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Volume 22 Supplement 1

Innovating with HIV self-testing for impact in southern Africa: Lessons learned from the STAR (Self-Testing AfRica) Initiative

Reaching priority populations with different HIV self-testing distribution models in South Africa: an analysis of programme data

BMC Infectious Diseases volume 22, Article number: 981 (2022) Cite this article

Abstract

Background

As in much of sub-Saharan Africa, substantial HIV testing gaps remain in South Africa, particularly among adult men ages 20–35, young people ages 15–24 and key populations. Innovative strategies, such as HIV self-testing (HIVST), are needed to reach such under-served populations. We evaluated a range of HIV self-test kit distribution models’ potential to reach adult men, young people and key populations in South Africa, to inform targeted approaches.

Methods

This cross-sectional study used data from community and facility-based HIV self-test kit distribution models implemented from October 2017 to April 2020. Self-test kits were distributed as part of the Unitaid-funded Self-Testing AfRica (STAR) programme. Data were collected from individuals who obtained self-test kits through five distribution models. Frequencies and proportions were used to describe the characteristics of the study populations and self-test kit distribution approaches.

Results

Over 2.5 years, 1 071 065 self-test kits were distributed across the five models. Community-based distribution accounted for 63% of total kits distributed, while the private sector (primarily workplace) accounted for 26%. Distribution at public sector health facilities accounted for 7% and distribution through the key population and secondary distribution models accounted for 2% each. Of those obtaining kits, and for whom we collected previous testing data (n = 771 612, 72%), 11% had never tested for HIV, 29% had not tested for at least a year, 41% had tested within the last 4–12 months and 19% had tested within the preceding three months. More men (64%) than women obtained self-test kits across all distribution models. The majority (80%) of men obtaining self-test kits were aged 20–40 years, and primarily received these at public transport terminals (36%), workplaces (18%) and hotspots (14%). A small proportion of men was reached through female sex workers.

Conclusions

This analysis of programme data enabled us to identify HIV self-test kit distribution models that are best suited to reach specific priority and under-tested populations, particularly adult men and young people. Models/sub-models that reach self-test users where they live, work and spend time, are likely to result in higher HIVST uptake. Study findings can inform future HIVST scale-up in South Africa.

Background

Global (95–95-95) targets stipulate that 95% of all people living with the Human Immunodeficiency Virus (HIV) know their HIV status, 95% of all people with diagnosed HIV infection are on sustained treatment and, 95% of all people on HIV treatment are virally suppressed [1]. Several countries in sub-Saharan Africa (SSA), the epicentre of the HIV epidemic [2], are on track to achieve these targets, demonstrating that they are realistic. Aggregated data however mask substantial variations between both geographic areas and population groups [3, 4]. For example, key populations, including female sex workers (FSWs), men who have sex with men (MSM) and people who inject drugs; young people (15–24 years-old) and; adult general population men ages 20–35 – all groups at greatest risk of HIV acquisition – continue to lag behind at each stage of the HIV treatment (95–95-95) cascade [4,5,6,7].

Recent global estimates show that compared to women, 1 million, 1.8 million and 1.6 million more men living with HIV do not know their status, know their status but are not on treatment and are not virally suppressed, respectively [8]. Lower uptake of HIV testing and treatment among men in SSA is often due to poor utilisation of public sector health facilities, reflecting both structural and social health systems barriers [9,10,11]. Social norms around masculinity that emphasise toughness also contribute to an avoidance of health services [9, 11, 12]. Further, greater formal and informal employment among men compared to women hinder access due to job insecurity and high indirect and opportunity costs [6, 11, 13].

Young people experience unique barriers to standard HIV testing services (HTS) that contribute to low testing uptake. These include stigma around HIV testing, fear of disrespect by healthcare providers, concerns over confidentiality and issues of parental/guardian consent [9]. Likewise, key population groups experience pervasive and multi-factorial structural barriers to conventional HIV testing services (HTS), including community- and institutional-level stigma and discrimination [8, 14,15,16].

Similar to other SSA settings, variations in HIV testing and treatment access exist in South Africa, home to the highest number of people living with HIV globally [2, 17]. As elsewhere, a substantial HIV testing gap remains, particularly among men in general [9,10,11], young people and key populations including FSWs and MSM [8]. For example, evidence from district-level data in South Africa showed that MSM and FSWs living with HIV were consistently less likely to know their HIV-positive status than the general population. Innovative solutions and decentralised HTS are therefore required to get to these hard-to-reach and chronically under-tested populations. This is particularly so given a new set of ambitious but achievable targets for 2025 [18], and renewed commitment to target specific age and gender groups, key populations and geographic areas to ensure all population groups are equitably served by HIV prevention and treatment services to ultimately end AIDS by 2030 [18, 19].

HIV self-testing (HIVST), whereby someone performs the test and interprets the result themselves, was until 2020 not widely available in SSA due to concerns about accuracy, acceptability, feasibility, safety and costs [20]. It has now been recommended by WHO as an additional approach to increase HIV testing uptake following substantial evidence that it is a safe, acceptable and effective approach to increase access to, and uptake of, HIV testing and subsequently, treatment, care and prevention services [21,22,23,24,25,26,27,28,29,30]. HIVST is showing potential to overcome some of the barriers to conventional HIV testing services, including among under-tested populations such as young people, men and key populations in SSA [9, 31,32,33,34].

Here, we present data from the Population Services International and Ezintsha (Wits Reproductive Health and HIV Institute, South Africa) Self-Testing AfRica (STAR) initiative (October 2017 to April 2020). The initiative assessed the potential of varying HIV self-test kit distribution models and sub-models to reach adult men ages 20–35, young people (15–24 years-old) and key populations in South Africa. These data would inform targeted approaches needed to reach the remaining 12% of people with HIV in South Africa who are still unaware of their status [5].

Methods

In 2017, consortium partners in the second phase of the STAR initiative [35] conducted HIVST implementation research in Eswatini, Lesotho and South Africa through different distribution models, including workplace-, facility- and community-based approaches [36]. Distribution models were identified through various STAR consultative processes (e.g., feasibility studies, discreet choice experiments) [16, 37, 38]. Distribution approaches were adapted to the specific target populations (e.g., adult men, young people) to be reached. In South Africa, HIVST was also introduced into the private sector and into existing key populations programmes.

Description of distribution models and sub-models

HIVST implementation was through five self-test kit distribution models: community-based, private sector, public sector facility, secondary-based and distribution specifically targeting key populations. Three models comprised discrete distribution sub-models (community based, n = 4; private sector, n = 5 and secondary-based, n = 2). Table 1 contains a detailed description of the distribution models/sub-models and their implementation. Of note, some sub-models (e.g., ANC, transport hub (public transport terminal), workplace) were intentionally designed to target adult men 20–35 years-old, the age group at greatest risk of HIV acquisition in South Africa and other SSA settings [6, 9, 11]. All implementation as of December 2020 was subject to COVID-19 adaptations that occurred in the local context.

Table 1 Description of models and sub-models
Full size table

Data collection and management

Community health workers and distributors collected data using paper-based forms which were specific to each distribution model/sub-model. Each form included a minimum set of parameters including: age, gender, time since last HIV test, whether the test was assisted or unassisted, and whether the test kit was for a primary or secondary recipient. All data were transcribed onto an electronic case report form by a team of data entry clerks using REDCap, and stored on a secure password-protected server.

Data analysis

We used frequencies and percentages to describe the characteristics of HIV distribution and the demographic characteristics of self-test kit recipients by distribution model and sub-model. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Results

Characteristics of self-test kit distribution and recipients

A total of 1 071 065 self-test kits were distributed across the models/sub-models (Table 2). Nearly all distributed kits (99%) were oral-fluid-based, with the remainder (1%) being blood-based/finger prick. Self-test kit distribution peaked in 2018 and 2019 but dropped in 2020 due to lower targets during programme wind-down. The community-based distribution model accounted for nearly two-thirds (63%) of total kits distributed, with the highest number of self-test kit recipients reached through transport hubs (42%) and hotspots (18%) sub-models, while the private sector accounted for just over a quarter (26%) of distributed kits, largely through the workplace (23%) sub-model. Distribution through the public sector facility, secondary (ANC & index testing) and key population models accounted for 7%, 2% and 2%, respectively (Table 2). The least number of self-test kits, less than 1% each, were distributed through: Community-based: integrated HTS (mobile) (0.3%) as well as three Private sector sub-models: nurse-led (0.8%), pharmacy (0.6%) and general practitioner (GP) practice (0.04%) (Table 2).

Table 2 Characteristics of self-test kit distribution (N = 1 071 065)
Full size table

Self-test kit recipients’ gender, age by model/sub-model

We analysed characteristics of self-test kit recipients across and within models and sub-models. More males (64%) than females obtained self-test kits across nearly all the five distribution models (Table 3). The exception was public sector facility outpatient department (OPD) where more females obtained self-test kits. Across all five distribution models, the majority (80%) of males obtaining self-test kits were aged 20–40 years (Table 3). The sub-models with the highest proportions of males ages 20–40 were transport hub (36%), workplace (18%) and hotspots (14%) (Table 4). Of note, a small proportion of men (1%) was reached through female sex workers (Table 3).

Table 3 Demographic characteristics of self-test kit recipients by distribution model (N = 1 071 065)
Full size table
Table 4 Demographic characteristics of self-test kit recipients by distribution sub-model (N = 1 071 065)
Full size table

Nearly a quarter (n = 261 846, 24%) of all self-test kit recipients were adolescents and young people aged 15–24 years (Table 3). The sub-models with the highest proportions of 15–24 year-olds were transport hub (10%), hotspots (5%) and workplace (4%) (Table 4).

Self-test kit recipients’ previous testing by model

Of those obtaining self-test kits and for whom we collected previous testing data (n = 771 612, 72%), 11% had never tested for HIV, 29% had not tested for at least a year, 41% had tested within the last 4–12 months and 19% had tested within the preceding three months (Table 3). Compared to the secondary (ANC and index testing) (4%) and key population (1%) models, the private sector, community-based and health facility OPD distribution approaches reached relatively high numbers of individuals with HIVST who had never tested for HIV (8% for all three models) (Table 3). Of note, key population and secondary (ANC and index testing) models had a high number of missing data for this variable (90% and 71%, respectively) (Table 3).

Discussion

Our analysis of programme data for the period October 2017 to April 2020 has shown a high rate of HIV self-test kit distribution (> 1 million kits over 2.5 years) in South Africa across a variety of models and during routine service provision. These data add to the growing evidence on the feasibility and acceptability of this testing approach. The majority of kits (63%) were distributed through the community-based distribution model, mostly via the transport hub and hotspots sub-models, highlighting the practicality of using these approaches for further scale up.

Across models, 11% of self-test kit recipients for whom we collected previous testing data had never tested for HIV, highlighting the importance of HIV self-testing in reaching previously untested individuals, some of whom may not have tested otherwise [9]. While the proportion of first-time testers reached in this programme appears lower than reported in previous studies [9], this likely reflects how challenging reaching this group might become as countries are nearing achievement of global targets. When considering the high volume of kits distributed, however, this suggests that wide-scale HIVST programming continues to be an important strategy for SSA in general and South Africa, specifically in working towards achieving the first 95 of the 95–95-95 targets [1].

Data on models/sub-models that reach higher proportions of specific population groups will be critical in closing the HIV testing gap that remains, among men in general [9, 10] and key populations including sex workers and MSM [8]. Achieving greater coverage of diagnosis, treatment and viral suppression among men is not only important for their own health, but also reduces the risk of HIV transmission to female partners [3, 39]. HIVST strategies that reached men were a key focus of this programme and models that witnessed the highest number of kits distributed were transport hub, workplace and hotspots. These findings are unsurprising as the programme conducted specific outreach to men, and previous studies have reported similar results [9]. The workplace model implemented in this programme is now recognised as a particularly useful way to reach men [40, 41]. Given that men are recognised i) as constituting the greatest gap in HIV services in SSA in general and South Africa, specifically [2], ii) for avoiding health facilities [42], using a combination of non-facility-based testing approaches to reach this group is an urgent necessity [39].

We also explored the feasibility of reaching men with HIVST through their female sexual partners. A small proportion of males were reached with HIVST through female sex workers. This secondary distribution model has not yet been strongly demonstrated by programme data. Our data add to the growing evidence on how HIVST could be an effective tool to improve access to, and frequency of, HIV testing among sex workers’ clients and other sexual partners [33, 43, 44]. However, given the potential risks HIVST may pose to sex workers, who are particularly vulnerable to violence [31, 44] it is crucial to involve sex worker networks and communities in the design of these approaches.

Adolescents and young people (ages 15–24) continue to be an important group to be reached with HIV services including HIV testing in SSA. Here, six in seven new HIV infections among adolescents (aged 15–19 years) are among girls, and young women (ages 15–24) are twice as likely to be living with HIV than their male counterparts [8, 45, 46]. Further, adolescent girls and young women (AGYW, ages 15–24) accounted for 25% of HIV infections in 2020, despite representing just 10% of the population [8]. AGYW therefore need access to HIVST throughout periods of risk and, in the form of flexible delivery. Although we are unable to delineate the sub-models that were effective at specifically reaching AGYW, programme data showed HIVST’s utility in reaching adolescents and young people overall, with 24% of all distributions reaching this group. The sub-models with the highest proportions of 15–24 year-olds were transport hub, hotspots and workplace; these can be utilised going forward.

HIVST may be a critical entry point for other sexual and reproductive health and HIV services for young people, including family planning and pre-exposure prophylaxis (PrEP). WHO now recommends self-testing as an important tool for differentiated service delivery of PrEP (oral PrEP and Dapivirine Vaginal Ring) both to optimise delivery and enable more people to access PrEP [24]. Further implementation research is needed to guide programmes on how best to scale-up this strategy and measure its impact toward PrEP targets and the global goal to reduce annual new HIV infections to 370,000 by 2025 [18].

With a high number of distributed kits (> 1 million), we were able to make substantial inferences. A limitation is that self-test kit distribution approaches used were intentionally designed to target specific priority populations such as adult men who are generally less likely to have tested compared to women; thus, these findings should be considered in this context and other programmes without targeting may have different results. In addition, some sub-models had a high number of missing data for some variables, which made it difficult to derive certain inferences. Also, due to pragmatic reasons, we followed up the HIVST result for some clients/sub-models and not others, a factor which influences observed positivity rates. Finally, we did not explore the findings in-depth (e.g., qualitatively), which would have provided context and nuances.

Conclusions

This analysis of programme data enabled us to identify self-test kit distribution models which could be used to reach men 20–35 years old and young people, groups at greatest risk of HIV acquisition in both South Africa and much of SSA. The data suggest that models/sub-models that reach targeted groups where they live, work and spend time, are likely to result in higher HIVST uptake. Study findings will be important in ensuring the scale-up of HIVST in South Africa is tailored to meet the needs of different population groups. Study findings are relevant to all programmes, government departments and implementers involved in scaling up HIVST.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AGYW :

Adolescent girls and young women

ANC:

Antenatal care

ART:

Antiretroviral therapy

FSW:

Female sex worker

GP:

General practitioner

HIV:

Human immunodeficiency virus

HIVST:

HIV self-testing

HTS:

HIV testing services

MSM:

Men who have sex with men

OPD:

Outpatient department

PrEP:

Pre-exposure prophylaxis

RDT:

Rapid Diagnostic Test

SSA :

Sub-Saharan Africa

STAR:

Self-Testing AfRica

STI:

Sexually Transmitted Infection

WHO:

World Health Organisation

References

  1. UNAIDS: Understanding Fast-Track: Accelerating Action to End the AIDS Epidemic by 2030. Geneva: Joint United Nations Programme on HIV/AIDS; 2015. Available: https://www.unaids.org/en/resources/documents/2015/201506_JC2743_Understanding_FastTrack.

  2. Cornell M, Majola M, Johnson LF, Dubula-Majola V. HIV services in sub-Saharan Africa: the greatest gap is men. Lancet. 2021;397(10290):2130–2.

    Article  PubMed  Google Scholar 

  3. Giguere K, Eaton JW, Marsh K, Johnson LF, Johnson CC, Ehui E, Jahn A, Wanyeki I, Mbofana F, Bakiono F, et al. Trends in knowledge of HIV status and efficiency of HIV testing services in sub-Saharan Africa, 2000–20: a modelling study using survey and HIV testing programme data. Lancet HIV. 2021;8(5):e284–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. UNAIDS: IN DANGER: UNAIDS Global AIDS Update 2022. Geneva: Joint United Nations Programme on HIV/AIDS; 2022. Available: https://www.unaids.org/en/resources/documents/2022/in-danger-global-aids-update.

  5. UNAIDS: The path that ends AIDS: UNAIDS Global AIDS Update 2023. Geneva: Joint United Nations Programme on HIV/AIDS; 2023. Available: https://www.unaids.org/en/resources/documents/2023/global-aids-update-2023.

  6. Mavhu W, Neuman M, Hatzold K, Buzuzi S, Maringwa G, Chabata ST, Mangenah C, Taruberekera N, Madidi N, Munjoma M et al: Innovative demand creation strategies to increase voluntary medical male circumcision uptake: a pragmatic randomised controlled trial in Zimbabwe. BMJ Glob Health 2021, 6(Suppl 4).

  7. Cowan FM, Machingura F, Ali MS, Chabata ST, Takaruza A, Dirawo J, Makamba M, Hove T, Bansi-Matharu L, Matambanadzo P, et al. A risk-differentiated, community-led intervention to strengthen uptake and engagement with HIV prevention and care cascades among female sex workers in Zimbabwe (AMETHIST): a cluster randomised trial. Lancet Glob Health. 2024;12(9):e1424–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. UNAIDS: UNAIDS Global AIDS Update-Confronting inequalities: lessons for pandemic responses from 40 years of AIDS. Geneva: Joint United Nations Programme on HIV/AIDS; 2021. Available: https://www.unaids.org/en/resources/documents/2021/2021-global-aids-update.

  9. Hatzold K, Gudukeya S, Mutseta MN, Chilongosi R, Nalubamba M, Nkhoma C, Munkombwe H, Munjoma M, Mkandawire P, Mabhunu V et al: HIV self-testing: breaking the barriers to uptake of testing among men and adolescents in sub-Saharan Africa, experiences from STAR demonstration projects in Malawi, Zambia and Zimbabwe. J Int AIDS Soc 2019, 22 Suppl 1(Suppl Suppl 1):e25244.

  10. Cornell M, Cox V, Wilkinson L. Public health blindness towards men in HIV programmes in Africa. Trop Med Int Health. 2015;20(12):1634–5.

    Article  PubMed  Google Scholar 

  11. Mavhu W, Makamba M, Hatzold K, Maringwa G, Takaruza A, Mutseta M, Ncube G, Cowan FM, Sibanda EL. Preferences for oral-fluid-based or blood-based HIV self-testing and provider-delivered testing: an observational study among different populations in Zimbabwe. BMC Infect Dis. 2023;22(Suppl 1):973.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Dovel K, Yeatman S, Watkins S, Poulin M. Men’s heightened risk of AIDS-related death: the legacy of gendered HIV testing and treatment strategies. AIDS. 2015;29(10):1123–5.

    Article  PubMed  Google Scholar 

  13. Mangenah C, Mavhu W, Garcia DC, Gavi C, Mleya P, Chiwawa P, Chidawanyika S, Ncube G, Xaba S, Mugurungi O et al: Relative efficiency of demand creation strategies to increase voluntary medical male circumcision uptake: a study conducted as part of a randomised controlled trial in Zimbabwe. BMJ Glob Health 2021, 6(Suppl 4).

  14. Lora WS, Desmond N, Obasi A, Kumwenda M, Taegtmeyer M, Tolhurst R, MacPherson EE. “I wanted evidence that my status had changed, so that is why I tested”: experiences with HIV self-testing among female sex workers in Malawi. AIDS Care. 2020;32(sup2):206–13.

    Article  PubMed  Google Scholar 

  15. Witzel TC, Eshun-Wilson I, Jamil MS, Tilouche N, Figueroa C, Johnson CC, Reid D, Baggaley R, Siegfried N, Burns FM, et al. Comparing the effects of HIV self-testing to standard HIV testing for key populations: a systematic review and meta-analysis. BMC Med. 2020;18(1):381.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kumwenda MK, Mavhu W, Lora WS, Chilongosi R, Sikwesese S, Taegtmeyer M. Feasibility and acceptability of a peer-led HIV self-testing model among female sex workers in Malawi: a qualitative study. BMJ Open. 2021;11(12): e049248.

    Article  PubMed Central  Google Scholar 

  17. Pillay Y, Johnson L. World AIDS Day 2020: Reflections on global and South African progress and continuing challenges. South Afr J HIV Med. 2021;22(1):1205.

    Article  PubMed  PubMed Central  Google Scholar 

  18. UNAIDS: Global AIDS Strategy 2021-2026: End Inequalities, End AIDS. Geneva: Joint United Nations Programme on HIV/AIDS; 2021. Available: https://www.unaids.org/en/resources/documents/2021/2021-2026-global-AIDS-strategy.

  19. Mahy MI, Sabin KM, Feizzadeh A, Wanyeki I. Progress towards 2020 global HIV impact and treatment targets. J Int AIDS Soc. 2021;24(Suppl 5): e25779.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Gupta-Wright A, Barnabas RV, Ingold H, Duneton P, Abubakar I: HIV self-testing: lessons learnt and priorities for adaptation in a shifting landscape. BMJ Glob Health 2021, 6(Suppl 4).

  21. WHO: Consolidated guidelines on HIV testing services, 2019. Geneva: World Health Organization; 2020: Available: https://iris.who.int/handle/10665/336323.

  22. Eshun-Wilson I, Jamil MS, Witzel TC, Glidded DV, Johnson C, Le Trouneau N, Ford N, McGee K, Kemp C, Baral S, et al. A Systematic Review and Network Meta-analyses to Assess the Effectiveness of Human Immunodeficiency Virus (HIV) Self-testing Distribution Strategies. Clin Infect Dis. 2021;73(4):e1018–28.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Jamil MS, Eshun-Wilson I, Witzel TC, Siegfried N, Figueroa C, Chitembo L, Msimanga-Radebe B, Pasha MS, Hatzold K, Corbett E, et al. Examining the effects of HIV self-testing compared to standard HIV testing services in the general population: A systematic review and meta-analysis. EClinicalMedicine. 2021;38: 100991.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kiptinness C, Kuo AP, Reedy AM, Johnson CC, Ngure K, Wagner AD, Ortblad KF. Examining the Use of HIV Self-Testing to Support PrEP Delivery: a Systematic Literature Review. Curr HIV/AIDS Rep. 2022;19(5):394–408.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lee VJ, Tan SC, Earnest A, Seong PS, Tan HH, Leo YS. User acceptability and feasibility of self-testing with HIV rapid tests. J Acquir Immune Defic Syndr. 2007;45(4):449–53.

    Article  PubMed  Google Scholar 

  26. Lippman SA, Moran L, Sevelius J, Castillo LS, Ventura A, Treves-Kagan S, Buchbinder S. Acceptability and Feasibility of HIV Self-Testing Among Transgender Women in San Francisco: A Mixed Methods Pilot Study. AIDS Behav. 2016;20(4):928–38.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ngoc BV, Majam M, Green K, Tran T, Hung MT, Que AL, Ngoc DB, Le Duy CH. Acceptability, feasibility, and accuracy of blood-based HIV self-testing: A cross-sectional study in Ho Chi Minh City. Vietnam PLOS Glob Public Health. 2023;3(2): e0001438.

    Article  PubMed  Google Scholar 

  28. Tao J, Li MY, Qian HZ, Wang LJ, Zhang Z, Ding HF, Ji YC, Li DL, Xiao D, Hazlitt M, et al. Home-based HIV testing for men who have sex with men in China: a novel community-based partnership to complement government programs. PLoS ONE. 2014;9(7): e102812.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Volk JE, Lippman SA, Grinsztejn B, Lama JR, Fernandes NM, Gonzales P, Hessol NA, Buchbinder S. Acceptability and feasibility of HIV self-testing among men who have sex with men in Peru and Brazil. Int J STD AIDS. 2016;27(7):531–6.

    Article  PubMed  Google Scholar 

  30. O’Reilly A, Mavhu W, Neuman M, Kumwenda MK, Johnson CC, Sinjani G, Indravudh P, Choko A, Hatzold K, Corbett EL. Accuracy of and preferences for blood-based versus oral-fluid-based HIV self-testing in Malawi: a cross-sectional study. BMC Infect Dis. 2024;22(Suppl 1):979.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Napierala S, Desmond NA, Kumwenda MK, Tumushime M, Sibanda EL, Indravudh P, Hatzold K, Johnson CC, Baggaley RC, Corbett L, et al. HIV self-testing services for female sex workers, Malawi and Zimbabwe. Bull World Health Organ. 2019;97(11):764–76.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Okoboi S, Lazarus O, Castelnuovo B, Nanfuka M, Kambugu A, Mujugira A, King R. Peer distribution of HIV self-test kits to men who have sex with men to identify undiagnosed HIV infection in Uganda: A pilot study. PLoS ONE. 2020;15(1): e0227741.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Shava E, Bogart LM, Manyake K, Mdluli C, Maribe K, Monnapula N, Nkomo B, Mosepele M, Moyo S, Mmalane M, et al. Feasibility of oral HIV self-testing in female sex workers in Gaborone, Botswana. PLoS ONE. 2021;16(11): e0259508.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mekonnen H, Manyazewal T, Kajogoo VD, Getachew Assefa D, Gugsa Bekele J, Tolossa Debela D. Advances in HIV self-testing: Systematic review of current developments and the road ahead in high-burden countries of Africa. SAGE Open Med. 2024;12:20503121231220788.

    Article  PubMed  Google Scholar 

  35. Ingold H, Mwerinde O, Ross AL, Leach R, Corbett EL, Hatzold K, Johnson CC, Ncube G, Nyirenda R, Baggaley RC. The Self-Testing AfRica (STAR) Initiative: accelerating global access and scale-up of HIV self-testing. J Int AIDS Soc. 2019;22(Suppl 1): e25249.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Matsimela K, Sande LA, Mostert C, Majam M, Phiri J, Zishiri V, Madondo C, Khama S, Chidarikire T, d'Elbee M et al: The cost and intermediary cost-effectiveness of oral HIV self-test kit distribution across 11 distribution models in South Africa. BMJ Glob Health 2021, 6(Suppl 4).

  37. Indravudh PP, Sibanda EL, d’Elbée M, Kumwenda MK, Ringwald B, Maringwa G, Simwinga M, Nyirenda LJ, Johnson CC, Hatzold K, et al. ‘I will choose when to test, where I want to test’: investigating young people’s preferences for HIV self-testing in Malawi and Zimbabwe. AIDS. 2017;31(Suppl 3):S203–12.

    Article  PubMed  Google Scholar 

  38. Sibanda EL, d'Elbee M, Maringwa G, Ruhode N, Tumushime M, Madanhire C, Ong JJ, Indravudh P, Watadzaushe C, Johnson CC et al: Applying user preferences to optimize the contribution of HIV self-testing to reaching the "first 90" target of UNAIDS Fast-track strategy: results from discrete choice experiments in Zimbabwe. J Int AIDS Soc 2019, 22 Suppl 1(Suppl Suppl 1):e25245.

  39. Sibanda EL, Mavhu W. Secondary HIV self-test distribution increases male partner testing. Lancet Glob Health. 2021;9(12):e1632–3.

    Article  CAS  PubMed  Google Scholar 

  40. WHO and ILO: Policy Brief: HIV self-testing at workplaces: approaches to implementation and sustainable financing. Geneva: World Health Organization & International Labour Organization; 2022. Available: https://iris.who.int/bitstream/handle/10665/354358/9789240040632-eng.pdf.

  41. Nsereko GM, Musanje K, Ayesiga ER, Kobusingye LK, Namubiru R, Sempala M, Kiwala C, Baluku MM. A workplace-based HIV self-testing intervention as a determinant for self-testing knowledge, beliefs, and use among unskilled workers in Wakiso Uganda. BMC Public Health. 2025;25(1):187.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Baker P, Dworkin SL, Tong S, Banks I, Shand T, Yamey G. The men’s health gap: men must be included in the global health equity agenda. Bull World Health Organ. 2014;92(8):618–20.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Ky-Zerbo O, Desclaux A, Boye S, Vautier A, Rouveau N, Kouadio BA, Fotso AS, Pourette D, Maheu-Giroux M, Sow S, et al. Willingness to use and distribute HIV self-test kits to clients and partners: A qualitative analysis of female sex workers’ collective opinion and attitude in Cote d’Ivoire, Mali, and Senegal. Womens Health (Lond). 2022;18:17455057221092268.

    Article  CAS  PubMed  Google Scholar 

  44. Mee P, Neuman M, Kumwenda M, Lora WS, Sikwese S, Sambo M, Fielding K, Indravudh PP, Hatzold K, Johnson C, et al. Experience of social harms among female sex workers following HIV self-test distribution in Malawi: results of a cohort study. BMC Infect Dis. 2024;22(Suppl 1):978.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Mavhu W, Rowley E, Thior I, Kruse-Levy N, Mugurungi O, Ncube G, Leclerc-Madlala S. Sexual behavior experiences and characteristics of male-female partnerships among HIV positive adolescent girls and young women: Qualitative findings from Zimbabwe. PLoS ONE. 2018;13(3): e0194732.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Mupambireyi Z, Simms V, Mavhu W, Mutasa C, Matsikire E, Ricotta A, Pascoe M, Shamu T, Senzanje B, Pierotti C, et al. Clinical and psychosocial context of HIV perinatally infected young mothers in Harare, Zimbabwe: A longitudinal mixed-methods study. PLoS ONE. 2025;20(1): e0315299.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The study was run by Ezintsha (Wits Reproductive Health and HIV Institute) staff and undertaken in collaboration with the NDOH, UNITAID, PSI, SFH, CHAI, WHO and the HIV Self-Testing Africa Research Consortium institutions. The authors would like to thank all their implementing partners and study participants in South Africa.

About this supplement

This article has been published as part of BMC Infectious Diseases Volume 22 Supplement 1 2021: Innovating with HIV self-testing for impact in southern Africa: Lessons learned from the STAR (Self-Testing AfRica) Initiative. The full contents of the supplement are available at https://biomedcentral-bmcinfectdis.publicaciones.saludcastillayleon.es/articles/supplements/volume-22-supplement-1.

Funding

Unitaid as part of the STAR Initiative, grant number 2017–17-SFH-STAR. Unitaid is a hosted partnership of the World Health Organisation. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

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Authors and Affiliations

  1. Ezintsha, a division of the Wits Health Consortium, University of the Witwatersrand, Johannesburg, South Africa

    Mohammed Majam, Angela Tembo, Vincent Zishiri, Jane Phiri & Francois Venter

  2. Population Services International, Cape Town, South Africa

    Karin Hatzold & Sangiwe Moyo

  3. Centre for Sexual Health and HIV/AIDS Research (CeSHHAR) Zimbabwe, Harare, Zimbabwe

    Webster Mavhu

  4. Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, UK

    Webster Mavhu

  5. Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA

    Donaldson Conserve

  6. Department of Social Medicine, Ohio University Heritage College of Osteopathic Medicine, Dublin, OH, USA

    Zelalem Haile

  7. HIV Prevention Department, National Department of Health, Pretoria, South Africa

    Thato Chidarikire

  8. Global HIV, Hepatitis and STI Programmes, World Health Organisation, Geneva, Switzerland

    Cheryl C. Johnson

  9. Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Gesine Meyer-Rath

  10. School of Public Health, Boston University, Boston, MA, USA

    Gesine Meyer-Rath

Authors
  1. Mohammed Majam
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  2. Karin Hatzold
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  3. Webster Mavhu
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  4. Angela Tembo
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  13. Francois Venter
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Contributions

MM, KH and FV were responsible for the conceptual design of the study. MM, AT, VZ, JP, TC, SM, KH and FV contributed to the initial design of the study. MM, AT, VZ, and JP collected data. MM, JP, DC, and ZH cleaned and analysed data. TC, CCJ, SM, KH, GMR and FV provided guidance throughout data collection, cleaning, and analysis. MM, KH, and WM wrote the paper, and all authors were involved in the review of drafts. All authors have approved the final manuscript.

Corresponding author

Correspondence to Mohammed Majam.

Ethics declarations

Ethics approval and consent to participate

Ethical approval was granted by the University of the Witwatersrand Human Research Ethics Committee (#180405). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The programme put in place a range of measures to deal with any social harms, including engaging social harm specialists, psychologists and law enforcement agencies. Potential social harms were explained to HIVST kit recipients, together with measures to take if such harms occurred, including contacting study counsellors using toll free numbers.

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Majam, M., Hatzold, K., Mavhu, W. et al. Reaching priority populations with different HIV self-testing distribution models in South Africa: an analysis of programme data. BMC Infect Dis 22 (Suppl 1), 981 (2022). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12879-025-10662-7

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BMC Infectious Diseases

ISSN: 1471-2334

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