The roles of the general practitioner and sexual health centre in HIV testing: comparative insights and impact on HIV incidence rates in the Rotterdam area, the Netherlands - a cross-sectional population-based study.

BACKGROUND: Access to HIV testing is crucial for detection, linkage to treatment, and prevention. In less urbanised areas, reliance on general practitioners (GPs) for HIV testing is probable, as sexual health centres (SHC) are mostly located within urbanised areas. Limited insight into individuals undergoing HIV testing stems from sparse standard registration of demographics at GPs. This cross-sectional study aims (1) to assess and compare HIV testing at the GP and SHC, and (2) to assess population- and provider-specific HIV incidence. METHODS: Individual HIV testing data of GPs and SHC were linked to population register data (aged ≥ 15 years, Rotterdam area, 2015-2019). We reported the proportion HIV tested, and compared GP and SHC testing rates with negative binomial generalised additive models. Data on new HIV diagnoses (2015-2019) from the Dutch HIV Monitoring Foundation relative to the population were used to assess HIV incidence. RESULTS: The overall proportion HIV tested was 1.14% for all residents, ranging from 0.41% for ≥ 40-year-olds to 4.70% for Antilleans. The GP testing rate was generally higher than the SHC testing rate with an overall rate ratio (RR) of 1.61 (95% CI: 1.56-1.65), but not for 15-24-year-olds (RR: 0.81, 95% CI: 0.74-0.88). Large differences in HIV testing rate (1.36 to 39.47 per 1,000 residents) and GP-SHC ratio (RR: 0.23 to 7.24) by geographical area were observed. The GPs' contribution in HIV testing was greater for GP in areas further away from the SHC. In general, population groups that are relatively often tested are also the groups with most diagnoses and highest incidence (e.g., men who have sex with men, non-western). The overall incidence was 10.55 per 100,000 residents, varying from 3.09 for heterosexual men/women to 24.04 for 25-29-year-olds. CONCLUSIONS: GPs have a pivotal role in HIV testing in less urbanised areas further away from the SHC, and among some population groups. A relatively high incidence often follows relatively high testing rates. Opportunities to improve HIV testing have been found for migrants, lower-educated individuals, in areas less urbanised areas and further away from GP/SHC. Strategies include additional targeted testing, via for example SHC branch locations and outreach activities.

Decreased Time to Viral Suppression After Implementation of Targeted Testing and Immediate Initiation of Treatment of Acute Human Immunodeficiency Virus Infection Among Men Who Have Sex With Men in Amsterdam.

BACKGROUND: Men who have sex with men (MSM) with acute human immunodeficiency virus (HIV) infection (AHI) are a key source of new infections. To curb transmission, we implemented a strategy for rapid AHI diagnosis and immediate initiation of combination antiretroviral therapy (cART) in Amsterdam MSM. We assessed its effectiveness in diagnosing AHI and decreasing the time to viral suppression. METHODS: We included 63 278 HIV testing visits in 2008-2017, during which 1013 MSM were diagnosed. Standard of care (SOC) included HIV diagnosis confirmation in < 1 week and cART initiation in < 1 month. The AHI strategy comprised same-visit diagnosis confirmation and immediate cART. Time from diagnosis to viral suppression was assessed for 3 cART initiation periods: (1) 2008-2011: cART initiation if CD4 < 500 cells/µL (SOC); (2) January 2012-July 2015: cART initiation if CD4 < 500 cells/µL, or if AHI or early HIV infection (SOC); and (3a) August 2015-June 2017: universal cART initiation (SOC) or (3b) August 2015-June 2017 (the AHI strategy). RESULTS: Before implementation of the AHI strategy, the proportion of AHI among HIV diagnoses was 0.6% (5/876); after implementation this was 11.0% (15/137). Median time (in days) to viral suppression during periods 1, 2, 3a, and 3b was 584 (interquartile range [IQR], 267-1065), 230 (IQR, 132-480), 95 (IQR, 63-136), and 55 (IQR, 31-72), respectively (P < .001). CONCLUSIONS: Implementing the AHI strategy was successful in diagnosing AHI and significantly decreasing the time between HIV diagnosis and viral suppression.

2021 update to HIV-TRePS: a highly flexible and accurate system for the prediction of treatment response from incomplete baseline information in different healthcare settings.

OBJECTIVES: With the goal of facilitating the use of HIV-TRePS to optimize therapy in settings with limited healthcare resources, we aimed to develop computational models to predict treatment responses accurately in the absence of commonly used baseline data. METHODS: Twelve sets of random forest models were trained using very large, global datasets to predict either the probability of virological response (classifier models) or the absolute change in viral load in response to a new regimen (absolute models) following virological failure. Two 'standard' models were developed with all baseline variables present and 10 others developed without HIV genotype, time on therapy, CD4 count or any combination of the above. RESULTS: The standard classifier models achieved an AUC of 0.89 in cross-validation and independent testing. Models with missing variables achieved AUC values of 0.78-0.90. The standard absolute models made predictions that correlated significantly with observed changes in viral load with a mean absolute error of 0.65 log10 copies HIV RNA/mL in cross-validation and 0.69 log10 copies HIV RNA/mL in independent testing. Models with missing variables achieved values of 0.65-0.75 log10 copies HIV RNA/mL. All models identified alternative regimens that were predicted to be effective for the vast majority of cases where the new regimen prescribed in the clinic failed. All models were significantly better predictors of treatment response than genotyping with rules-based interpretation. CONCLUSIONS: These latest models that predict treatment responses accurately, even when a number of baseline variables are not available, are a major advance with greatly enhanced potential benefit, particularly in resource-limited settings. The only obstacle to realizing this potential is the willingness of healthcare professions to use the system.

Understanding Reasons for HIV Late Diagnosis: A Qualitative Study Among HIV-Positive Individuals in Amsterdam, The Netherlands.

Since the introduction of effective anti-retroviral therapy, early diagnosis and treatment of HIV have become increasingly important from individual and public health perspectives. People who are diagnosed with a CD4 count below 350 cells/µL blood are today considered to be "late" diagnoses. In an effort to understand the reasons for late diagnosis, we conducted in-depth interviews (n = 14) in Amsterdam, the Netherlands. Two main factors were identified: psychosocial factors and health-system factors. Psychosocial factors relate to people's personal relationship with health professionals, low risk perception, fear related to the outcome of testing, and trauma from observed past experiences of living with HIV. Health-system factors relate to institutional barriers and missed opportunities during client-provider interactions. We conclude that in order to mitigate late diagnosis, the social and institutional context within which HIV testing is conducted should be addressed.

RESUMEN: Desde la introducción de la terapia antirretroviral eficaz, el diagnóstico temprano y el tratamiento del VIH ha aumentado en importancia desde las perspectivas individuales y de salud pública. Personas que son diagnosticadas con VIH y que tienen un conteo de CD4 menor de 350 células/µL de sangre, se consideran de diagnóstico "tardío". En un esfuerzo por comprender las razones de este diagnóstico tardío del VIH, realizamos entrevistas en profundidad (n = 14) en Amsterdam, Países Bajos. Se identificaron dos factores principales: factores psicosociales y factores relacionados con el sistema de salud. Los factores psicosociales incluyen la relación entre el paciente y los profesionales de la salud, la baja percepción del riesgo, el miedo relacionado con el resultado de la prueba de VIH y el trauma luego de observar experiencias pasadas de personas que padecen VIH. Los factores relacionados con el sistema de salud incluyen las barreras institucionales y las oportunidades perdidas durante las interacciones entre el cliente y el proveedor de salud. Concluimos que, para mitigar el diagnóstico tardío, se deben abordar los contextos sociales e institucionales dentro de los cuales se realiza la prueba de VIH.

Human Immunodeficiency Virus Continuum of Care in 11 European Union Countries at the End of 2016 Overall and by Key Population: Have We Made Progress?

BACKGROUND: High uptake of antiretroviral treatment (ART) is essential to reduce human immunodeficiency virus (HIV) transmission and related mortality; however, gaps in care exist. We aimed to construct the continuum of HIV care (CoC) in 2016 in 11 European Union (EU) countries, overall and by key population and sex. To estimate progress toward the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, we compared 2016 to 2013 estimates for the same countries, representing 73% of the population in the region. METHODS: A CoC with the following 4 stages was constructed: number of people living with HIV (PLHIV); proportion of PLHIV diagnosed; proportion of those diagnosed who ever initiated ART; and proportion of those ever treated who achieved viral suppression at their last visit. RESULTS: We estimated that 87% of PLHIV were diagnosed; 92% of those diagnosed had ever initiated ART; and 91% of those ever on ART, or 73% of all PLHIV, were virally suppressed. Corresponding figures for men having sex with men were: 86%, 93%, 93%, 74%; for people who inject drugs: 94%, 88%, 85%, 70%; and for heterosexuals: 86%, 92%, 91%, 72%. The proportion suppressed of all PLHIV ranged from 59% to 86% across countries. CONCLUSIONS: The EU is close to the 90-90-90 target and achieved the UNAIDS target of 73% of all PLHIV virally suppressed, significant progress since 2013 when 60% of all PLHIV were virally suppressed. Strengthening of testing programs and treatment support, along with prevention interventions, are needed to achieve HIV epidemic control.

Impact of frequent testing on the transmission of HIV and N. gonorrhoeae among men who have sex with men: a mathematical modelling study.

OBJECTIVES: To investigate the impact and efficiency of combined testing for HIV and other STIs on HIV and STI transmission among men who have sex with men (MSM) and to assess what subgroups of MSM should be targeted for frequent testing. METHODS: We developed an agent-based transmission model that simulates infection with HIV or Neisseria gonorrhoeae (NG) among MSM. We examined scenarios with increased percentages of MSM getting tested six monthly, among all MSM or only specific subgroups of MSM (defined according to recent gonorrhoea, number of partners and engagement in condomless anal intercourse (CAI)) and scenarios with reduced intervals between HIV/STI tests. RESULTS: The most efficient strategies were those with increased percentage of MSM getting tested every 6 months among MSM with a recent gonorrhoea diagnosis; or among MSM who had CAI and ≥10 partners; or MSM who had ≥10 partners. Over 10 years, these strategies resulted in 387-718 averted HIV infections and required 29-164 additional HIV tests per averted HIV infection or one to seven additional gonorrhoea tests per averted NG infection. The most effective strategy in reducing HIV transmission was the one where the intervals between tests were reduced by half, followed by the strategy with increased percentage of MSM getting tested every 6 months among all MSM. Over 10 years, these strategies resulted in 1362 and 1319 averted HIV infections, but required 663 and 584 additional HIV tests per averted HIV infection, respectively. CONCLUSIONS: Targeting MSM with recent gonorrhoea diagnosis or MSM with many partners is efficient in terms of HIV/STI tests needed to prevent new HIV or NG infections. Major reductions in HIV incidence can be achieved with consistent HIV/STI testing every 6 months among larger groups, including low-risk MSM. To impede HIV transmission, frequent testing should be combined with other prevention measures.

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%-43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical "Brownian motion" model and another model ("Ornstein-Uhlenbeck") that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%-43%) is consistent with other studies based on regression of viral load in donor-recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation.

Correction: Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

[This corrects the article DOI: 10.1371/journal.pbio.2001855.].

Monitoring progress towards the first UNAIDS 90-90-90 target in key populations living with HIV in Norway.

BACKGROUND: In line with the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, Norway aims for at least 90% of people living with HIV (PLHIV) to know their HIV-status. We produced current estimates of the number of PLHIV and undiagnosed population in Norway, overall and for six key subpopulations: Norwegian-born men who have sex with men (MSM), migrant MSM, Norwegian-born heterosexuals, migrant Sub-Saharan Africa (SSA)-born heterosexuals, migrant non-SSA-born heterosexuals and people who inject drugs. METHODS: We used the European Centre for Disease Prevention and Control (ECDC) HIV Modelling Tool on Norwegian HIV surveillance data through 2018 to estimate incidence, time from infection to diagnosis, PLHIV, and the number and proportion undiagnosed. As surveillance data on CD4 count at diagnosis were not collected in Norway, we ran two models; using default model CD4 assumptions, or a proxy for CD4 distribution based on Danish national surveillance data. We also generated alternative overall PLHIV estimates using the Spectrum AIDS Impact Model, to compare with those obtained from the ECDC tool. RESULTS: Estimates of the overall number of PLHIV in 2018 using different modelling approaches aligned at approximately 5000. In both ECDC models, the overall number undiagnosed decreased continuously from 2008. The proportion undiagnosed in 2018 was lower using default model CD4 assumptions (7.1% [95%CI: 5.3-8.9%]), than the Danish CD4 proxy (10.2% [8.3-12.1%]). This difference was driven by results for heterosexual migrants. Estimates for Norwegian-born MSM, migrant MSM and Norwegian-born heterosexuals were similar in both models. In these three subpopulations, incidence in 2018 was < 30 new infections, and the number undiagnosed had decreased in recent years. Norwegian-born MSM had the lowest estimated number of undiagnosed infections (45 [30-75], using default CD4 assumptions) and undiagnosed fraction (3.6% [2.4-5.7%], using default CD4 assumptions) in 2018. CONCLUSIONS: Results allow cautious confidence in concluding that Norway has achieved the first UNAIDS 90-90-90 target, and clearly highlight the success of prevention strategies among MSM. Estimates for subpopulations strongly influenced by migration remain less clear, and future modelling should appropriately account for all-cause mortality and out-migration, and adjust for time of in-migration.

Effect Estimates in Randomized Trials and Observational Studies: Comparing Apples With Apples.

Effect estimates from randomized trials and observational studies might not be directly comparable because of differences in study design, other than randomization, and in data analysis. We propose a 3-step procedure to facilitate meaningful comparisons of effect estimates from randomized trials and observational studies: 1) harmonization of the study protocols (eligibility criteria, treatment strategies, outcome, start and end of follow-up, causal contrast) so that the studies target the same causal effect, 2) harmonization of the data analysis to estimate the causal effect, and 3) sensitivity analyses to investigate the impact of discrepancies that could not be accounted for in the harmonization process. To illustrate our approach, we compared estimates of the effect of immediate with deferred initiation of antiretroviral therapy in individuals positive for the human immunodeficiency virus from the Strategic Timing of Antiretroviral Therapy (START) randomized trial and the observational HIV-CAUSAL Collaboration.

Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.

Decisions about when to start or switch a therapy often depend on the frequency with which individuals are monitored or tested. For example, the optimal time to switch antiretroviral therapy depends on the frequency with which HIV-positive individuals have HIV RNA measured. This paper describes an approach to use observational data for the comparison of joint monitoring and treatment strategies and applies the method to a clinically relevant question in HIV research: when can monitoring frequency be decreased and when should individuals switch from a first-line treatment regimen to a new regimen? We outline the target trial that would compare the dynamic strategies of interest and then describe how to emulate it using data from HIV-positive individuals included in the HIV-CAUSAL Collaboration and the Centers for AIDS Research Network of Integrated Clinical Systems. When, as in our example, few individuals follow the dynamic strategies of interest over long periods of follow-up, we describe how to leverage an additional assumption: no direct effect of monitoring on the outcome of interest. We compare our results with and without the "no direct effect" assumption. We found little differences on survival and AIDS-free survival between strategies where monitoring frequency was decreased at a CD4 threshold of 350 cells/µl compared with 500 cells/µl and where treatment was switched at an HIV-RNA threshold of 1000 copies/ml compared with 200 copies/ml. The "no direct effect" assumption resulted in efficiency improvements for the risk difference estimates ranging from an 7- to 53-fold increase in the effective sample size.

Disparities in access to and use of HIV-related health services in the Netherlands by migrant status and sexual orientation: a cross-sectional study among people recently diagnosed with HIV infection.

BACKGROUND: Migrants often face barriers to accessing healthcare. We examined disparities in access to and use of HIV-related health services between migrant and non-migrant people recently diagnosed with HIV living in the Netherlands, taken into account sexual orientation. Also, we examined differences in experiences in living with HIV between these groups. METHODS: We used a questionnaire and clinical data collected between July 2013 and June 2015 among migrant and non-migrant participants of the European cross-sectional aMASE (Advancing Migrant Access to health Services in Europe) study in the Netherlands. Using univariable logistic regression analyses, we compared outcomes on between migrants and non-migrants, stratified by sexual orientation (with non-migrant men having sex with men [MSM] as the reference group). RESULTS: We included 77 migrant MSM, 115 non-migrant MSM, 21 migrant heterosexual men, 14 non-migrant heterosexual men and 20 migrant women. In univariable analyses, all heterosexual groups were less likely to ever have had an HIV-negative test before their diagnosis and were more likely to be diagnosed late than non-migrant MSM. All migrant groups were more likely to have experienced difficulties accessing general healthcare in the Netherlands and were less likely to have heard of post-exposure prophylaxis than non-migrant MSM. Migrants frequently reported uncertainty about their rights to healthcare and language barriers. Most (93%) participants visited a healthcare facility in the 2 years before HIV diagnosis but only in 41% an HIV test was discussed during that visit (no statistical difference between groups). Migrant heterosexuals were more likely to have missed appointments at their HIV clinic due to the travel costs than non-migrant MSM. Migrant MSM and women were more likely to have experienced HIV discrimination in the Netherlands than non-migrant MSM. CONCLUSION: Disparities in access to and use of HIV-related health services and experiences exist by migrant status but also by sexual orientation. Our data suggests heterosexual men and women may particularly benefit from improved access to HIV testing (e.g., through provider-initiated testing), while migrant MSM may benefit from improved access to HIV prevention interventions (e.g., pre-exposure prophylaxis).

Challenges in modelling the proportion of undiagnosed HIV infections in Sweden.

BackgroundSweden has a low HIV prevalence. However, among new HIV diagnoses in 2016, the proportion of late presenters and migrants was high (59% and 81%, respectively). This poses challenges in estimating the proportion of undiagnosed persons living with HIV (PLHIV).AimTo estimate the proportion of undiagnosed PLHIV in Sweden comparing two models with different demands on data availability and modelling expertise.MethodsAn individual-based stochastic simulation model of HIV positive populations (SSOPHIE) and the incidence method of the European Centre for Disease Prevention and Control (ECDC) HIV Modelling Tool were applied to clinical, surveillance and migration data from Sweden 1980-2016.ResultsSSOPHIE estimated that the proportion of undiagnosed PLHIV in 2013 was 26% (n = 2,100; 90% plausibility range (PR): 900-5,000) for all PLHIV, 17% (n = 600; 90% PR: 100-2,000) for men who have sex with men (MSM), 35% in male (n = 300; 90% PR: 200-700) and 34% in female (n = 400; 90% PR: 200-800) migrants from sub-Saharan Africa (SSA). The estimates for the ECDC model in 2013 were 21% (n = 2,013; 95% confidence interval (CI): 1,831-2,189) for all PLHIV, 15% (n = 369; 95% CI: 299-434) for MSM and 21% (n = 530; 95% CI: 436-632) for migrants from SSA.ConclusionsThe proportion of undiagnosed PLHIV in Sweden is uncertain. SSOPHIE estimates had wide PR. The ECDC model estimates were unreliable because migration was not accounted for. Better migration data and estimation methods are required to obtain reliable estimates of proportions of undiagnosed PLHIV in similar settings.

Piloting a surveillance system for HIV drug resistance in the European Union.

BackgroundA steady increase in HIV drug resistance (HIVDR) has been demonstrated globally in individuals initiating first-line antiretroviral therapy (ART). To support effective use of ART and prevent spread of HIVDR, monitoring is essential.AimWe piloted a surveillance system for transmitted HIVDR to assess the feasibility of implementation at the European level.MethodAll 31 countries in the European Union and European Economic Area were invited to retrospectively submit data on individuals newly diagnosed with HIV in 2015 who were tested for antiviral susceptibility before ART, either as case-based or as aggregate data. We used the Stanford HIV database algorithm to translate genetic sequences into levels of drug resistance.ResultsNine countries participated, with six reporting case-based data on 1,680 individuals and four reporting aggregated data on 1,402 cases. Sequence data were available for 1,417 cases: 14.5% of individuals (n = 244) showed resistance to at least one antiretroviral drug. In case-based surveillance, the highest levels of transmitted HIVDR were observed for non-nucleoside reverse-transcriptase inhibitors (NNRTIs) with resistance detected in 8.6% (n = 145), followed by resistance to nucleoside reverse-transcriptase inhibitors (NRTI) (5.1%; n = 85) and protease inhibitors (2.0%; n = 34).ConclusionWe conclude that standard reporting of HIVDR data was feasible in the participating countries. Legal barriers for data sharing, consensus on definitions and standardisation of interpretation algorithms should be clarified in the process of enhancing European-wide HIV surveillance with drug resistance information.

Cardiovascular Disease Prevention Policy in Human Immunodeficiency Virus: Recommendations From a Modeling Study.

Background: Cardiovascular disease (CVD) is expected to contribute a large noncommunicable disease burden among human immunodeficiency virus (HIV)-infected people. We quantify the impact of prevention interventions on annual CVD burden and costs among HIV-infected people in the Netherlands. Methods: We constructed an individual-based model of CVD in HIV-infected people using national ATHENA (AIDS Therapy Evaluation in The Netherlands) cohort data on 8791 patients on combination antiretroviral therapy (cART). The model follows patients as they age, develop CVD (by incorporating a CVD risk equation), and start cardiovascular medication. Four prevention interventions were evaluated: (1) increasing the rate of earlier HIV diagnosis and treatment; (2) avoiding use of cART with increased CVD risk; (3) smoking cessation; and (4) intensified monitoring and drug treatment of hypertension and dyslipidemia, quantifying annual number of averted CVDs and costs. Results: The model predicts that annual CVD incidence and costs will increase by 55% and 36% between 2015 and 2030. Traditional prevention interventions (ie, smoking cessation and intensified monitoring and treatment of hypertension and dyslipidemia) will avert the largest number of annual CVD cases (13.1% and 20.0%) compared with HIV-related interventions-that is, earlier HIV diagnosis and treatment and avoiding cART with increased CVD risk (0.8% and 3.7%, respectively)-as well as reduce cumulative CVD-related costs. Targeting high-risk patients could avert the majority of events and costs. Conclusions: Traditional CVD prevention interventions can maximize cardiovascular health and defray future costs, particularly if targeting high-risk patients. Quantifying additional public health benefits, beyond CVD, is likely to provide further evidence for policy development.

2018 update to the HIV-TRePS system: the development of new computational models to predict HIV treatment outcomes, with or without a genotype, with enhanced usability for low-income settings.

Objectives: Optimizing antiretroviral drug combination on an individual basis can be challenging, particularly in settings with limited access to drugs and genotypic resistance testing. Here we describe our latest computational models to predict treatment responses, with or without a genotype, and compare their predictive accuracy with that of genotyping. Methods: Random forest models were trained to predict the probability of virological response to a new therapy introduced following virological failure using up to 50 000 treatment change episodes (TCEs) without a genotype and 18 000 TCEs including genotypes. Independent data sets were used to evaluate the models. This study tested the effects on model accuracy of relaxing the baseline data timing windows, the use of a new filter to exclude probable non-adherent cases and the addition of maraviroc, tipranavir and elvitegravir to the system. Results: The no-genotype models achieved area under the receiver operator characteristic curve (AUC) values of 0.82 and 0.81 using the standard and relaxed baseline data windows, respectively. The genotype models achieved AUC values of 0.86 with the new non-adherence filter and 0.84 without. Both sets of models were significantly more accurate than genotyping with rules-based interpretation, which achieved AUC values of only 0.55-0.63, and were marginally more accurate than previous models. The models were able to identify alternative regimens that were predicted to be effective for the vast majority of cases in which the new regimen prescribed in the clinic failed. Conclusions: These latest global models predict treatment responses accurately even without a genotype and have the potential to help optimize therapy, particularly in resource-limited settings.

The Human Immunodeficiency Virus Continuum of Care in European Union Countries in 2013: Data and Challenges.

BACKGROUND.: The Joint United Nations Programme on HIV/AIDS (UNAIDS) has set a "90-90-90" target to curb the human immunodeficiency virus (HIV) epidemic by 2020, but methods used to assess whether countries have reached this target are not standardized, hindering comparisons. METHODS.: Through a collaboration formed by the European Centre for Disease Prevention and Control (ECDC) with European HIV cohorts and surveillance agencies, we constructed a standardized, 4-stage continuum of HIV care for 11 European Union countries for 2013. Stages were defined as (1) number of people living with HIV in the country by end of 2013; (2) proportion of stage 1 ever diagnosed; (3) proportion of stage 2 that ever initiated ART; and (4) proportion of stage 3 who became virally suppressed (≤200 copies/mL). Case surveillance data were used primarily to derive stages 1 (using back-calculation models) and 2, and cohort data for stages 3 and 4. RESULTS.: In 2013, 674500 people in the 11 countries were estimated to be living with HIV, ranging from 5500 to 153400 in each country. Overall HIV prevalence was 0.22% (range, 0.09%-0.36%). Overall proportions of each previous stage were 84% diagnosed, 84% on ART, and 85% virally suppressed (60% of people living with HIV). Two countries achieved ≥90% for all stages, and more than half had reached ≥90% for at least 1 stage. CONCLUSIONS.: European Union countries are nearing the 90-90-90 target. Reducing the proportion undiagnosed remains the greatest barrier to achieving this target, suggesting that further efforts are needed to improve HIV testing rates. Standardizing methods to derive comparable continuums of care remains a challenge.

CD4 cell count response to first-line combination ART in HIV-2+ patients compared with HIV-1+ patients: a multinational, multicohort European study.

Background: CD4 cell recovery following first-line combination ART (cART) is poorer in HIV-2+ than in HIV-1+ patients. Only large comparisons may allow adjustments for demographic and pretreatment plasma viral load (pVL). Methods: ART-naive HIV+ adults from two European multicohort collaborations, COHERE (HIV-1 alone) and ACHIeV2e (HIV-2 alone), were included, if they started first-line cART (without NNRTIs or fusion inhibitors) between 1997 and 2011. Patients without at least one CD4 cell count before start of cART, without a pretreatment pVL and with missing a priori-defined covariables were excluded. Evolution of CD4 cell count was studied using adjusted linear mixed models. Results: We included 185 HIV-2+ and 30321 HIV-1+ patients with median age of 46 years (IQR 36-52) and 37 years (IQR 31-44), respectively. Median observed pretreatment CD4 cell counts/mm3 were 203 (95% CI 100-290) in HIV-2+ patients and 223 (95% CI 100-353) in HIV-1+ patients. Mean observed CD4 cell count changes from start of cART to 12 months were +105 (95% CI 77-134) in HIV-2+ patients and +202 (95% CI 199-205) in HIV-1+ patients, an observed difference of 97 cells/mm3 in 1 year. In adjusted analysis, the mean CD4 cell increase was overall 25 CD4 cells/mm3/year lower (95% CI 5-44; P = 0.0127) in HIV-2+ patients compared with HIV-1+ patients. Conclusions: A poorer CD4 cell increase during first-line cART was observed in HIV-2+ patients, even after adjusting for pretreatment pVL and other potential confounders. Our results underline the need to identify more potent therapeutic regimens or strategies against HIV-2.

Phylogenetic evidence for underreporting of male-to-male sex among human immunodeficiency virus-infected donors in the Netherlands and Flanders.

BACKGROUND: Separate transmission networks for human immunodeficiency virus (HIV) coexist. Molecular typing of viral genomes can provide insight in HIV transmission routes in donors for whom risk behavior-based donor selection failed. STUDY DESIGN AND METHODS: This study includes all HIV-infected Dutch and Flemish donors in the period 2005 to 2014 (n = 55). Part of the HIV polymerase (pol) gene was amplified, sequenced, and compared with more than 10,000 HIV strains obtained from HIV-infected Dutch and Flemish patients. The most likely transmission route was determined based on HIV phylogeny and the donor's self-reported risk behavior during the exit interview. RESULTS: HIV-infected donors were predominantly male (69%), were repeat donors (73%), were born in the Netherlands or Belgium (95%), and harbored HIV Subtype B (68%). Seventy-five percent of HIV-infected male donors were part of robust phylogenetic clusters linked to male-to-male sex, while only 24% of HIV-infected male donors reported male-to-male sex during posttest counseling. Sex between men and women accounted for 13% of HIV infections in male donors and 93% of HIV infections in female donors based on phylogenetic analysis. Only 40% of HIV-infected female donors had HIV Subtype B; 65% of female donors reported a foreign partner and indeed HIV sequences interspersed with sequences from HIV-endemic areas abroad, in particular sub-Saharan Africa. CONCLUSION: HIV typing helps to understand HIV transmission routes in donor populations. We found substantial underreporting of male-to-male sex among HIV-infected male donors. Donor education on HIV risk factors and the danger of window-period donations and a donor environment that encourages frank disclosure of sexual behavior will contribute to a decrease of HIV-infected donors.

Reduction in undiagnosed HIV infection in the European Union/European Economic Area, 2012 to 2016.

It is well-documented that early HIV diagnosis and linkage to care reduces morbidity and mortality as well as HIV transmission. We estimated the median time from HIV infection to diagnosis in the European Union/European Economic Area (EU/EEA) at 2.9 years in 2016, with regional variation. Despite evidence of a decline in the number of people living with undiagnosed HIV in the EU/EEA, many remain undiagnosed, including 33% with more advanced HIV infection (CD4 < 350 cells/mm3).