Evidence map›Paper›PMID 34620119›Full record

ArticleBMC infectious diseases2021

Drivers of HIV-1 drug resistance to non-nucleoside reverse-transcriptase inhibitors (NNRTIs) in nine southern African countries: a modelling study.

Julien Riou, Carole Dupont, Silvia Bertagnolio, Ravindra K Gupta, Roger D Kouyos, Matthias Egger, Christian L Althaus

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
1.0field-weighted citation impact, top 21% of its field
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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 3 countries.

Julien RiouInstitute of Social and Preventive Medicine (ISPM), University of Bern, Mittelstrasse 43, 3012, Bern, Switzerland. julien.riou@ispm.unibe.ch.
Carole DupontInstitute of Social and Preventive Medicine (ISPM), University of Bern, Mittelstrasse 43, 3012, Bern, Switzerland.
Silvia BertagnolioHIV/Hepatitis/STI Department, World Health Organization, Geneva, Switzerland.
Ravindra K GuptaDepartment of Infection, University College London, London, UK.
Roger D KouyosDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
Matthias EggerInstitute of Social and Preventive Medicine (ISPM), University of Bern, Mittelstrasse 43, 3012, Bern, Switzerland.
Christian L AlthausInstitute of Social and Preventive Medicine (ISPM), University of Bern, Mittelstrasse 43, 3012, Bern, Switzerland.
University of Bern · CHAfrica Health Research Institute · ZAUniversity of Zurich · CHWorld Health Organization · CH

Funding

Observational Antiretroviral Studies In Southern Africa (OASIS) CollaborationU01AI069924 · NIAID · UNIVERSITAT BERN · PI Cleophas Chimbetete, Mary-Ann Davies · 2006 to 2026
$55.9M
National Institute of Allergy and Infectious Diseases 5U01-AI069924-05NIAID NIH HHS U01 AI069924Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 174281World Health Organization 001
6 · The paper itself

Abstract

introductionThe rise of HIV-1 drug resistance to non-nucleoside reverse-transcriptase inhibitors (NNRTI) threatens antiretroviral therapy's long-term success (ART). NNRTIs will remain an essential drug for the management of HIV-1 due to safety concerns associated with integrase inhibitors. We fitted a dynamic transmission model to historical data from 2000 to 2018 in nine countries of southern Africa to understand the mechanisms that have shaped the HIV-1 epidemic and the rise of pretreatment NNRTI resistance.

methodsWe included data on HIV-1 prevalence, ART coverage, HIV-related mortality, and survey data on pretreatment NNRTI resistance from nine southern Africa countries from a systematic review, UNAIDS and World Bank. Using a Bayesian hierarchical framework, we developed a dynamic transmission model linking data on the HIV-1 epidemic to survey data on NNRTI drug resistance in each country. We estimated the proportion of resistance attributable to unregulated, off-programme use of ART. We examined each national ART programme's vulnerability to NNRTI resistance by defining a fragility index: the ratio of the rate of NNRTI resistance emergence during first-line ART over the rate of switching to second-line ART. We explored associations between fragility and characteristics of the health system of each country.

resultsThe model reliably described the dynamics of the HIV-1 epidemic and NNRTI resistance in each country. Predicted levels of resistance in 2018 ranged between 3.3% (95% credible interval 1.9-7.1) in Mozambique and 25.3% (17.9-33.8) in Eswatini. The proportion of pretreatment NNRTI resistance attributable to unregulated antiretroviral use ranged from 6% (2-14) in Eswatini to 64% (26-85) in Mozambique. The fragility index was low in Botswana (0.01; 0.0-0.11) but high in Namibia (0.48; 0.16-10.17), Eswatini (0.64; 0.23-11.8) and South Africa (1.21; 0.83-9.84). The combination of high fragility of ART programmes and high ART coverage levels was associated with a sharp increase in pretreatment NNRTI resistance.

conclusionsThis comparison of nine countries shows that pretreatment NNRTI resistance can be controlled despite high ART coverage levels. This was the case in Botswana, Mozambique, and Zambia, most likely because of better HIV care delivery, including rapid switching to second-line ART of patients failing first-line ART.

Indexed as

HIV-1HIV InfectionsBayes TheoremDNA-Directed RNA PolymerasesDrug Resistance, ViralHumansSouth AfricaDNA-Directed RNA PolymerasesAntiretroviral therapyEpidemiologyHealth system scienceHIV drug resistanceModellingSouthern Africa

Identifiers

PMID34620119
PMCPMC8499543
OpenAlexW4205943263

What OpenQuestion holds

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LicenceCC BY
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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.