Evidence map›Paper›PMID 29460226›Full record

ReviewCurrent HIV/AIDS reports2018

Genetic Cluster Analysis for HIV Prevention.

Mary Kate Grabowski, Joshua T Herbeck, Art F Y Poon

Abstract readReview
In one paragraph

Review in Current HIV/AIDS reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  16. Characterization of HIV-1 Epidemic in Kyrgyzstan.Frontiers in microbiology · 2021
    Article
  17. Article
  18. Article
  19. Phylogenetic Analysis of Human Immunodeficiency Virus from People Who Inject Drugs in Indonesia, Ukraine, and Vietnam: HPTN 074.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mary Kate GrabowskiDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Rakai Health Sciences Program, Baltimore, MD, USA.
Joshua T HerbeckInternational Clinical Research Center, Department of Global Health, University of Washington, Seattle, WA, USA. herbeck@uw.edu.
Art F Y PoonDepartment of Pathology and Laboratory Medicine, Western University, London, ON, Canada.

Funding

Integrating Assisted Partner Services and Phylogenetics for HIV and HCV PreventionR01DA043409 · NIDA · UNIVERSITY OF WASHINGTON · PI FARQUHAR, CAREY, HERBECK, JOSHUA T · 2017 to 2021
$3.6M
Combined phylogenetic and epidemiological analysis to identify HIV transmission sources in Seattle WAR01AI127232 · NIAID · UNIVERSITY OF WASHINGTON · PI HERBECK, JOSHUA T, KERANI, ROXANNE PIEPER · 2016 to 2019
$2.0M
Revealing women's hidden role as critical components of HIV transmission networks in Rakai, Uganda: an interdisciplinary approachK01AI125086 · NIAID · JOHNS HOPKINS UNIVERSITY · PI GRABOWSKI, MARY KATHRYN · 2016 to 2020
$638k
CIHR BOP-149562CIHR CIHR FRN-130609CIHR PJT-153391NIAID NIH HHS K01 AI125086NIAID NIH HHS R01 AI127232NIH HHS K01AI125086NIH HHS R01AI127232NIH HHS R01DA043409
6 · The paper itself

Abstract

purpose of reviewThis review summarizes the use of genetic similarity clusters to understand HIV transmission and inform prevention efforts. RECENT

findingsRecent emphases include the development of real-time cluster identification in order to interrupt transmission chains, the use of clusters to estimate rates of transmission along the HIV care cascade, and the extension of cluster analyses to understand transmission in the generalized epidemics of sub-Saharan Africa. Importantly, this recent empirical work has been accompanied by theoretical work that elucidates the processes that underlie HIV genetic similarity clusters; multiple studies suggest that clusters are not necessarily enriched with individuals with high transmission rates, but rather can reflect variation in sampling times within a population, with individuals sampled early in infection more likely to cluster. Analyses of genetic similarity clusters have great promise to inform HIV epidemiology and prevention. Future emphases should include the collection of additional sequence data from underrepresented populations, such as those in sub-Saharan Africa, and further development and evaluation of clustering methods.

Indexed as

Africa South of the SaharaCluster AnalysisEpidemicsGenetic Predisposition to DiseaseHIV InfectionsHumansCluster identificationGenetic similarity clustersHIVHIV epidemiologyPrevention

Identifiers

PMID29460226
PMCPMC5882762

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.