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.

Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver.

Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver.

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.].

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.

TB-HIV co-infection in the Netherlands: estimating prevalence and under-reporting in national registration databases using a capture-recapture analysis.

BACKGROUND: Knowledge of the HIV status in patients with tuberculosis (TB) and vice versa is crucial for proper individual patient management, while knowledge of the prevalence of co-infection guides preventive and therapeutic strategies. The aim of the study was to assess if national disease databases on TB and HIV are adequate sources to provide this information. METHODS: A two way capture-recapture analysis to assess the completeness of the registers, and to obtain the prevalence of TB-HIV co-infection in the Netherlands in the years 2002-2012. RESULTS: HIV testing was performed in less than 50% of the patients with TB. Of the 932 TB-HIV infected patients, just 293 (31.4%) were registered in both registers. Under-reporting of TB-HIV co-infection ranged from 50% to 70% in the national TB register, and from 31% to 37% in the HIV database. Prevalence of TB-HIV co-infection in the Netherlands in 2012 was 7.1% (95% CI 6.0% to 8.3%), which was more than double of the prevalence estimated from the national TB database. CONCLUSIONS: TB-HIV co-infection is markedly under-reported in national disease databases. There is an urgent need for improved registration and preferably a routine data exchange between the two surveillance systems.

Prolonged decrease of CD4+ T lymphocytes in HIV-1-infected patients after radiotherapy for a solid tumor.

BACKGROUND: In HIV-negative patients, radiotherapy (RT) decreases CD4 T-cell counts. We studied the effects of RT in HIV-1 positive patients. METHODS: HIV-1 positive patients with a subsequent diagnosis of a solid tumor were selected from the Dutch national observational HIV cohort, Aids Therapy Evaluation in the Netherlands (ATHENA). The patients were grouped according to whether they had received RT or not. Primary endpoint of the study was the time from baseline to reaching CD4 cell counts higher than those at baseline. Kaplan-Meier estimates of the percentage of patients reaching the endpoint were calculated. RESULTS: Ninety patients were included of whom 36 received RT and 54 did not. Median duration of RT was 46 [interquartile range (IQR) 30-63] days. Median first CD4 cell count after stopping RT was 150 (IQR 30-270) × 10/L lower compared with baseline. In 13 of the 36 patients receiving RT, CD4 cell counts recovered to baseline, after a median of 469 (IQR 345-595) days. In 35 of the 54 patients without RT, the CD4 cell count recovered to baseline or higher, after a median of 112 (IQR 42-182) days. After 3 years, in 39% of patients who had RT compared with 71% of patients without RT, CD4 cell counts recovered to baseline or higher (P < 0.0001). In a Cox regression adjusted for potential confounders, RT was associated with a longer (hazard ratio 0.29; 95% confidence interval 0.13 to 0.63) and combination antiretroviral therapy use with a shorter time to return to baseline [hazard ratio 2.46 (95% confidence interval 1.11 to 5.48)]. CONCLUSIONS: RT resulted in a significant and prolonged decrease in CD4 cell counts.

Measuring the Quality of Data Collection in a Large Observational Cohort of HIV and AIDS.

The aim of this study was to examine the quality of data collection by studying the validity of collected data. Data were extracted from the clinic charts of two anonymous outpatients by 38 data collectors. A standard for the data to be collected was determined (168 items). The validity was measured by comparing the collected items with the standard; in this way, the percentages of the collected items that were 'correct' could be calculated. The percentage 'correct' was higher for clinic chart 1 (mean: 83% correct, SD 7%) than for clinic chart 2 (mean: 78% correct, SD 8%). All categories contained incorrectly collected data. These data were divided into missing data, incorrect start-stop dates, and surplus collected data. Almost all start-stop dates would change into 'correct' if 'monthyear' was considered correct (instead of the standard 'daymonthyear'). Not all data collectors used specific protocols, and sources other than the written comments were not always checked. This study shows that a high proportion of data was correctly collected. However, the collection of start-stop dates was not optimal, and the collected data included surplus and missing data. Data collectors should be more knowledgeable about HIV disease and trained in the use of difficult protocols, so that they can better recognize what data to collect and how it should be collected. Among physicians, there should be more agreement about what information to record in the charts, to facilitate data extraction for data collectors.