A Review of Quality Management Systems in South African HIV-AIDS Programmes: A Pre-Requisite for Sustainable Health Delivery

The global commitment to end HIV-AIDS is a bold one; requiring a multi-sectoral response strongly embedded within effective HIV-AIDS prevention efforts, patient advocacy and effective healthcare programme delivery. UNAIDS estimates that, of the 36.7 million individuals infected with HIV-AIDS globally, 19.1 million reside in South Africa (UNAIDS Gap report, 2016).In addition, approximately 2.1 million new HIV infections occurred in 2015 with almost 960 000 of those occurring in South Africa signalling that the rates of infections are not dropping as expected (UNAIDS Gap report, 2016). Given the unrelenting nature of this disease burden, even greater efforts are now required to turn the tide on HIV-AIDS globally, but more so in South Africa. These efforts entail more effective HIV-AIDS service delivery with combination prevention modalities, access to HIV-AIDS treatment and care, harm reduction of HIV-AIDS stigma and discrimination together with HIV-AIDS education, awareness and advocacy. Enhancing HIV-AIDS service delivery requires strong commitment with implementation of quality management systems in programme service delivery resulting in sustainable, effective and well run HIV-AIDS programmes. Quality management systems in HIV-AIDS programmes allow programmes to successfully meet their objectives thus allowing optimal patient care through effective and efficient means. To date there has been minimal implementation of quality systems in healthcare especially in South Africa. The use of health quality tools and systems in HIV-AIDS programmes locally and globally will allow for efficient and cost effective benefits for the optimal wellbeing of all those affected and infected by HIV-AIDS. This article reviews available data on the prevalence of quality management systems in HIV-AIDS healthcare and identifies gaps and smart practises towards recommendations for comprehensive global HIV-AIDS standards development

Prevalence of HIV-1 Drug Resistance among Women Screening for HIV Prevention Trials in KwaZulu-Natal, South Africa (MTN-009)

Background:A major concern with using antiretroviral (ARV)-based products for HIV prevention is the potential spread of drug resistance, particularly from individuals who are HIV-infected but unaware of their status. Limited data exist on the prevalence of HIV infection or drug resistance among potential users of ARV-based prevention products.Methods:A cross-sectional study of reproductive-aged women who presented to screen for an HIV prevention trial was conducted at 7 clinical sites in Durban, South Africa. CD4+T cell counts, HIV-1 RNA levels and population sequencing of the protease and reverse transcriptase genes were performed for all women with 2 positive HIV rapid tests. Resistance mutations were identified using the Stanford Calibrated Population Resistance Tool.Results:Of the 1073 evaluable women, 400(37%) were confirmed as HIV-infected. Of those, plasma HIV-1 RNA was detectable in 365/400(91%) and undetectable(200 copies/ml) analyzed for drug resistance, 26(7.4%) had nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor (PI) drug resistance mutations. Among those with resistance, 18/26 participants(62%) had single-class NNRTI resistance and 5/26(19%) had dual-class NRTI/NNRTI. Major mutations in reverse transcriptase included K65R(n = 1), L74I(n = 1), K103N(n = 19), V106M(n = 4), Y181C(n = 2), M184V(n = 4), and K219E/R(n = 2). Major PI-resistance mutations were rare: M46L(n = 1) and I85V(n = 1). All participants were infected with subtype C virus, except one infected with subtype A.Conclusions:In women from Durban, South Africa screening for an HIV prevention trial, the HIV prevalence was high (37%) and HIV drug resistance prevalence was above 5%. This study highlights the potential challenges faced when implementing an ARV-based prevention product that overlaps with first-line antiretroviral therapy. Effective screening to exclude HIV infection among women interested in uptake of ARV-based HIV prevention will be essential in limiting the spread of ARV resistance

Tenofovir-based preexposure prophylaxis for HIV infection among African women.

CAPRISA, 2015.Abstract available in pdf

Characteristics associated with HIV drug resistance among women screening for an HIV prevention trial in KwaZulu-Natal, South Africa

While the expansion of antiretroviral therapy (ART) in sub-Saharan Africa has reduced morbidity and mortality from HIV/AIDS, it has increased concern about drug resistance. The Microbicide Trials Network 009 study assessed the prevalence of drug-resistance mutations among women at clinical sites in Durban, South Africa who tested seropositive for HIV-1 at screening for the VOICE trial. The objective of this paper was to identify characteristics and behaviors associated with drug resistance. Factors found to be significantly associated with increased resistance were high perceived risk of getting HIV and prior participation in a microbicide trial, a likely proxy for familiarity with the health care system. Two factors were found to be significantly associated with reduced resistance: having a primary sex partner and testing negative for HIV in the past year. Other variables hypothesized to be important in identifying women with resistant virus, including partner or friend on ART who shared with the participant and being given antiretrovirals during pregnancy or labor, or the proxy variable—number of times given birth in a health facility—were not significantly associated. The small number of participants with resistant virus and the probable underreporting of sensitive behaviors likely affected our ability to construct a comprehensive profile of the type of HIV-positive women at greatest risk of developing resistance mutations

CD4+ T Cell Counts and HIV-1 RNA Levels of HIV-1 Positive Participants.

<p>Histogram showing frequency of HIV positive participants (n = 400) that have (A) CD4+ T cell counts <200 cells/mm³ indicating risk for AIDS, 200–349 cells/mm³ indicating treatment eligibility, and >350 cells/mm³; and (B) varying levels of HIV-1 RNA (copies/ml).</p

Demographic Factors for All Evaluable Participants and the Subset that was HIV Positive and Tested for Drug Resistance in MTN-009.

<p>Notes: SD = Standard Deviation.</p

Major Drug Resistance Mutation Profiles Detected.

<p>Major Drug Resistance Mutation Profiles Detected.</p

Frequency of ARV Resistance Mutations.

<p>Histogram showing number of women with drug resistant HIV infection that had each of the following protease inhibitor (PI), nucleoside reverse transcriptase inhibitor (NRTI) or non-nucleoside reverse transcriptase inhibitor (NNRTI) mutations M46L, I85V, K65R, L74I, K219E, M184V, K101E, V106M, Y181C or G190A. Resistance mutations were identified using the Stanford Calibrated Population Resistance Tool.</p

Consort Diagram.

<p>Consort Diagram.</p