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Record W2747592538 · doi:10.1093/ve/vew036.001

A2 HIV transmission networks among injection drug users in Pakistan

2017· article· en· W2747592538 on OpenAlexaff
François Cholette, John Ho, Hillary McCoubrey, K. Kadivar, Laura H. Thompson, James Blanchard, Faran Emmanuel, James Brooks, John Kim, Paul Sandstrom

Bibliographic record

VenueVirus Evolution · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsHealth Sciences CentreUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsTransmission (telecommunications)DrugHuman immunodeficiency virus (HIV)VirologyBusinessComputer scienceMedicinePharmacologyTelecommunications

Abstract

fetched live from OpenAlex

Pakistan is currently facing a concentrated HIV epidemic among injection drug users (IDUs). Well-defined transmission networks, based on molecular epidemiology, have the potential to assist in the development of targeted screening and prevention strategies as well as identify hidden epidemic drivers. Here we present molecular transmission networks re-constructed from HIV-1 pol sequences collected from injection drug users located in major urban centres in Pakistan. Dried blood spots (DBS) were collected on Whatman 903 cards from IDUs in Karachi (n = 300), Hyderabad (n = 300), and Peshawar (n = 257). Nucleic acids were extracted using an easyMAG instrument. Protease and part of the reverse transcriptase genes were amplified and sequenced using an in-house HIV genotyping assay. Transmission networks were re-constructed using publicly available bioinformatics software. Most of the HIV pol sequences (75%) from 96 individuals formed connected nodes arranged in 7 clusters, ranging in size from 3 to 33 individuals. Clusters were mainly homogeneous, in which 87 inferred transmission events (90.6%) occurred within a particular city. A small number (9.4%) of transmission events occurred between cities. The highest number of inter-city transmission events (7.3%) occurred between Karachi and Hyderabad while only 2 (2.1%) occurred between Karachi and Peshawar. Transmission events were not observed between Hyderabad and Peshawar. The majority of sequences analyzed formed localized transmission networks partitioned according to city of collection, although some inter-city linkages are apparent. Reconstruction of transmission networks based on sequencing-based approaches has the potential to expand our understanding of the HIV epidemic currently taking place in Pakistan especially if used in combination with epidemiological data. Particular attention maybe warranted for Karachi since transmission linkages were observed with all the other cities included in this study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.336
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
Has abstractno

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