Implementation and operational feasibility of SAMBA I HIV-1 semi-quantitative viral load testing at the point-of-care in rural settings in Malawi and Uganda

Objective We monitored a large-scale implementation of the Simple Amplification-Based Assay semi-quantitative viral load test for HIV-1 version I (SAMBA I Viral Load = SAMBA I VL) within Medecins Sans Frontieres' HIV programmes in Malawi and Uganda, to assess its performance and operational feasibility. Methods Descriptive analysis of routine programme data between August 2013 and December 2016. The dataset included samples collected for VL monitoring and tested using SAMBA I VL in five HIV clinics in Malawi (four peripheral health centres and one district hospital), and one HIV clinic in a regional referral hospital in Uganda. SAMBA I VL was used for VL testing in patients who had been receiving ART for between 6 months and ten years, to determine whether plasma VL was above or below 1000 copies/mL of HIV-1, reflecting ART failure or efficacy. Randomly selected samples were quantified with commercial VL assays. SAMBA I instruments and test performance, site throughput, and delays in communicating results to clinicians and patients were monitored. Results Between August 2013 and December 2016 a total of 60 889 patient samples were analysed with SAMBA I VL. Overall, 0.23% of initial SAMBA I VL results were invalid; this was reduced to 0.04% after repeating the test once. Global test failure, including instrument failure, was 1.34%. Concordance with reference quantitative testing of VL was 2620/2727, 96.0% (1338/1382, 96.8% in Malawi; 1282/1345, 95.3% in Uganda). For Chiradzulu peripheral health centres and Arua Hospital HIV clinic, where testing was performed on-site, same-day results were communicated to clinicians for between 91% and 97% of samples. Same-day clinical review was obtained for 84.7% across the whole set of samples tested. Conclusions SAMBA I VL testing is feasible for monitoring cohorts of 1000 to 5000 ART-experienced patients. Same-day results can be used to inform rapid clinical decision-making at rural and remote health facilities, potentially reducing time available for development of resistance and conceivably helping to reduce morbidity and mortality.