Evidence map›Paper›PMID 41867175›Full record

ArticlemedRxiv : the preprint server for health sciences2026

The age and sex dynamics of heterosexual HIV transmission in Zambia: an HPTN 071 (PopART) phylogenetic and modelling study.

M Hall, W Probert, L Abeler-Dörner, C Wymant, F Di Lauro, X Xi, R Sauter, T Golubchik, D Bonsall, M Pickles and 16 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. 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.

No citing paper in PubMed yet.

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

26 authors.

M HallDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0002-2671-3864
W ProbertBig Data Institute, University of Oxford, Oxford, UK.
L Abeler-DörnerPandemic Sciences Institute, University of Oxford, Oxford, UK.
C WymantPandemic Sciences Institute, University of Oxford, Oxford, UK.
F Di LauroPandemic Sciences Institute, University of Oxford, Oxford, UK.
X XiDepartment of Mathematics, Imperial College, London, UK.
R SauterBig Data Institute, University of Oxford, Oxford, UK.
T GolubchikBig Data Institute, University of Oxford, Oxford, UK.
D BonsallPandemic Sciences Institute, University of Oxford, Oxford, UK.
M PicklesMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College, London, UK.
A CoriMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College, London, UK.
J BwalyaZambart, Lusaka, Zambia.
S FloydDepartment of Infectious Disease Epidemiology and International Health, London School of Hygiene and Tropical Medicine, London, UK.
N MandlaDesmond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
K ShanaubeZambart, Lusaka, Zambia.
B YangDesmond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
P BockDesmond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
D DonnellFred Hutchinson Cancer Research Center, Seattle, US.
M K GrabowskiBloomberg School of Public Health, Johns Hopkins University, Baltimore, US.
D PillayDivision of Infection and Immunity, University College London, London, United Kingdom.
O RatmannDepartment of Mathematics, Imperial College, London, UK.
S FidlerDepartment of Infectious Disease, Faculty of Medicine, Imperial College, London, UK.
H AylesDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK.
R HayesDepartment of Infectious Disease Epidemiology and International Health, London School of Hygiene and Tropical Medicine, London, UK.
C FraserPandemic Sciences Institute, University of Oxford, Oxford, UK.ORCID 0000-0003-2399-9657
PANGEA-HIV consortium HPTN 071 (PopART) study team

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While much progress has been made in reducing the incidence of HIV-1 infection in sub-Saharan Africa in recent years, bringing the epidemic to an end will require identification of the demographic groups that continue to contribute to transmission. Pathogen phylogenetics and individual-based mathematical models (IBMs) of transmission are approaches that enable researchers to explore such questions. Here, we used both methods to characterise the ages and sexes of the individuals involved in heterosexual transmission in the context of the HPTN 071 (PopART) trial in Zambia. The two methods produced largely concordant results, strengthening confidence in both. A principal finding was that when the age gap in transmission (the difference of ages between the two individuals) was stratified by recipient age, the largest differences were for the youngest female recipients and the smallest for the youngest males. For women under 21 this stood at a male 9.87 years older (95% CI: 8.02 - 11.59) in the phylogenetics, compared to 6.93 (95% HDI: 6.56 - 7.32) in the IBM. As the age of female recipients increased, this gap decreased towards parity. Conversely, the under-21 male recipients saw the smallest gaps with the female older by 0.14 years (95% CI: -2.95 - 3.23) in the phylogenetics and 1.38 years (95% HDI: 0.98 - 1.68) in the IBM. As the age of male recipients decreased, this gap steadily increased. The consequence of this pattern is that transmission to new age cohorts first entering into sexual activity is driven predominantly by male-to-female transmission. We also showed that targeting interventions at younger adults captures most of the benefit of population-wide approaches. We used the IBM to simulate the PopART universal testing and treatment intervention into the future, showing that effective treatment of under-35-year-olds would account for 94.3% (95% HDI: 65.8% - 126.6%) of the reduction in incidence by 2039 that would be achieved by treating the entire population, while effective treatment of under-35 men accounts for 60% (95% HDI: 23.2% - 92.1%). Finally, we simulated a one-year cessation of ART treatment for the whole population, which resulted in an immediate increase in both incidence and the average age at transmission of both sources and recipients. The magnitude of this was 4.6 years (95% HDI: 2.17 - 6.24) for female recipients, 5.3 (95% HDI: 2.74 - 7.09) for male recipients, 5.24 (95% HDI: 2.78 - 6.97) for female sources, and 6.04 (95% HDI: 2.92 - 8.09) for male sources. These changes would be slow to reverse even after ART was restored. These findings indicate that substantial reductions in HIV incidence can be achieved through intensified testing and treatment of individuals aged under 35, and in particular young men, a group that drives the infection of younger women and for whom engagement with care remains disproportionately low.

Identifiers

PMID41867175
PMCPMC13004098

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