DOI: 10.5061/dryad.m37pvmdgr
title: HIV epidemic and needs beyond fast-track cities: a transmission networks analysis to study the dynamic of HIV clusters in a French region near Paris

description: The Centre-Loire Valley region is a low-density demographic and medical
 region near the fast-track city of Paris, with persistent elevated rate of
 positive HIV testing. We investigated the role and characteristics of
 transmission clusters in the HIV dynamics in this region for appropriate
 local response. HIV pol gene sequences collected in Centre-Loire Valley
 over a decade (2010-2020) were included in a phylogenetic analysis
 combined with epidemiological data. Putative transmission clusters were
 inferred using HIV TRACE methods. Risk factors of being part of a cluster
 were studied using multivariate logistic regression models. Of the 1305
 participants, 579 (44%) were born out of France, mainly from Sub-Saharan
 Africa, 494 (38%) were women, 433 (33%) men who have sex with men (MSM),
 694 (53%) heterosexuals. Migrants had lower CD4 cell count at diagnosis
 than those born in France (296 vs 443, p&lt; 0.01), likely due to
 delayed time to diagnosis. A total of 86 clusters were identified
 (clustering rate of 21%) including 33 of size ≥ 3 involving 170
 participants (3-16 per cluster). MSM (OR 2.16, p&lt; 0.01) and higher
 viral load (OR 1.21, p&lt; 0.01) were risk factors of clustering.
 Individuals born abroad were at lower risk than those born in France (OR
 0.03, p &lt; 0.01). Among large clusters, persistent virological
 control was achieved in a median of 75% of participants vs 83% outside
 clusters (p&lt;0.01). Molecular epidemiology showed that MSM were part
 of local transmission networks but not heterosexual migrants, suggesting
 distinct epidemic features and needs.
description: Drug resistance genotyping was realized in the two specialized
 virology laboratories of the CLV region (903 from Tours and 402 from
 Orléans), by sequencing <em>pol</em> gene encoding HIV-1
 reverse transcriptase (RT) and protease from patients’ plasma samples,
 using Sanger as previously described (Chaix M-L, Descamps D, Harzic M, et
 al. Stable prevalence of genotypic drug resistance mutations but increase
 in non-B virus among patients with primary HIV-1 infection in France. AIDS
 2003; 17:2635–2643).
description: ## HIV epidemic and needs beyond fast-track cities: a transmission
 networks analysis to study the dynamic of HIV clusters in a French region
 near Paris This dataset includes HIV pol sequences isolated from 1305
 adults who were followed at one of the hospitals in the Centre-Val de
 Loire region (France) between 2010 and 2020. We have submitted our raw
 data as a fasta file (PHYLOVIH.fasta) and specimen information
 (PHYLOVIH_Metadata.csv). ## Description of the data and file structure ###
 PHYLOVIH.fasta This fasta file includes 1305 Partial pol gene sequences.
 Each sequence is labeled with the participant's unique identifier.
 For example: &gt;VIH-000001 refers to participant 1 of the study. ###
 PHYLOVIH_Metadata.csv * Sequence name : unique participant identifier
 (same identifier used in PHYLOVIH.fasta ) * Sample date : date of the
 blood sample  (month-year) * Country : where the sample was taken (all
 samples from the study ) * Subtype : HIV-subtype determined by uploading
 sequences individually into the REGA HIV-1 Automated Subtyping Tool
 version 3.47
 ([https://www.genomedetective.com/app/typingtool/hiv](https://www.genomedetective.com/app/typingtool/hiv)) and HIV Blast ([https://www.hiv.lanl.gov/](https://www.hiv.lanl.gov/)) * Host : all samples were collected from human participants * Sequencing technology : all sequences were obtained using Sanger sequencing * Length : total number of nucleotides in each sequence * GenomeStart : sequence start relative to the reference sequence for HIV-1(HXB2) * GenomeEnd : sequence end relative to the reference sequence for HIV-1 (HXB2) * Stop Codons : total number of stop codons in each sequence (corresponding to codon TAA, TAG and TGA) * Hypermutation : detection of mutations fitting a specific parttern of hypermutation by the HYPERMUT 3 tool ([https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html](https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html)) * Non-ACGT : frequence of ambiguous nucleotides in each sequence, defined IUPAC nucleotide ambiguity codes (Cornish-Bowden (1985) IUPAC-IUB SYMBOLS FOR NUCLEOTIDE NOMENCLATURE. Nucl. Acids Res. 13: 3021-3030) ## Human subjects data All subjects of this study gave their informed and written consent for the reuse of their anonymized data for research purposes. Metadata only contain sequence features but no identifying information (date of birth, home address or identification number). The clinical data of participants involved in clusters were not disclosed in order to minimise the risk of re-identification and stigmatisation of participants when communicating molecular clusters.