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PLoS One. 2019 Aug 26;14(8):e0221586. doi: 10.1371/journal.pone.0221586. eCollection 2019.

Optimizing viral load testing access for the last mile: Geospatial cost model for point of care instrument placement.

Author information

1
Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
2
Department of Global Health, School of Public Health, Boston University, Boston, MA, United States of America.
3
EQUIP Zambia, Lusaka, Zambia.
4
Right to Care, GIS Mapping Department, Johannesburg, South Africa.

Abstract

INTRODUCTION:

Viral load (VL) monitoring programs have been scaled up rapidly, but are now facing the challenge of providing access to the most remote facilities (the "last mile"). For the hardest-to-reach facilities in Zambia, we compared the cost of placing point of care (POC) viral load instruments at or near facilities to the cost of an expanded sample transportation network (STN) to deliver samples to centralized laboratories.

METHODS:

We extended a previously described geospatial model for Zambia that first optimized a STN for centralized laboratories for 90% of estimated viral load volumes. Amongst the remaining 10% of volumes, facilities were identified as candidates for POC placement, and then instrument placement was optimized such that access and instrument utilization is maximized. We evaluated the full cost per test under three scenarios: 1) POC placement at all facilities identified for POC; 2)an optimized combination of both on-site POC placement and placement at facilities acting as POC hubs; and 3) integration into the centralized STN to allow use of centralized laboratories.

RESULTS:

For the hardest-to-reach facilities, optimal POC placement covered a quarter of HIV-treating facilities. Scenario 2 resulted in a cost per test of $39.58, 6% less than the cost per test of scenario 1, $41.81. This is due to increased POC instrument utilization in scenario 2 where facilities can act as POC hubs. Scenario 3 was the most costly at $53.40 per test, due to high transport costs under the centralized model ($36 per test compared to $12 per test in scenario 2).

CONCLUSIONS:

POC VL testing may reduce the costs of expanding access to the hardest-to-reach populations, despite the cost of equipment and low patient volumes. An optimal combination of both on-site placement and the use of POC hubs can reduce the cost per test by 6-35% by reducing transport costs and increasing instrument utilization.

Conflict of interest statement

The authors have declared that no competing interests exist.

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