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Applying a seven-step approach to rapidly improve viral load testing coverage: lessons from Burundi, Nigeria and Togo

Title
Applying a seven-step approach to rapidly improve viral load testing coverage: lessons from Burundi, Nigeria and Togo
Presenter
Moses Bateganya
Authors
E.A. Oladele (1), M. Bateganya * (2), P. Imohi (3), P. Sadate-Ngatchou (4), N. Nkurunziza (5), N. Persaud (2), J.P. Tchupo (6), M.D. Ndung'u (4), E. Omoregbe (3), O. Anika (7), J. Mukundu (8), A. Oduola (1), M. Abass (1), C. Akolo (2), H. Mahler (9), FHI 360 Viral Load Action Group
Institutions
(1) FHI 360, HIV Division, Abuja, Nigeria, (2) FHI 360, HIV Division, Durham, United States, (3) Achieving Health Nigeria Initiative, Calabar, Nigeria, (4) FHI 360, Durham, United States, (5) FHI 360, Gitega, Burundi, (6) FHI 360, Lome, Togo, (7) Achieving Health Nigeria Initiative, Uyo, Nigeria, (8) FHI 360, Chipata, Zambia, (9) FHI 360, HIV Division, Washington DC, United States

BACKGROUND: Viral load (VL) monitoring is the preferred approach for monitoring treatment outcomes for people living with HIV on antiretroviral therapy. Globally, VL testing coverage falls short of the 95% benchmark and in 2021 was only 73%, 69%, and 35% in Burundi, Nigeria, and Togo, respectively. The FHI 360 Viral Load Action Group worked with three FHI-360-supported projects (RAFG Burundi, #EAWA Togo/Burkina Faso, SIDHAS Nigeria) to implement a seven-step approach to examine barriers to VL testing coverage, develop and implement tailored plans to address barriers, and track progress to achieve optimal VL coverage.
DESCRIPTION: We implemented the following steps:

  1. Developed the VL testing service chain framework to guide identification of and address gaps
  2. Developed a 31-item VL testing coverage gap diagnostic tool in MS Forms'¢ to identify barriers at each step in the VL service chain
  3. Developed an interactive analytic and visualization tool in Excel'¢ using PowerQuery'¢ and PowerPivot'¢ to generate graphs and tables
  4. Applied the VL diagnostic tool in 10 provinces in Burundi, three regions in Togo, and two states in Nigeria
  5. Used the data analytics and visualization tool to map gaps, decide which sites to prioritize, and develop VL testing surge plans tailored to the largest gaps
  6. Implemented the VL testing surge plans
  7. Tracked progress and provided feedback
We conducted a pre- and post-intervention analysis using routine data from the three projects to determine the impact of these interventions.
LESSONS LEARNED: On the Burunid project, VL testing coverage increased post-intervention from 34% in March 2021 to 83% in August 2021 at an average of 9.0% per month compared to 5.8% per month pre-intervention (p'value=0.01). In Togo, coverage increased from 6% in October 2020 to 93% in August 2021, with an average growth of 9.9% per month post-intervention (p'value=0.34). On the Nigeria project, coverage increased from 61% in October 2020 to a peak of 94% but dropped to 78% at the end of August 2021.
CONCLUSIONS: The multi-step, structured approach tailored to country context improved VL testing coverage significantly. When scaled up, this approach could help close global VL testing coverage gaps.

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