Molecular Epidemiology Reveals Long‐Term Changes in HIV Type 1 Subtype B Transmission in Switzerland

Kouyos, Roger D.; Wyl, Viktor von; Yerly, Sabine; Böni, Jürg; Taffé, Patrick; Shah, Cyril; Bürgisser, Philippe; Klimkait, Thomas; Weber, Rainer; Hirschel, Bernard; Cavassini, Matthias; Furrer, Hansjakob; Battegay, Manuel; Vernazza, Pietro; Bernasconi, Enos; Rickenbach, Martin; Ledergerber, Bruno; Bonhoeffer, Sebastian; Günthard, Huldrych F.

doi:10.1086/651951

Cited by 166 publications

(227 citation statements)

References 32 publications

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“…The importance of shared language has also been demonstrated by work on the Swiss HIV Cohort Study, which found evidence of preferential within-group transmission among German and French speaking persons. 16 Although we cannot exclude the possibility that the linked non-U.S. sequences from the LANL database were obtained from the same individuals in the U.S. National HIV Surveillance System, these linkages point to international travel of HIV to countries of birth and shared language.…”

Section: Discussionmentioning

confidence: 99%

“…Transmission networks inferred from genetic sequences allow the study of viral dynamics on a local or national level. [14][15][16][17][18][19] Moreover, these networks provide the means to improve the effect of targeted treatment intervention. 20 Recent work by Wertheim et al 2 has demonstrated how the global diversity of HIV can be efficiently queried for transmission links by comparing genetic distances between isolates.…”

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confidence: 99%

See 1 more Smart Citation

The International Dimension of the U.S. HIV Transmission Network and Onward Transmission of HIV Recently Imported into the United States

WertheimJoel

OsterAlexandra

HernandezAngela

et al. 2016

AIDS Research and Human Retroviruses

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

The International Dimension of the U.S. HIV Transmission Network and Onward Transmission of HIV Recently Imported into the United States

WertheimJoel

OsterAlexandra

HernandezAngela

et al. 2016

AIDS Research and Human Retroviruses

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“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] However, there is confusion surrounding HIV clustering due to differences in sampling, methodological approaches, and interpretation of HIV clustering results across studies. Issues that still need to be resolved through dedicated studies, meta-analyses, and comprehensive reviews include the following: What is the definition of an HIV cluster?…”

Section: Introductionmentioning

confidence: 99%

Impact of Sampling Density on the Extent of HIV Clustering

NovitskyVlad

Moyo²,

LeiQuanhong³

et al. 2014

AIDS Research and Human Retroviruses

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Identifying and monitoring HIV clusters could be useful in tracking the leading edge of HIV transmission in epidemics. Currently, greater specificity in the definition of HIV clusters is needed to reduce confusion in the interpretation of HIV clustering results. We address sampling density as one of the key aspects of HIV cluster analysis. The proportion of viral sequences in clusters was estimated at sampling densities from 1.0% to 70%. A set of 1,248 HIV-1C env gp120 V1C5 sequences from a single community in Botswana was utilized in simulation studies. Matching numbers of HIV-1C V1C5 sequences from the LANL HIV Database were used as comparators. HIV clusters were identified by phylogenetic inference under bootstrapped maximum likelihood and pairwise distance cut-offs. Sampling density below 10% was associated with stochastic HIV clustering with broad confidence intervals. HIV clustering increased linearly at sampling density > 10%, and was accompanied by narrowing confidence intervals. Patterns of HIV clustering were similar at bootstrap thresholds 0.7 to 1.0, but the extent of HIV clustering decreased with higher bootstrap thresholds. The origin of sampling (local concentrated vs. scattered global) had a substantial impact on HIV clustering at sampling densities ‡ 10%. Pairwise distances at 10% were estimated as a threshold for cluster analysis of HIV-1 V1C5 sequences. The node bootstrap support distribution provided additional evidence for 10% sampling density as the threshold for HIV cluster analysis. The detectability of HIV clusters is substantially affected by sampling density. A minimal genotyping density of 10% and sampling density of 50-70% are suggested for HIV-1 V1C5 cluster analysis.

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“…Achievement of this goal could be facilitated by a better understanding of the structure and dynamics of HIV transmission networks and comprehensive HIV cluster analysis. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] The extent of viral clustering is one of the key factors in making inferences about epidemiologic processes inferred from viral phylogenies. However, it remains to be established how the selection of region across the HIV-1 genome and its length affects the extent of HIV clustering.…”

Section: Introductionmentioning

confidence: 99%

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

Novitsky

Moyo

Lei

et al. 2015

AIDS Research and Human Retroviruses

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To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

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Molecular Epidemiology Reveals Long‐Term Changes in HIV Type 1 Subtype B Transmission in Switzerland

Abstract: Our analysis suggests (1) the absence of a self-sustaining epidemic of HIV-1 subtype B in HETs in Switzerland and (2) a temporally decreasing clustering of HIV infections in HETs and IDUs.

Cited by 166 publications

References 32 publications

The International Dimension of the U.S. HIV Transmission Network and Onward Transmission of HIV Recently Imported into the United States

The International Dimension of the U.S. HIV Transmission Network and Onward Transmission of HIV Recently Imported into the United States

Impact of Sampling Density on the Extent of HIV Clustering

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

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