Binderupdavenport0733

BackgroundPeople who inject drugs (PWID) are frequently incarcerated, which is associated with multiple negative health outcomes.AimWe aimed to estimate the associations between a history of incarceration and prevalence of HIV and HCV infection among PWID in Europe.MethodsAggregate data from PWID recruited in drug services (excluding prison services) or elsewhere in the community were reported by 17 of 30 countries (16 per virus) collaborating in a European drug monitoring system (2006-2020; n = 52,368 HIV+/-; n = 47,268 HCV+/-). Country-specific odds ratios (OR) and prevalence ratios (PR) were calculated from country totals of HIV and HCV antibody status and self-reported life-time incarceration history, and pooled using meta-analyses. Country-specific and overall population attributable risk (PAR) were estimated using pooled PR.ResultsUnivariable HIV OR ranged between 0.73 and 6.37 (median 2.1; pooled OR 1.92; 95% CI 1.52-2.42). Pooled PR was 1.66 (95% CI 1.38-1.98), giving a PAR of 25.8% (95% CI 16.7-34.0). Univariable anti-HCV OR ranged between 1.06 and 5.04 (median 2.70; pooled OR 2.51; 95% CI 2.17-2.91). Pooled PR was 1.42 (95% CI 1.28-1.58) and PAR 16.7% (95% CI 11.8-21.7). Subgroup analyses showed differences in the OR for HCV by geographical region, with lower estimates in southern Europe.ConclusionIn univariable analysis, a history of incarceration was associated with positive HIV and HCV serostatus among PWID in Europe. Applying the precautionary principle would suggest finding alternatives to incarceration of PWID and strengthening health and social services in prison and after release ('throughcare').BACKGROUND The reduction of Kenya´s TB burden requires improving resource allocation both to and within the National TB, Leprosy and Lung Disease Program (NTLD-P). We aimed to estimate the unit costs of TB services for budgeting by NTLD-P, and allocative efficiency analyses for future National Strategic Plan (NSP) costing.METHODS We estimated costs of all TB interventions in a sample of 20 public and private health facilities from eight counties. We calculated national-level unit costs from a health provider´s perspective using bottom-up (BU) and top-down (TD) approaches for the financial year 2017-2018 using Microsoft Excel and STATA v16.RESULTS The mean unit cost for passive case-finding (PCF) was respectively US$38 and US$60 using the BU and TD approaches. The unit BU and TD costs of a 6-month first-line treatment (FLT) course, including monitoring tests, was respectively US$135 and US$160, while those for adult drug-resistant TB (DR-TB) treatment was respectively US$3,230.28 and US$3,926.52 for the 9-month short regimen. Intervention costs highlighted variations between BU and TD approaches. Overall, TD costs were higher than BU, as these are able to capture more costs due to inefficiency (breaks/downtime/leave).CONCLUSION The activity-based TB unit costs form a comprehensive cost database, and the costing process has built-in capacity within the NTLD-P and international TB research networks, which will inform future TB budgeting processes.BACKGROUND Patient-centred care along with optimal financing of inpatient and outpatient services are the main priorities of the Georgia National TB Programme (NTP). This paper presents TB diagnostics and treatment unit cost, their comparison with NTP tariffs and how the study findings informed TB financing policy.METHODS Top-down (TD) and bottom-up (BU) mean unit costs for TB interventions by episode of care were calculated. TD costs were compared with NTP tariffs, and variations in these and the unit costs cost composition between public and private facilities was assessed.RESULTS Outpatient interventions costs exceeded NTP tariffs. selleck products Unit costs in private facilities were higher compared with public providers. There was very little difference between per-day costs for drug-susceptible treatment and NTP tariffs in case of inpatient services. Treatment day financing exceeded actual costs in the capital (public facility) for drug-resistant TB, and this was lower in the regions.CONCLUSION Use of reliable unit costs for TB services at policy discussions led to a shift from per-day payment to a diagnosis-related group model in TB inpatient financing in 2020. A next step will be informing policy decisions on outpatient TB care financing to reduce the existing gap between funding and costs.BACKGROUND There is a dearth of economic analysis required to support increased investment in TB in India. This study estimates the costs of TB services from a health systems´ perspective to facilitate the efficient allocation of resources by India´s National Tuberculosis Elimination Programme.METHODS Data were collected from a multi-stage, stratified random sample of 20 facilities delivering TB services in two purposively selected states in India as per Global Health Cost Consortium standards and using Value TB Data Collection Tool. Unit costs were estimated using the top-down (TD) and bottom-up (BU) methodology and are reported in 2018 US dollars.RESULTS Cost of delivering 50 types of TB services and four interventions varied according to costing method. Key services included sputum smear microscopy, Xpert® MTB/RIF and X-ray with an average BU costs of respectively US$2.45, US$17.36 and US$2.85. Average BU cost for bacille Calmette-Guérin vaccination, passive case-finding, TB prevention in children under 5 years using isoniazid and first-line drug treatment in new pulmonary and extrapulmonary TB cases was respectively US$0.76, US$1.62, US$2.41, US$103 and US$98.CONCLUSION The unit cost of TB services and outputs are now available to support investment decisions, as diagnosis algorithms are reviewed and prevention or treatment for TB are expanded or updated in India.OBJECTIVE To develop a population pharmacokinetic (PK) model for bedaquiline (BDQ) to describe the concentration-time data from patients with multidrug-resistant TB (MDR-TB) in China.METHOD A total of 306 PK observations from 69 patients were used in a non-linear, mixed-effects modelling (NONMEM) approach. BDQ PK can be adequately described by a three-compartment model with a transit absorption model. The impact of baseline covariates, including age, sex, height, weight, alanine aminotransferase (ALT), aspartate aminotransferase (AST), apolipoprotein (ALP), total bilirubin (TBIL), direct bilirubin (DBIL), creatinine (CR), potassium (K+), calcium (Ca++) and magnesium (Mg++) on the oral clearance (CL/F) of BDQ were investigated.RESULTS In final population PK model, no significant covariates were found in the population PK model for BDQ. The population PK parameter estimate values for oral clearance (CL/F); CL/F between central compartment and peripheral compartment (Q1/F, Q2/F); peripheral volume of distribution (Vp1/F, VP2/F) were respectively 1.50 L/h (95% CI 1.07-1.93), 2.54 L/h (95% CI 1.67-3.41), 1,250 L (95% CI 616.9-1883.1), 2.00 L/h (95% CI 1.10-2.90) and 4,960 L (95% CI 1647.6-8272.4). Inter-individual variability on CL/F was 65.0%.CONCLUSION This is the first study to establish a population PK model for BDQ in Chinese patients with MDR-TB. The final model adequately described the data and had good simulation characteristics. Despite some limitations, the final population PK model was stable with good accuracy of parameter estimation.BACKGROUND Tests that identify individuals at greatest risk of TB will allow more efficient targeting of preventive therapy. The WHO target product profile for such tests defines optimal sensitivity of 90% and minimum sensitivity of 75% for predicting incident TB. The CORTIS (Correlate of Risk Targeted Intervention Study) evaluated a blood transcriptomic signature (RISK11) for predicting incident TB in a high transmission setting. RISK11 is able to predict TB disease progression but optimal prognostic performance was limited to a 6-month horizon.METHODS Using a mathematical model, we estimated how subsequent Mycobacterium tuberculosis (MTB) infection may have contributed to the decline in sensitivity of RISK11. We calculated the effect at different RISK11 thresholds (60% and 26%) and for different assumptions about the risk of MTB infection.RESULTS Modelled sensitivity over 15 months, excluding new infection, was 28.7% (95% CI 12.3-74.1) compared to 25.0% (95% CI 12.7-45.9) observed in the trial. Modelled sensitivity exceeded the minimum criteria (>75%) over a 9-month horizon at the 60% threshold and over 12 months at the 26% threshold.CONCLUSIONS The effect of new infection on prognostic signature performance is likely to be small. Signatures such as RISK11 may be most useful in individuals, such as household contacts, where probable time of infection is known.BACKGROUND Distinguishing TB relapse from re-infection is important from a clinical perspective to document transmission patterns. We investigated isolates from patients classified as relapse to understand if these were true relapses or re-infections. We also investigated shifts in drug susceptibility patterns to distinguish acquired drug resistance from re-infection with resistant strains.METHODS Isolates from pulmonary TB patients from 2009 to 2017 were analysed using whole-genome sequencing (WGS).RESULTS Of 11 patients reported as relapses, WGS results indicated that 4 were true relapses (single nucleotide polymorphism difference ≤5), 3 were re-infections with new strains, 3 were both relapse and re-infection and 1 was a suspected relapse who was later categorised as treatment failure based on sequencing. Of the 9 patients who went from a fully susceptible to a resistant profile, WGS showed that none had acquired drug resistance; 6 were re-infected with new resistant strains, 1 was probably infected by at least two different genotype strains and 2 were phenotypically misclassified.CONCLUSIONS WGS was shown to distinguish between relapse and re-infection in an unbiased way. The use of WGS minimises the risk of false classification of treatment failure instead of re-infection. Furthermore, our study showed that strains without major genetic differences can cause re-infection.BACKGROUND Treatment of TB is often extended beyond the recommended duration. The aim of this study was to assess prevalence of extended treatment and to identify associated risk factors. We also aimed to determine the frequency and type of adverse drug reactions (ADR) experienced by this study population.METHODS We performed a retrospective cohort study of all patients treated for active TB at Christchurch Hospital, Christchurch, New Zealand, between 1 March 2012 and 31 December 2018. Data for 192 patients were collected on patient demographics, disease characteristics and treatment characteristics, including planned and actual duration of treatment and ADRs.RESULTS Of 192 patients, 35 (18.2%) had treatment extended, and 85 (46.5%) of 183 with fully drug-susceptible TB received ≥9 months treatment. The most common reasons for extension were persistent or extensive disease and ADR. Extended treatment duration was not associated with any patient or disease characteristics. We found 35 (18.2%) patients experienced at least one ADR. The most common ADRs were hepatitis, rash and peripheral neuropathy.CONCLUSION TB treatment extension beyond WHO guidelines is common. Further research is needed to guide management of those with slow response to treatment. Methods for early detection of ADR, systems to improve adherence and therapeutic drug monitoring are potentially useful strategies.