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Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data.

ABSTRACT: Episodic high-risk sexual behavior is common and can have a profound effect on HIV transmission. In a model of HIV transmission among men who have sex with men (MSM), changing the frequency, duration and contact rates of high-risk episodes can take endemic prevalence from zero to 50% and more than double transmissions during acute HIV infection (AHI). Undirected test and treat could be inefficient in the presence of strong episodic risk effects. Partner services approaches that use a variety of control options will be likely to have better effects under these conditions, but the question remains: What data will reveal if a population is experiencing episodic risk effects? HIV sequence data from Montreal reveals genetic clusters whose size distribution stabilizes over time and reflects the size distribution of acute infection outbreaks (AIOs). Surveillance provides complementary behavioral data. In order to use both types of data efficiently, it is essential to examine aspects of models that affect both the episodic risk effects and the shape of transmission trees. As a demonstration, we use a deterministic compartmental model of episodic risk to explore the determinants of the fraction of transmissions during acute HIV infection (AHI) at the endemic equilibrium. We use a corresponding individual-based model to observe AIO size distributions and patterns of transmission within AIO. Episodic risk parameters determining whether AHI transmission trees had longer chains, more clustered transmissions from single individuals, or different mixes of these were explored. Encouragingly for parameter estimation, AIO size distributions reflected the frequency of transmissions from acute infection across divergent parameter sets. Our results show that episodic risk dynamics influence both the size and duration of acute infection outbreaks, thus providing a possible link between genetic cluster size distributions and episodic risk dynamics.

SUBMITTER: Alam SJ

PROVIDER: S-EPMC3748724 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data.

Alam Shah Jamal SJ Zhang Xinyu X Romero-Severson Ethan Obie EO Henry Christopher C Zhong Lin L Volz Erik M EM Brenner Bluma G BG Koopman James S JS

Epidemics 20121123 1

Episodic high-risk sexual behavior is common and can have a profound effect on HIV transmission. In a model of HIV transmission among men who have sex with men (MSM), changing the frequency, duration and contact rates of high-risk episodes can take endemic prevalence from zero to 50% and more than double transmissions during acute HIV infection (AHI). Undirected test and treat could be inefficient in the presence of strong episodic risk effects. Partner services approaches that use a variety of ...[more]

PMID: 23438430

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Project description:BackgroundThe structure of sexual contact networks plays a key role in the epidemiology of sexually transmitted infections, and their reconstruction from interview data has provided valuable insights into the spread of infection. For HIV, the long period of infectivity has made the interpretation of contact networks more difficult, and major discrepancies have been observed between the contact network and the transmission network revealed by viral phylogenetics. The high rate of HIV evolution in principle allows for detailed reconstruction of links between virus from different individuals, but often sampling has been too sparse to describe the structure of the transmission network. The aim of this study was to analyze a high-density sample of an HIV-infected population using recently developed techniques in phylogenetics to infer the short-term dynamics of the epidemic among men who have sex with men (MSM).Methods and findingsSequences of the protease and reverse transcriptase coding regions from 2,126 patients, predominantly MSM, from London were compared: 402 of these showed a close match to at least one other subtype B sequence. Nine large clusters were identified on the basis of genetic distance; all were confirmed by Bayesian Monte Carlo Markov chain (MCMC) phylogenetic analysis. Overall, 25% of individuals with a close match with one sequence are linked to 10 or more others. Dated phylogenies of the clusters using a relaxed clock indicated that 65% of the transmissions within clusters took place between 1995 and 2000, and 25% occurred within 6 mo after infection. The likelihood that not all members of the clusters have been identified renders the latter observation conservative.ConclusionsReconstruction of the HIV transmission network using a dated phylogeny approach has revealed the HIV epidemic among MSM in London to have been episodic, with evidence of multiple clusters of transmissions dating to the late 1990s, a period when HIV prevalence is known to have doubled in this population. The quantitative description of the transmission dynamics among MSM will be important for parameterization of epidemiological models and in designing intervention strategies.

Project description:BACKGROUND:Viruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora. RESULTS:VirMiner achieved 41.06% ± 17.51% sensitivity and 81.91% ± 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% ± 16.94%) than VirFinder (34.63% ± 17.96%) and VirSorter (18.75% ± 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at http://sbb.hku.hk/VirMiner/ . CONCLUSIONS:We developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder-the most widely used tools-VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics. TRIAL REGISTRATION:The European Union Clinical Trials Register, EudraCT Number: 2013-003378-28 . Registered on 9 April 2014.

Dataset Information

Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data.

Publications

Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data.

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