Technology & Industry

Evidence brief: Implementation bottlenecks of near point of care HIV viral load monitoring for children and young people in Tanzania: A Qualitative Study

A sourced PLOS One study, published 2026-06-12. Read the researchers’ findings, methods and context, with links to connected African health evidence.

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Published in PLOS One on 2026-06-12, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.

Original authors: Perry Msoka, Alan Mtenga, Rehema Maro, Rhoda Akello, Iraseni Ufoo Swai, Blandina T Mmbaga, Ria Reis, Marion Sumari-de Boer, Hamufare Mugauri

Source: PLOS One • DOI 10.1371/journal.pone.0351304

Read the complete primary study ↗ · Creative Commons Attribution licence

From the researchers

Abstract

Near point-of-care (n)POC Human Immunodeficiency Virus (HIV) viral load (VL) monitoring, consisting of VL testing in laboratories close to HIV treatment facilities, improves turnaround time from sampling to result. Other benefits of using nPOC monitoring are reduced laboratory workload, and limited loss of results, all leading to improved clinic retention and treatment adherence. However, the specific implementation bottlenecks are still unclear. This study aims to investigate the bottlenecks in the implementation of nPOC HIV VL monitoring among children and young people (ages 0–24 years) living with HIV, as experienced by healthcare workers (HCWs) in Tanzania.

We conducted observations in clinics and in-depth interviews with HCWs from January 2023 to January 2024 at Tanzanian intervention sites within the East Africa Point-of-Care Viral Load Monitoring (EAPOC-VL) study. The EAPOC-VL study was conducted in four countries in East Africa (Tanzania, Kenya, Rwanda, Uganda). It was a cluster-randomised controlled trial, in which participants were tested at three time points (months 0, 6, and 12). We purposively selected 25 HCWs involved in implementing nPOC at the intervention sites for in-depth interviews. We interviewed HCWs at baseline (month 0) and after the initiation of nPOC HIV VL monitoring (months 1 and 6). We conducted deductive thematic framework analysis using the Measurement Instrument for Determinants of Innovations (MIDI), to which an inductive approach was added to identify facilitators and barriers across intervention, provider, organisational, social and political contexts. We used NVivo 12 to organise the data.

A total of 75 interviews were conducted among 43 HCWs across 3 time points: 33 at baseline (T0), 25 at month 1 (T1; 19 participants from T0 and 6 new participants) and 17 at month 6 follow up (T2;6 participants from T1, 7 returning participants from T0 and 4 new participants). Observations and interviews showed that nPOC HIV VL testing improved result turnaround time and enabled same-day counselling, which motivated both HCWs and clients. This data showed that knowledge, confidence, and adherence to procedures after training. Near POC, HIV VL was supported by compatibility with existing practices, strong teamwork, and management commitment. However, challenges included clients waiting at the clinic for over two hours to receive their results, the scarcity of resources, such as rooms and electricity, and staff shortages. Finally, delays were observed when samples had to be transported to nearby laboratories.

Near POC HIV VL monitoring shortens turnaround times and enables immediate counselling. To maximise these benefits, there is a need to prioritise investment in staff training, infrastructure, improving sample handling/turnaround time and guideline alignment. Developing these areas will enhance service delivery and allow for improved outcomes among children and young people living with HIV.

Reading this evidence

Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.

This briefing makes the source accessible within the wider technology & industry desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.

© 2026 Perry Msoka, Alan Mtenga, Rehema Maro, Rhoda Akello, Iraseni Ufoo Swai, Blandina T Mmbaga, Ria Reis, Marion Sumari-de Boer, Hamufare Mugauri. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.

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Health Signal’s publication desk curates source-based health analysis and attributed research briefings. Study authors and originating institutions are credited within each article. Preparation used AI assistance; source and licence checks do not constitute independent replication or clinical endorsement.

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