Scale-up of Kenya's national HIV viral load program: Findings and lessons learned

Matilu Mwau, Catherine Akinyi Syeunda, Maureen Adhiambo, Priska Bwana, Lucy Kithinji, Joy Mwende, Laura Oyiengo, Martin Sirengo, Caroline E Boeke, Matilu Mwau, Catherine Akinyi Syeunda, Maureen Adhiambo, Priska Bwana, Lucy Kithinji, Joy Mwende, Laura Oyiengo, Martin Sirengo, Caroline E Boeke

Abstract

Objectives: Kenya is one of the first African countries to scale up a national HIV viral load monitoring program. We sought to assess program scale up using the national database and identify areas for systems strengthening.

Methods: Data from January 2012 to March 2016 were extracted from Kenya's national viral load database. Characteristics of 1,108,356 tests were assessed over time, including reason for testing, turnaround times, test results, treatment regimens, and socio-demographic information.

Results: The number of facilities offering viral load testing increased to ~2,000 with >40,000 tests being conducted per month by 2016. By March 2016, most (84.2%) tests were conducted for routine monitoring purposes and the turnaround time from facility-level sample collection to result dispatch from the lab was 21(24) [median (IQR)] days. Although the proportions of repeat viral load tests increased over time, the volumes were lower than expected. Elevated viral load was much more common in pediatric and adolescent patients (0-<3 years: 43.1%, 3-<10 years: 34.5%, 10-<20 years: 36.6%) than in adults (30-<60 years: 13.3%; p<0.001).

Conclusions: Coverage of viral load testing dramatically increased in Kenya to >50% of patients on antiretroviral therapy (ART) by early 2016 and represents a relatively efficient laboratory system. However, strengthening of patient tracking mechanisms and viral load result utilization may be necessary to further improve the system. Additional focus is needed on paediatric/adolescent patients to improve viral suppression in these groups. Kenya's national viral load database has demonstrated its usefulness in assessing laboratory programs, tracking trends in patient characteristics, monitoring scale-up of new policies and programs, and identifying problem areas for further investigation.

Conflict of interest statement

Competing Interests: This does not alter our adherence to PLOS ONE policies on sharing data and materials and the authors have no competing interests to declare.

Figures

Fig 1. Flow Chart of samples included…
Fig 1. Flow Chart of samples included in the analysis.

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