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Enhancing HIV data systems in South Africa : integrating key population identifiers for inclusive health monitoring
Journal article   Open access   Peer reviewed

Enhancing HIV data systems in South Africa : integrating key population identifiers for inclusive health monitoring

Mashudu Rampilo, Edith Phalane, Edmond Mpho Shinwana, Regina Maithufi and Refilwe Nancy Phaswana-Mafuya
Population medicine, Vol.8(2), 7
2026
Handle:
https://hdl.handle.net/10210/521134

Abstract

HIV key populations South Africa
INTRODUCTION Accurate collection of sexual orientation and gender identity (SOGI) data is essential to identify and address disparities in the HIV treatment cascade. In many countries, routine health information management systems (RHIMS) record gender using limited categories such as ‘male’, ‘female’, or ‘unknown’, which fail to adequately capture the diversity of gender identities of transgender and gender-diverse populations. This study aimed to analyze the structure and content of the routine HIV program dataset within the South African routine health information management system for the inclusion of key population unique identifier codes. METHODS A retrospective, exploratory analysis was conducted using routinely collected HIV program data from Limpopo Province. The dataset comprised 37934 records of individuals who underwent HIV testing between April and June 2023. A cohort extract was obtained from the national standard TIER.Net system and analyzed to describe the structure and content of routine HIV data and to assess how the system supports cascade reporting. The analysis, performed in STATA 17, included descriptive statistical procedures such as frequencies, proportions, and crosstabulations to examine HIV testing outcomes, ART initiation, retention, and viral load monitoring. RESULTS The RHIMS comprised 37 934 records and 95 HIVrelated variables. The overall HIV positivity rate was 2.3%, with ART initiation at 94.6%, viral load testing at 93.9%, viral suppression at 85.1%, and 12-month retention at 61.2%. When comparing male and female outcomes, HIV positivity was 2.8% and 2.2%, ART initiation (94.5% and 96.2%), retention (59.3% and 60.0%), and viral suppression (79.8% and 88.2%), respectively. Disaggregation by sexual orientations could not be done as there were no unique identifiers for them. CONCLUSIONS The RHIMS allows only male–female disaggregation, which is limiting. Integrating key populations' unique identifier codes and gender identity would enable KP-specific data, supporting more targeted interventions, effective resource allocation, and stronger monitoring and evaluation for an inclusive HIV response.
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https://doi.org/10.18332/popmed/219979View
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