Evidence map›Paper›PMID 42721221›Full record

ArticlePLoS medicine2026

HIV diagnosis and treatment status in individuals dying from HIV in Zimbabwe, Malawi, and South Africa: A model comparison analysis.

Loveleen Bansi-Matharu, Daniel T Citron, Rowan Martin-Hughes, Haroon Moolla, John Stover, Michael Pickles, Tara Mangal, Jenny Smith, Owen Mugurungi, Mmatlou Simeon Kubyana and 12 more

Abstract readComparative Study
In one paragraph

Article in PLoS medicine, 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

22 authors.

Loveleen Bansi-MatharuInstitute for Global Health, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0002-0233-7622
Daniel T CitronDepartment of Population Health, New York University Grossman School of Medicine, New York, New York, United States of America.ORCID https://orcid.org/0000-0002-1282-4176
Rowan Martin-HughesBurnet Institute, Melbourne, Australia.ORCID https://orcid.org/0000-0002-3724-2412
Haroon MoollaCentre for Integrated Data and Epidemiological Research, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0000-0001-7027-6297
John StoverAvenir Health, Takoma Park, Maryland, United States of America.ORCID https://orcid.org/0000-0001-7236-1989
Michael PicklesMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-6754-3945
Tara MangalMRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-9222-8632
Jenny SmithInstitute for Global Health, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0002-8809-8553
Owen MugurungiMinistry of Health & Child Welfare, Harare, Zimbabwe.
Mmatlou Simeon KubyanaDepartment of Decision Sciences, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0003-1324-2140
Isaac TaramusiUNAIDS UCO, Harare, Zimbabwe.ORCID https://orcid.org/0000-0002-5871-2874
Valentina CambianoInstitute for Global Health, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0003-0700-105X
Amon MpofuNational AIDS Council, Harare, Zimbabwe.
Debra Ten BrinkBurnet Institute, Melbourne, Australia.ORCID https://orcid.org/0000-0001-5938-6970
Edinah MudimuDepartment of Decision Sciences, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0002-5479-9255
Tsitsi ApolloMinistry of Health and Child Care, HIV Program, Harare, Zimbabwe.ORCID https://orcid.org/0000-0001-9881-0914
Anna BershteynDepartment of Population Health, New York University Grossman School of Medicine, New York, New York, United States of America.ORCID https://orcid.org/0000-0002-6604-7093
Linley ChewereDepartment of HIV, STI & Hepatitis, Ministry of Health, Lilongwe, Malawi.
Dobromir DimitrovPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America.ORCID https://orcid.org/0000-0002-2842-5436
Stephen MachesoUNICEF Country Office, Lilongwe, Malawi (SM).ORCID https://orcid.org/0009-0009-5133-3423
Leigh F JohnsonCentre for Integrated Data and Epidemiological Research, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-2717-011X
Andrew PhillipsInstitute for Global Health, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0003-2384-4807

Funding

SDMC: HPTN 084 Pregnancy SupplementUM1AI068617 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Elizabeth Renata Brown, Deborah J Donnell · 2011 to 2026
$204.9M
Bill & Melinda Gates Foundation INV-007145NIAID NIH HHS UM1 AI068617
6 · The paper itself

Abstract

backgroundAntiretroviral therapy (ART) has greatly reduced HIV-related mortality and improved life expectancy in sub-Saharan Africa since the early 2000s. However, HIV-related mortality remains high. To guide intervention priorities, we used seven established HIV simulation models to identify where in the HIV care cascade deaths occur in Zimbabwe, Malawi, and South Africa. This multi-model approach provided a more comprehensive and robust assessment than could be achieved using any single modelling approach. METHODS AND

findingsTo assess alignment, each model generated key HIV metrics from 2000 to 2045, including total population, HIV prevalence, annual new infections, and proportions of people with HIV (PWH) who were diagnosed, on ART, and virally suppressed. HIV-related deaths were estimated annually and categorised by whether they occurred in individuals who were (1) undiagnosed, (2) diagnosed but had not yet started ART, (3) on ART, or (4) had interrupted ART. The models showed strong consistency with population estimates and HIV prevalence across the different settings. There was, however, variation in the absolute number of HIV-related deaths between models; in Zimbabwe in 2025, this ranged from 3,666 to 17,475; in Malawi from 4,580 to 17,835; and in South Africa from 39,470 to 114,968. In Zimbabwe, all models consistently indicated that PWH receiving ART made up the largest proportion of HIV-related deaths, though this proportion differed across models, ranging from 35% to 64%. This was followed by HIV-related deaths amongst those who had interrupted ART, ranging from 17% to 29%. Similar trends were seen in Malawi. In South Africa, a high proportion of HIV-related deaths occurred amongst people who had interrupted ART (23% to 74% in 2025) as well as those who were currently receiving ART (23% to 56%). Models are reliant on empirical data and limited data availability-in this instance, lack of national death registries-is a key constraint on modelling studies.

conclusionAbsolute numbers of HIV-related deaths vary substantially between models, highlighting wider issues around ascertainment of death in the region. However, our results do consistently show that most deaths are occurring amongst PWH on ART in Zimbabwe and Malawi, and amongst those who have interrupted treatment in South Africa, suggesting interventions around adherence counselling and retention in care need to be prioritised.

Indexed as

Anti-HIV AgentsHIV InfectionsAdultFemaleHumansMalawiMalePrevalenceSouth AfricaYoung AdultZimbabweAnti-HIV Agents

Identifiers

PMID42721221
PMCPMC13561354

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.