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HIV-1 drug resistance (HIVDR) impedes treatment and control of HIV-1, especially in high-prevalence settings such as KwaZulu-Natal (KZN) province, South Africa. This study merged routine HIV-1 genotypic resistance test (GRT) data with Geographic Information Systems coordinates to assess patterns and geographic distribution of HIVDR in KZN, among ART-experienced adults with virological failure. We curated 3133 GRT records generated between 1 January 2018 and 30 June 2022, which includes the early phase of dolutegravir (DTG) rollout, of which 2735 (87.30%) had HIVDR. Of the 2735, major protease, nucleoside, and non-nucleoside reverse transcriptase inhibitor mutations were detected in 41.24%, 84.97% and 88.08% of GRTs, respectively. Additional genotyping of HIV-1 integrase for 41/3133 (1.31%) GRTs showed that 17/41 (41.46%) had integrase strand transfer inhibitor resistance. Notably, of 26 patients on DTG with integrase genotyping, 9 (34.62%) had DTG-associated resistance mutations. Dual- or triple-class resistance was observed in four of every five GRTs. The odds of HIVDR increased significantly with age, with ≥60 years having 5 times higher odds of HIVDR compared to 18–29 years (p = 0.001). We identified geospatial differences in the burden of HIVDR, providing proof of concept that this could be used for data-driven public health decision making. Ongoing real-time HIVDR surveillance is essential for evaluating the outcomes of the updated South African HIV treatment programme.

South Africa rolled out dolutegravir (DTG) as first-line antiretroviral therapy (ART) in December 2019 to overcome high rates of pretreatment non-nucleoside reverse transcriptase inhibitor drug resistance. In the context of transition to DTG-based ART, this study spatiotemporally analysed detectable HIV viral loads (VLs) prior to- and following DTG rollout in public-sector healthcare facilities in KwaZulu-Natal (KZN) province, the epicentre of the HIV epidemic in South Africa. We retrospectively curated a HIV VL database using de-identified routine VL data obtained from the National Health Laboratory Service for the period January 2018 to June 2022. We analysed trends in HIV viraemia and mapped median log10 HIV VLs per facility on inverse distance weighted interpolation maps. We used Getis-Ord Gi* hotspot analysis to identify geospatial HIV hotspots. We obtained 7,639,978 HIV VL records from 736 healthcare facilities across KZN, of which 1,031,171 (13.5%) had detectable VLs (i.e., VLs ≥400 copies/millilitre (mL)). Of those with detectable VLs, we observed an overall decrease in HIV VLs between 2018 and 2022 (median 4.093 log10 copies/mL; 95% confidence interval (CI) 4.087-4.100 to median 3.563 log10 copies/mL; CI 3.553-3.572), p

Abstract Background As use of dolutegravir (DTG) becomes more common in resource limited settings (RLS), the demand for integrase resistance testing is increasing. Affordable methods for genotyping all relevant HIV-1 pol genes (i.e., protease (PR), reverse transcriptase (RT) and integrase (IN)) are required to guide choice of future antiretroviral therapy (ART). We designed an in-house HIV-1 drug resistance (HIVDR) genotyping method that is affordable and suitable for use in RLS. Methods We obtained remnant plasma samples from CAPRISA 103 study and amplified HIV-1 PR, RT and IN genes, using an innovative PCR assay. We validated the assay using remnant plasma samples from an external quality assessment (EQA) programme. We genotyped samples by Sanger sequencing and assessed HIVDR mutations using the Stanford HIV drug resistance database. We compared drug resistance mutations with previous genotypes and calculated method cost-estimates. Results From 96 samples processed, we obtained sequence data for 78 (81%), of which 75 (96%) had a least one HIVDR mutation, with no major-IN mutations observed. Only one sample had an E157Q INSTI-accessory mutation. When compared to previous genotypes, 18/78 (23%) had at least one discordant mutation, but only 2/78 (3%) resulted in different phenotypic predictions that could affect choice of subsequent regimen. All CAPRISA 103 study sequences were HIV-1C as confirmed by phylogenetic analysis. Of the 7 EQA samples, 4 were HIV-1C, 2 were HIV-1D, and 1 was HIV-1A. Genotypic resistance data generated using the IDR method were 100% concordant with EQA panel results. Overall genotyping cost per sample was estimated at ~ US$43–$US49, with a processing time of ~ 2 working days. Conclusions We successfully designed an in-house HIVDR method that is suitable for genotyping HIV-1 PR, RT and IN genes, at an affordable cost and shorter turnaround time. This HIVDR genotyping method accommodates changes in ART regimens and will help to guide HIV-1 treatment decisions in RLS.

The most common HIV-1 subtype in South Africa is subtype C, and detection of other subtypes is rare. We report the first known case of HIV-1 subtype CRF18_cpx identified in KwaZulu-Natal, South Africa, the epicenter of the HIV epidemic, through HIV drug resistance genotyping.The 31-year-old female patient was initiated on fixed dose combination (tenofovir, emtricitabine, efavirenz) in 2017, with failure to achieve virologic suppression. Change to second-line antiretroviral therapy (tenofovir, emtricitabine and ritonavir-boosted lopinavir) was made in 2018. Adherence was impacted by lopinavir-induced diarrhoea. In 2020, she was switched to zidovudine, lamivudine and ritonavir-boosted atazanavir. Virologic failure persisted, and HIV drug resistance genotyping in April 2021 showed multidrug resistance. Third-line regimen (tenofovir, lamivudine, dolutegravir and ritonavir-boosted darunavir) was commenced in May 2021 and virologic suppression was achieved.Co-incidentally we discovered from the HIV drug resistance sequence report that the patient was infected with HIV-1 subtype CRF18_cpx. Analysis of the HIV sequence using REGA HIV-1 Subtyping Tool confirmed sequence subtype assignment as HIV-1 CRF 18_cpx (bootstrap confidence = 90%). Subtyping was also confirmed with the COMET HIV-1 tool, HIV BLAST tool and phylogenetic analysis.Based on our incidental finding, CRF18_cpx may be circulating locally as the patient had no travel history. Introduction of non-subtype C and recombinant viruses are expected to have increased in South Africa due to increased travel. This highlights the need to characterize subtype diversity in South Africa, particularly in KwaZulu-Natal, as HIV subtype can influence pathogenesis, treatment response, drug resistance and efforts towards vaccine development.

Background: KwaZulu-Natal ranked second highest among South African provinces for the number of laboratory-confirmed cases during the second wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The seroprevalence of SARS-CoV-2 among certain vulnerable groups, such as people living with HIV in KwaZulu-Natal, is unknown. Objective: The study aimed to determine the prevalence of SARS-CoV-2 immunoglobulin G (IgG) in HIV-positive versus HIV-negative patients. Methods: This was a retrospective analysis of residual clinical blood specimens unrelated to coronavirus disease 2019 (COVID-19) submitted for diagnostic testing at Inkosi Albert Luthuli Central Hospital, Durban, from 10 November 2020 to 09 February 2021. Specimens were tested for SARS-CoV-2 immunoglobulin G on the Abbott Architect analyser. Results: A total of 1977/8829 (22.4%) specimens were positive for SARS-CoV-2 antibodies. Seroprevalence varied between health districts from 16.4% to 37.3%, and was 19% in HIV-positive and 35.3% in HIV-negative specimens. Seroprevalence was higher among female patients (23.6% vs 19.8%; p 0.0001) and increased with increasing age, with a statistically significant difference between the farthest age groups ( 10 years and 79 years; p 0.0001). The seroprevalence increased from 17% on 10 November 2020 to 43% on 09 February 2021 during the second wave. Conclusion: Our results highlight that during the second COVID-19 wave in KwaZulu-Natal a large proportion of people living with HIV were still immunologically susceptible. The reduced seropositivity in people with virological failure further emphasises the importance of targeted vaccination and vaccine response monitoring in these individuals. What the study adds: This study contributes to data on SARS-CoV-2 seroprevalence before and during the second wave in KwaZulu-Natal, South Africa, which has the highest HIV prevalence globally. Reduced seropositivity was found among people living with HIV with virological failure, highlighting the importance of targeted booster vaccination and vaccine response monitoring.

ABSTRACT: Objectives: In low–middle-income countries, increasing levels of HIV drug resistance (HIVDR) on second-line protease inhibitor (PI)-based regimens are a cause for concern given the limited drug options for third-line antiretroviral therapy (ART). We conducted a retrospective analysis of routine HIV-1 genotyping laboratory data from KwaZulu-Natal, South Africa, to describe the frequency and patterns of HIVDR mutations and their consequent impact on standardised third-line regimens. Methods: This was a cross-sectional analysis of all HIV-1 genotypic resistance tests conducted by the National Health Laboratory Service in KwaZulu-Natal (January 2015 to December 2016) for adults and adolescents (age ≥10 years) on second-line PI-based ART with virological failure. We assigned a third-line regimen to each record based on a national treatment algorithm and calculated the genotypic susceptibility score (GSS) for that regimen. Results: Of 348 samples analysed, 287 (82.5%) had at least one drug resistance mutation (DRM) and 114 (32.8%) had at least one major PI DRM. Major PI resistance was associated with longer duration on second-line ART (aOR per 6-months = 1.11, 95% CI 1.04–1.19) and older age (aOR = 1.03, 95% CI 1.01–1.05). Of 112 patients requiring third-line ART, 12 (10.7%) had a GSS of

Affordable, sensitive, and scalable technologies are needed for monitoring antiretroviral treatment (ART) success with the goal of eradicating HIV-1 infection. This review discusses use of Sanger sequencing and next generation sequencing (NGS) methods for HIV-1 drug resistance (HIVDR) genotyping, focusing on their use in resource limited settings (RLS). Sanger sequencing remains the gold-standard method for detecting HIVDR mutations of clinical relevance but is mainly limited by high sequencing costs and low-throughput. NGS is becoming a more common sequencing method, with the ability to detect low-abundance drug-resistant variants and reduce per sample costs through sample pooling and massive parallel sequencing. However, use of NGS in RLS is mainly limited by infrastructure costs. Given these shortcomings, our review discusses sequencing technologies for HIVDR genotyping, focusing on common in-house and commercial assays, challenges with Sanger sequencing in keeping up with changes in HIV-1 treatment programs, as well as challenges with NGS that limit its implementation in RLS and in clinical diagnostics. We further discuss knowledge gaps and offer recommendations on how to overcome existing barriers for implementing HIVDR genotyping in RLS, to make informed clinical decisions that improve quality of life for people living with HIV.