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Comparative Study
. 2025 Jun;13(6):e1006-e1019.
doi: 10.1016/S2214-109X(25)00121-4.

Identifying gaps in the HIV treatment cascade in Africa: a model comparison study

Loveleen Bansi-Matharu  1 , Haroon Moolla  2 , Daniel T Citron  3 , John Stover  4 , Michael Pickles  5 , Rowan Martin-Hughes  6 , Marie-Claude Boily  7 , Rose Nyirenda  8 , Edinah Mudimu  9 , Debra Ten Brink  6 , Leigh F Johnson  2 , Owen Mugurungi  10 , Valentina Cambiano  11 , Dobromir Dimitrov  12 , Jenny Smith  11 , Robert Glaubius  13 , Issac Taramusi  14 , Amon Mpofu  15 , Andrew Phillips  11 , Anna Bershteyn  3
Affiliations
Comparative Study

Identifying gaps in the HIV treatment cascade in Africa: a model comparison study

Loveleen Bansi-Matharu et al. Lancet Glob Health. 2025 Jun.

Abstract

Background: Although HIV incidence has considerably decreased in eastern, central, and southern Africa, new HIV infections continue to be a major public health challenge in the region. We aimed to investigate where in the HIV treatment cascade new transmissions are occurring in Malawi, Zimbabwe, and South Africa (the three countries involved in the Modelling to Inform HIV Programmes in Sub-Saharan Africa project).

Methods: In this model comparison study, we used six well described and independently calibrated HIV transmission dynamics models that have been used to inform HIV policy in Africa (Optima HIV, EMOD, Goals, Thembisa, PopART-IBM, and HIV Synthesis) to estimate and predict the proportion of annual new HIV transmissions attributable to people living with HIV who are undiagnosed, have been diagnosed but have not yet started antiretroviral therapy (ART), are receiving ART, and have interrupted ART in Malawi, Zimbabwe, and South Africa from 2010 to 2040 stratified by the age and sex of the individual acquiring HIV.

Findings: Despite the different model structures and underlying assumptions, the six models were well aligned in relation to key HIV epidemic characteristics (including population estimates and HIV prevalence) in each of the three settings. There was, however, considerable variation in the predicted number of new infections, particularly in Malawi and Zimbabwe where this number ranged from fewer than 10 000 new infections to over 30 000 new infections in 2024. Most model results suggested that the mean age of HIV acquisition has been increasing since 2000, with men acquiring HIV at an older age than women in all three settings. All models attributed fewer than 5% of transmissions to individuals who had been diagnosed but had not yet started ART. In Malawi, the proportion of transmissions attributable to undiagnosed people with HIV in 2024 ranged from 33·3% to 75·3% across the models, and transmissions attributable to individuals who had experienced interrupted treatment ranged from 8·4% to 20·1%. In Zimbabwe, the proportion of transmissions attributable to undiagnosed individuals in 2024 ranged from 29·8% to 64·6% across the models and the proportion of transmissions attributable to individuals who had interrupted treatment ranged from 4·7% to 21·5%. In South Africa, 21·8-46·4% of transmissions in 2024 were attributable to undiagnosed individuals and 27·6-58·9% of transmissions were attributable to individuals who had interrupted treatment.

Interpretation: Across the three study settings, a substantial proportion of new HIV transmissions were attributable to undiagnosed individuals and people who have received interrupted ART, reinforcing the importance of continuing HIV testing and ART re-engagement and retention interventions.

Funding: The Bill & Melinda Gates Foundation.

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Conflict of interest statement

Declaration of interests MCB has received funds paid to their institution from the US National Institutes of Health (NIH) for this study and from the Wellcome Trust not in relation to this study. AP has received funds paid to their institution from the Bill & Melinda Gates Foundation for this study, from the NIH, National Institute for Health and Care Research, Wellcome Trust, and EU Horizon paid to their institution not in relation to this study; and consulting fees from WHO. LBM has received funds paid to their institution from the Gates Foundation for this study, and from the Wellcome Trust and EU Horizon paid to their institution not in relation to this study; and consulting fees from WHO. AB has received funds paid to their institution from the Gates Foundation for this study, and from the NIH, Foundation for Innovative New Diagnostics, New York City Department of Health and Mental Hygiene, the Gates Foundation, and WHO not in relation to this study; and consulting fees from Gates Ventures. HM has received funds paid to their institution from the Gates Foundation for this study. VC has received funds paid to their institution from UK Research and Innovation not in relation to this study and consulting fees from Source Market Access. DD has received funds paid to their institution from NIH for this study, and from the NIH and US Centers for Disease Control and Prevention paid to their institution not in relation to this study. All other authors declare no competing interests.

Figures

Figure 1:
Figure 1:. HIV epidemic characteristics for adults aged 15–64 years in Malawi (A), Zimbabwe (B), and South Africa (C)
ART=antiretroviral therapy.
Figure 1:
Figure 1:. HIV epidemic characteristics for adults aged 15–64 years in Malawi (A), Zimbabwe (B), and South Africa (C)
ART=antiretroviral therapy.
Figure 1:
Figure 1:. HIV epidemic characteristics for adults aged 15–64 years in Malawi (A), Zimbabwe (B), and South Africa (C)
ART=antiretroviral therapy.
Figure 2:
Figure 2:. Mean age at HIV acquisition in Malawi, South Africa, and Zimbabwe
Figure 3:
Figure 3:. Treatment status of source partners in Malawi (A), Zimbabwe (B), and South Africa (C) by model
(A) Number of new infections in 2024: 30 582 infections in EMOD; 10 120 infections in Goals; 8459 infections in Optima HIV; and 22 689 infections in HIV Synthesis. *Goals did not differentiate between people who had been diagnosed and were treatment naive and those who had started treatment but had had it interrupted; these individuals were all classified as people not receiving treatment. (B) Number of new infections in 2024: 27 581 infections in PopART-IBM; 21 384 infections in Goals; 6772 infections in Optima HIV; and 30 536 infections in HIV Synthesis. (C) Number of new infections in 2024: 164 252 infections in Thembisa; 95 513 infections in Goals; 101 852 infections in Optima HIV; and 138 872 infections in HIV Synthesis.
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