Sunday, January 31, 2016

Costs per Diagnosis of Acute HIV Infection in Community-Based Screening Strategies: A Comparative Analysis of Four Screening Algorithms

In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking.

To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%.

Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%.

Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%.

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  • 1Division of Infectious Diseases, University of California-San Diego Division of Pulmonology Section of Infectious Diseases and Tropical Medicine, Department of Internal Medicine, Medical University of Graz, Austria.
  • 2School of International Relations and Pacific Studies and Department of Economics, University of California-San Diego.
  • 3Division of Infectious Diseases, University of California-San Diego 
  •  2016 Feb 15;62(4):501-11. doi: 10.1093/cid/civ912. Epub 2015 Oct 27.

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