Impact of a borderless sample transport network for scaling up viral load monitoring: results of a geospatial optimization model for Zambia.

ABSTRACT:

Introduction

The World Health Organization recommends viral load (VL) monitoring at six and twelve months and then annually after initiating antiretroviral treatment for HIV. In many African countries, expansion of VL testing has been slow due to a lack of efficient blood sample transportation networks (STN). To assist Zambia in scaling up testing capacity, we modelled an optimal STN to minimize the cost of a national VL STN.

Methods

The model optimizes a STN in Zambia for the anticipated 1.5 million VL tests that will be needed in 2020, taking into account geography, district political boundaries, and road, laboratory and facility infrastructure. We evaluated all-inclusive STN costs of two alternative scenarios: (1) optimized status quo: each district provides its own weekl

SUBMITTER: Nichols BE 

PROVIDER: S-EPMC6280013 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature