 12.09, p = 0.006) compared to BMI <18.5 kg/m2, and high blood pressure (HR = 2.05, 95% CI 1.16 to 3.63, p = 0.013) compared to those without high blood pressure, were associated with developing DM. The hazard was reduced for females (HR = 0.47, 95% CI 0.28 to 0.80, p = 0.006).ConclusionsType 2 DM in HIV‐infected Asians was associated with later years of follow‐up, high blood pressure, obesity and older age. This highlights the importance of monitoring and routine screening for non‐communicable diseases including DM as PLHIV age.

Introduction Since 2015, the World Health Organization (WHO) has recommended that all people living with HIV (PLHIV) initiate antiretroviral treatment (ART), irrespective of CD4+ count or clinical stage. National adoption of universal treatment has accelerated since WHO's 2015 “Treat All” recommendation; however, little is known about the translation of this guidance into practice. This study aimed to assess the status of Treat All implementation across regions, countries, and levels of the health care delivery system. Methods Between June and December 2017, 201/221 (91%) adult HIV treatment sites that participate in the global IeDEA research consortium completed a survey on capacity and practices related to HIV care. Located in 41 countries across seven geographic regions, sites provided information on the status and timing of site‐level introduction of Treat All, as well as site‐level practices related to ART initiation. Results Almost all sites (93%) reported that they had begun implementing Treat All, and there were no statistically significant differences in site‐level Treat All introduction by health facility type, urban/rural location, sector (public/private) or country income level. The median time between national policy adoption and site‐level introduction was one month. In countries where Treat All was not yet adopted in national guidelines, 69% of sites reported initiating all patients on ART, regardless of clinical criteria, and these sites had been implementing Treat All for a median period of seven months at the time of the survey. The majority of sites (77%) reported typically initiating patients on ART within 14 days of confirming diagnosis, with 60% to 62% of sites implementing Treat All in East, Southern and West Africa reporting same‐day ART initiation for most patients. Conclusions By mid‐ to late‐2017, the Treat All strategy was the standard of care at almost all IeDEA sites, including rural, primary‐level health facilities in low‐resource settings. While further assessments of site‐level capacity to provide high‐quality HIV care under Treat All and to support sustained viral suppression after ART initiation are needed, the widespread introduction of Treat All at the service delivery level is a critical step towards global targets for ending the HIV epidemic as a public health threat.

Introduction Multiple comorbidities among HIV ‐positive individuals may increase the potential for polypharmacy causing drug‐to‐drug interactions and older individuals with comorbidities, particularly those with cognitive impairment, may have difficulty in adhering to complex medications. However, the effects of age‐associated comorbidities on the treatment outcomes of combination antiretroviral therapy ( cART ) are not well known. In this study, we investigated the effects of age‐associated comorbidities on therapeutic outcomes of cART in HIV ‐positive adults in Asian countries. Methods Patients enrolled in the TREAT Asia HIV Observational Database cohort and on cART for more than six months were analysed. Comorbidities included hypertension, diabetes, dyslipidaemia and impaired renal function. Treatment outcomes of patients ≥ 50 years of age with comorbidities were compared with those <50 years and those ≥ 50 years without comorbidities. We analysed 5411 patients with virological failure and 5621 with immunologic failure. Our failure outcomes were defined to be in‐line with the World Health Organization 2016 guidelines. Cox regression analysis was used to analyse time to first virological and immunological failure. Results The incidence of virologic failure was 7.72/100 person‐years. Virological failure was less likely in patients with better adherence and higher CD 4 count at cART initiation. Those acquiring HIV through intravenous drug use were more likely to have virological failure compared to those infected through heterosexual contact. On univariate analysis, patients aged <50 years without comorbidities were more likely to experience virological failure than those aged ≥50 years with comorbidities (hazard ratio 1.75, 95% confidence interval (CI) 1.31 to 2.33, p < 0.001). However, the multivariate model showed that age‐related comorbidities were not significant factors for virological failure (hazard ratio 1.31, 95% CI 0.98 to 1.74, p = 0.07). There were 391 immunological failures, with an incidence of 2.75/100 person‐years. On multivariate analysis, those aged <50 years without comorbidities ( p = 0.025) and age <50 years with comorbidities ( p = 0.001) were less likely to develop immunological failure compared to those aged ≥50 years with comorbidities. Conclusions In our Asia regional cohort, age‐associated comorbidities did not affect virologic outcomes of cART . Among those with comorbidities, patient...

Introduction Interruptions in treatment pose risks for people with HIV (PWH) and threaten progress in ending the HIV epidemic; however, the COVID‐19 pandemic's impact on HIV service delivery across diverse settings is not broadly documented. Methods From September 2020 to March 2021, the International epidemiology Databases to Evaluate AIDS (IeDEA) research consortium surveyed 238 HIV care sites across seven geographic regions to document constraints in HIV service delivery during the first year of the pandemic and strategies for ensuring care continuity for PWH. Descriptive statistics were stratified by national HIV prevalence (<1%, 1–4.9% and ≥5%) and country income levels. Results Questions about pandemic‐related consequences for HIV care were completed by 225 (95%) sites in 42 countries with low ( n = 82), medium ( n = 86) and high ( n = 57) HIV prevalence, including low‐ ( n = 57), lower‐middle ( n = 79), upper‐middle ( n = 39) and high‐ ( n = 50) income countries. Most sites reported being subject to pandemic‐related restrictions on travel, service provision or other operations (75%), and experiencing negative impacts (76%) on clinic operations, including decreased hours/days, reduced provider availability, clinic reconfiguration for COVID‐19 services, record‐keeping interruptions and suspension of partner support. Almost all sites in low‐prevalence and high‐income countries reported increased use of telemedicine (85% and 100%, respectively), compared with less than half of sites in high‐prevalence and lower‐income settings. Few sites in high‐prevalence settings (2%) reported suspending antiretroviral therapy (ART) clinic services, and many reported adopting mitigation strategies to support adherence, including multi‐month dispensing of ART (95%) and designating community ART pick‐up points (44%). While few sites (5%) reported stockouts of first‐line ART regimens, 10–11% reported stockouts of second‐ and third‐line regimens, respectively, primarily in high‐prevalence and lower‐income settings. Interruptions in HIV viral load (VL) testing included suspension of testing (22%), longer turnaround times (41%) and supply/reagent stockouts (22%), but did not differ across settings. Conclusions While many sites in high HIV prevalence settings and lower‐income countries reported introducing or expanding measures to support treatment adherence and continuity of care, the COVID‐19 pandemic resulted in disruptions to VL testing and ART supply chains that may negatively affect the quality of HIV care in these settings.