# Formative work for the development of an intervention to support combined HIV/syphilis self-testing and linkage to prevention and treatment services for transgender women in South Africa

> **NIH NIH R21** · UNIVERSITY OF COLORADO DENVER · 2024 · $211,326

## Abstract

ABSTRACT
In South Africa (SA), the country with the world's largest HIV epidemic, ~45.6% of transgender women (TW) may
be living with HIV. Of these, estimates show that 1/3 are not in treatment. Furthermore, there is low engagement
with HIV prevention behaviors, such as ever having an HIV test (20.5%) and pre-exposure prophylaxis (PrEP)
use (11%). Data on syphilis outcomes, which significantly increase risk for HIV and viral load if already living with
HIV, are unknown in this context; though one estimate of prevalence in SA TW is ~9%. Dual self-testing for HIV
and syphilis may be a promising strategy to improve SA TW's uptake of regular HIV/syphilis testing and linkage
to PrEP and/or HIV/syphilis treatment. Specifically, self-testing is overwhelmingly supported by stakeholders in
SA, the infrastructure to scale-up self-testing is in place and rapidly expanding, analyses show that this strategy
is life and cost-saving in SA, and PrEP and HIV/syphilis treatment are widely available. Also, self-testing may
address the unique social/structural barriers affecting regular testing and subsequent linkage to services for TW,
including transphobia, health system mistrust, discrimination, stigma, cost, and privacy concerns. Thus,
interventions to improve dual self-testing uptake and linkage to PrEP and/or HIV/syphilis treatment following a
self-test are urgently needed for SA TW. Yet, we must first address 3 critical gaps in our knowledge, since
findings from studies on self-testing and linkage in other groups do not extend to TW; formative work shows
TW's life context is unique, and affects self-testing/linkage differently. Gaps include TW's needs/preferences on:
self-test access and uptake; logistical support needed to correctly use/interpret self-tests; and linkage to and
uptake of PrEP and/or HIV/syphilis treatment following self-tests. Using the INSTI Multiplex, a dual blood-based
HIV/syphilis test that delivers results in 1-minute, we use mixed-methods to inform these knowledge gaps and
draft a dual self-testing and linkage to care intervention tailored to TW. Research takes place in Johannesburg,
SA, brings together a gender diverse team and community advisory board (CAB), and is informed by the Mensch
Model; work will occur in 3 stages. In Stage 1, we will conduct in-depth interviews (IDIs) with: N=15 TW and
N=15 healthcare workers (HCW) who care for TW. TW will use INSTI Multiplex in front of a study team member
to provide immediate feedback on logistical support needed to test/interpret results; they will also discuss
preferences on test access, and linkage. In Stage 2, we will enroll N=80 TW to complete self-administered web-
based surveys on their mobile phones. Surveys are developed from IDI themes and will identify TW's preferred
intervention strategy to address each domain. We will engage a data convergence process to ensure that
quantitative/qualitative findings inform one another. We will then draft the intervention using the 4 COM-B
Inter...

## Key facts

- **NIH application ID:** 10924846
- **Project number:** 1R21MH135779-01A1
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Christine Tagliaferri Rael
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $211,326
- **Award type:** 1
- **Project period:** 2024-07-15 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10924846

## Citation

> US National Institutes of Health, RePORTER application 10924846, Formative work for the development of an intervention to support combined HIV/syphilis self-testing and linkage to prevention and treatment services for transgender women in South Africa (1R21MH135779-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10924846. Licensed CC0.

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