Predictors for viral load in a resource limited setting: A case study of TASO Mulago

Abstract

The burden of human immunodeficiency virus (HIV) response in resource-poor countries is extensive, and a large proportion of HIV patients rely on accessing health care services in rural and underserved areas that do not have the capacity or capability to determine CD4 cell counts and viral loads for monitoring HIV disease progression (Mwamburi, Ghosh, Fauntleroy, Gorbach, & Wanke, 2005). In rural Uganda, return of viral load test results from ministry of health (MoH) for persons living with HIV is after 2 weeks, and these tests are usually done annually. This leaves progression to symptoms (“2. 9 History of viral load tests | Training manual | HIV i-Base,” n.d.) as the only indicator for failure to Viral Load Suppression (VLS) during the lag between collecting samples and return of test results. Therefore, models to predict VLS and to minimize the lag between sample collection and return of results are needed in rural Uganda.