Evidence map›Paper›PMID 38076835›Full record

ArticleResearch square2023

HIV transmission dynamics and population-wide drug resistance in rural South Africa.

Ravindra Gupta, Steven Kemp, Kimia Kamelian, Diego Cuadros, Ravindra Gupta, Mark Cheng, Elphas Okango, Willem Hanekom, Thumbi Ndung'u, Deenan Pillay and 4 more

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 10 institutions in 6 countries.

Ravindra GuptaUniversity of Cambridge.ORCID 0000-0001-9751-1808
Steven KempUniversity of Oxford.ORCID 0000-0001-7077-6793
Kimia KamelianUniversity of Cambridge.
Diego CuadrosUniversity of Cincinnati.ORCID 0000-0001-7060-4203
Ravindra GuptaUniversity College London.
Mark Chengcambridge university.
Elphas OkangoAHRI.
Willem HanekomUniversity of KwaZulu-Natal.ORCID 0000-0003-3070-6154
Thumbi Ndung'u
Deenan PillayUCL.
David Bonsalloxford university.
Emily WongAfrica Health Research Institute.ORCID 0000-0003-4755-5380
Frank TanserStellenbosch University.
Mark SiednerHarvard Medical School.ORCID 0000-0003-3506-842X
University of Cambridge · GBAfrica Health Research Institute · ZAAnanthapuri Hospitals and Research Institute · INBridge University · SSHarvard University · USStellenbosch University · ZAUniversity College Lahore · PKUniversity of Cincinnati · USUniversity of KwaZulu-Natal · ZAUniversity of Oxford · GB

Funding

Mentoring patient-oriented research to improve cardiovascular health among people with HIV in sub-Saharan AfricaK24HL166024 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MARK J SIEDNER · 2022 to 2026
$616k
NHLBI NIH HHS K24 HL166024Wellcome Trust
6 · The paper itself

Abstract

Despite the scale-up of antiretroviral therapy (ART) in South Africa, HIV-1 incidence remains high. The anticipated use of potent integrase strand transfer inhibitors and long-acting injectables aims to enhance viral suppression at the population level and diminish transmission. Nevertheless, pre-existing drug resistance could impede the efficacy of long-acting injectable ART combinations, such as rilpivirine (an NNRTI) and cabotegravir (an INSTI). Consequently, a thorough understanding of transmission networks and geospatial distributions is vital for tailored interventions, including pre-exposure prophylaxis with long-acting injectables. However, empirical data on background resistance and transmission networks remain limited. In a community-based study in rural KwaZulu-Natal (2018-2019), prior to the widespread use of integrase inhibitor-based first-line ART, we performed HIV testing with reflex HIV-1 RNA viral load quantification on 18,025 participants. From this cohort, 6,096 (33.9%) tested positive for HIV via ELISA, with 1,323 (21.7%) exhibiting detectable viral loads (> 40 copies/mL). Of those with detectable viral loads, 62.1% were ART-naïve, and the majority of the treated were on an efavirenz + cytosine analogue + tenofovir regimen. Deep sequencing analysis, with a variant abundance threshold of 20%, revealed NRTI resistance mutations such as M184V in 2% of ART-naïve and 32% of treated individuals. Tenofovir resistance mutations K65R and K70E were found in 12% and 5% of ART-experienced individuals, respectively, and in less than 1% of ART-naïve individuals. Integrase inhibitor resistance mutations were notably infrequent (< 1%). Prevalence of pre-treatment drug resistance to NNRTIs was 10%, predominantly consisting of the K103N mutation. Among those with viraemic ART, NNRTI resistance was 50%, with rilpivirine-associated mutations observed in 9% of treated and 6% of untreated individuals. Cluster analysis revealed that 20% (205/1,050) of those sequenced were part of a cluster. We identified 171 groups with at least two linked participants; three quarters of clusters had only two individuals, and a quarter had 3-6 individuals. Integrating phylogenetic with geospatial analyses, we revealed a complex transmission network with significant clustering in specific regions, notably peripheral and rural areas. These findings derived from population scale genomic analyses are encouraging in terms of the limited resistance to DTG, but indicate that transitioning to long-acting cabotegravir + rilpivirine for transmission reduction should be accompanied by prior screening for rilpivirine resistance. Whole HIV-1 genome sequencing allowed identification of significant proportions of clusters with multiple individuals, and geospatial analyses suggesting decentralised networks can inform targeting public health interventions to effectively curb HIV-1 transmission.

Identifiers

PMID38076835
PMCPMC10705695
OpenAlexW4389077066

What OpenQuestion holds

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Registered trials

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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.