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IntroductionElevated IL‐6 levels have been linked to increased risk of cardiovascular disease (CVD), cancer and death. Compared to the general population, treated HIV+ persons have 50–100% higher IL‐6 levels, but few data on the determinants of IL‐6 levels during HIV infection currently exist.Material and MethodsParticipants in three international HIV trials (SMART, ESPRIT and SILCAAT) with IL‐6 plasma levels measured at baseline were included (N=9864). Factors independently associated with log2‐transformed IL‐6 level were identified by multivariate linear regression; exponentiated estimates corresponding to fold differences (FDs) in IL‐6 were calculated. Demographics (age, gender, race, BMI) and HIV‐specific variables (nadir and entry CD4 counts, HIV‐RNA, use of different ART regimens) were investigated in all three trials. In SMART (N=4498), smoking, comorbidities (CVD, diabetes, hepatitis B/C [HBV/HCV]), HDL‐cholesterol, renal function (eGFR) and educational level were also assessed.ResultsDemographics associated with higher IL‐6 were older age (FD [95% CI]: 1.09 [1.08–1.11] per 10 yr) and higher BMI (1.02 [1.01–1.04] per 5 kg/m2), whereas black race was associated with reduced IL‐6 (0.96 [0.93–0.99]). As for HIV variables, patients not receiving ART (1.36 [1.29–1.43]) and with higher HIV‐RNA (1.24 [1.01–1.52] for >100,000 vs. ≤500 copies/mL) had increased IL‐6. Participants taking protease inhibitors (PI) had higher IL‐6 (1.14[1.09–1.19]). Higher nadir CD4 count (0.98 [0.97–0.99]/100 cells/µL) was related to lower IL‐6. All evaluated comorbidities were related to higher IL‐6; FDs in IL‐6 were 1.08 [1.04–1.12] for smoking, 1.12 [1.02–1.24] for CVD, 1.07 [1.00–1.16] for diabetes and 1.12 [1.02–1.24] for HBV (1.15 [1.02–1.30]) and 1.53 [1.45–1.62] for HCV. IL‐6 increased with decreasing eGFR (0.98 [0.97–1.00]/10 mL/min) and HDL‐cholesterol (0.98 [0.96–0.99]/10 mg/mL). Lower education was related to higher IL‐6 (1.09 [1.03–1.15] for high school vs. bachelor's degree).ConclusionsHigher IL‐6 levels were associated with older age and non‐black race, higher BMI and lower HDL‐cholesterol, ongoing HIV replication, low nadir CD4 counts, comorbidities and decreased renal function. This suggests that there are multiple causes of inflammation in treated HIV infection. A possible contribution from PI use was also observed. Contribution from inflammation to explain variation in clinical outcomes for these factors should be investigated.

IntroductionSeveral resistance mutations have been shown to affect viral fitness, and the presence of certain mutations might result in clinical benefit for patients kept on a virologically failing regimen due to an exhaustion of drug options. We sought to quantify the effect of resistance mutations on CD4 slopes in patients undergoing episodes of viral failure.Materials and MethodsPatients from the EuroSIDA and UK CHIC cohorts undergoing at least one episode of virological failure (>3 consecutive RNA measurements >500 on ART) with at least three CD4 measurements and a resistance test during the episode were included. Mutations were identified using the IAS‐US (2013) list, and were presumed to be present from detection until the end of an episode. Multivariable linear mixed models with a random intercept and slope adjusted for age, baseline CD4 count, hepatitis C, drug type, RNA (log‐scale), risk group and subtype were used to estimate CD4 slopes. Individual mutations with a population prevalence of >10% were tested for their effect on the CD4 slope.ResultsA total of 2731 patients experiencing a median of 1 (range 1–4) episodes were included in this analysis. The prevalence of any resistance per episode was 88.4%; NNRTI resistance was most common (78.5%). Overall, CD4 counts declined by 17.1 (−19.7; −14.5) cells per year; this decline was less marked with partial viral suppression (current HIV RNA more than 1.5 log below the setpoint; p=0.01). In multivariable models adjusting for viral load, CD4 decline was slower during episodes with detected resistance compared to episodes without detected resistance (21.0 cells/year less, 95% CI 11.75–30.31, p<0.001). Among those with more than one resistance mutation, there was only weak evidence that class‐specific mutations had any effect on the CD4 slope (Table 1). The effects of individual mutations (incl. M184V) were explored, but none were significantly associated with the CD4 slope; for these comparisons, a Bonferroni‐corrected p‐value level was 0.003.ConclusionsIn our study population, detected resistance was associated with slightly less steep CD4 declines. This may be due to a biological effect of resistance on CD4 slopes, or other unmeasured factors such as poor adherence among individuals without resistance. Among individuals with detected drug resistance, we found no evidence suggesting that the presence of individual mutations was associated with beneficial CD4 slope changes.

AbstractIntroductionThe 90‐90‐90 targets set by the United Nations aspire to 73% of people living with HIV (PLHIV) being virally suppressed by 2020. Using the HIV Synthesis Model, we aim to mimic the epidemic in Zimbabwe and make projections to assess whether Zimbabwe is on track to meet the 90‐90‐90 targets and assess whether recently proposed UNAIDS HIV transition metrics are likely to be met.MethodsWe used an approximate Bayesian computation approach to identify model parameter values which result in model outputs consistent with observed data, evaluated using a calibration score. These parameter values were then used to make projections to 2020 to compare with the 90‐90‐90 targets and other key indicators. We also calculated HIV transition metrics proposed by UNAIDS (percentage reduction in new HIV infections and AIDS‐related mortality from 2010 to 2020, absolute rate of new infections and AIDS‐related mortality, incidence–mortality ratio and incidence–prevalence ratios).ResultsAfter calibration, there was general agreement between modelled and observed data. The median predicted outcomes in 2020 were: proportion of PLHIV (aged 15 to 65) diagnosed 0.91 (90% uncertainty range 0.87, 0.94) (0.84 men, 0.95 women); of those diagnosed, proportion on treatment 0.92 (0.90, 0.93); of those receiving treatment, proportion with viral suppression 0.86 (0.81, 0.91). This results in 72% of PLHIV having viral suppression in 2020. We estimated a percentage reduction of 36.5% (13.7% increase to 67.4% reduction) in new infections from 2010 to 2020, and of 30.4% (9.7% increase to 56.6% reduction) in AIDS‐related mortality (UNAIDS target 75%). The modelled absolute rates of HIV incidence and AIDS‐related mortality in 2020 were 5.48 (2.26, 9.24) and 1.93 (1.31, 2.71) per 1000 person‐years respectively. The modelled incidence–mortality ratio and incidence–prevalence ratios in 2020 were 1.05 (0.46, 1.66) and 0.009 (0.004, 0.013) respectively.ConclusionsOur model was able to produce outputs that are simultaneously consistent with an array of observed data and predicted that while the 90‐90‐90 targets are within reach in Zimbabwe, increased efforts are required in diagnosing men in particular. Calculation of the HIV transition metrics suggest increased efforts are needed to bring the HIV epidemic under control.

AbstractIntroductionUNAIDS' goal of ending AIDS by 2030 is unreachable without better targeting of testing, prevention and care. Female sex workers (FSW) in Zimbabwe are at high risk of HIV acquisition and transmission. Here, we report on collated programme and research data from Zimbabwe's national sex work programme. We also assess the potential for wider population impact of FSW programmes by modelling the impact on HIV incidence of eliminating transmission through FSW (i.e. calculate the population attributable fraction of incidence attributable to sex work).MethodsDescriptive analyses of individual‐level programme data collected from FSW between 2009 and June 2018 are triangulated with data collected through 37 respondent driven sampling surveys from 19 sites in Zimbabwe 2011 to 2017. We describe programme coverage, uptake, retention and patterns of sex work behaviour and gaps in service provision. An individual‐level stochastic simulation model is used to reconstruct the epidemic and then the incidence compared with the counter‐factual trend in incidence from 2010 had transmission through sex work been eliminated from that date.ResultsSisters has reached >67,000 FSW since 2009, increasing attendance as number of sites, programme staff and peer educators were increased. Over 57% of all FSW estimated to be working in Zimbabwe in 2017 (n = 40,000) attended the programme at least once. The proportion of young FSW reached has increased with introduction of the "Young Sisters programme." There are no clear differences in pattern of sex work across settings. Almost all women report condom use with clients at last sex (95%); however, consistent condom use with clients in the last month varies from 52% to 95% by site. Knowledge of HIV‐positive status has increased from 48 to 78% between 2011 and 2016, as has prevalence of ART use among diagnosed women (29 to 67%). Although subject to uncertainty, modelling suggests that 70% (90% range: 32%, 93%) of all new infections in Zimbabwe from 2010 are directly or indirectly attributable to transmission via sex work.ConclusionsIt is feasible to increase coverage and impact of sex work programming through community‐led scale‐up of evidence‐based interventions. Eliminating transmission through commercial sex would likely have a substantial impact on new infections occurring more widely across Zimbabwe.

AbstractIntroductionSuboptimal ART adherence, despite HIV viral suppression, has been associated with chronic residual inflammation. Whether this association extends to individuals who initiate ART during early HIV infection remains unknown, which was the objective of this study.MethodsPlasma levels of interleukin‐6 (IL‐6), high‐sensitivity C‐reactive protein, serum amyloid A protein (SAA), IL‐27, soluble intercellular adhesion molecule‐1, soluble vascular adhesion molecule‐1, D‐dimer and the CD4+/CD8+ T‐cell ratio, were analysed at baseline and eight months after ART initiation in treatment‐naïve participants with HIV and CD4+ T‐cells >500 cells/mm3 enrolled in the immediate arm of START. Adherence was assessed by seven‐day self‐report. Multivariable linear regression was utilized to analyse the association between ART adherence and each biomarker at the eight‐month visit in participants who achieved virologic suppression (<50 copies/mL).ResultsWe evaluated 1627 participants (422 female) who achieved virologic suppression at the eight‐month visit in the period between 2009 and 2013. Median (IQR) CD4+ T‐cell count before ART was 651 (585, 769) cells/mm3. Incomplete adherence was reported in 109 (7%) participants at the eight month visit. After adjusting for covariates, plasma IL‐6 was 1.12 (95% CI, 1.00 to 1.26; p = 0.047) fold higher in participants reporting incomplete versus 100% adherence. A similar association for SAA was observed in an exploratory analysis (1.29 (95% CI 1.04 to 1.60); p = 0.02). No significant differences in other biomarkers were observed.ConclusionsIncomplete ART adherence was associated with higher IL‐6 levels in individuals who achieved virologic suppression early after ART initiation in START. A potential similar association for SAA requires confirmation. These findings suggest a role for identifying strategies to maximize ART adherence even during virologic suppression. ClinicalTrials.gov number: NCT00867048.

AbstractIntroductionAs prevalence of undiagnosed HIV declines, it is unclear whether testing programmes will be cost‐effective. To guide their HIV testing programmes, countries require appropriate metrics that can be measured. The cost‐per‐diagnosis is potentially a useful metric.MethodsWe simulated a series of setting‐scenarios for adult HIV epidemics and ART programmes typical of settings in southern Africa using an individual‐based model and projected forward from 2018 under two policies: (i) a minimum package of "core" testing (i.e. testing in pregnant women, for diagnosis of symptoms, in sex workers, and in men coming forward for circumcision) is conducted, and (ii) core‐testing as above plus additional testing beyond this ("additional‐testing"), for which we specify different rates of testing and various degrees to which those with HIV are more likely to test than those without HIV. We also considered a plausible range of unit test costs. The aim was to assess the relationship between cost‐per‐diagnosis and the incremental cost‐effectiveness ratio (ICER) of the additional‐testing policy. The discount rate used in the base case was 3% per annum (costs in 2018 U.S. dollars).ResultsThere was a strong graded relationship between the cost‐per‐diagnosis and the ICER. Overall, the ICER was below $500 per‐DALY‐averted (the cost‐effectiveness threshold used in primary analysis) so long as the cost‐per‐diagnosis was below $315. This threshold cost‐per‐diagnosis was similar according to epidemic and programmatic features including the prevalence of undiagnosed HIV, the HIV incidence and a measure of HIV programme quality (the proportion of HIV diagnosed people having a viral load <1000 copies/mL). However, restricting to women, additional‐testing did not appear cost‐effective even at a cost‐per‐diagnosis of below $50, while restricting to men additional‐testing was cost‐effective up to a cost‐per‐diagnosis of $585. The threshold cost per diagnosis for testing in men to be cost‐effective fell to $256 when the cost‐effectiveness threshold was $300 instead of $500, and to $81 when considering a discount rate of 10% per annum.ConclusionsFor testing programmes in low‐income settings in southern African there is an extremely strong relationship between the cost‐per‐diagnosis and the cost‐per‐DALY averted, indicating that the cost‐per‐diagnosis can be used to monitor the cost‐effectiveness of testing programmes.