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Impact and Cost-Effectiveness of Point-Of-Care CD4 Testing on the HIV Epidemic in South Africa

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  • Alastair Heffernan
  • Ella Barber
  • Ranjeeta Thomas
  • Christophe Fraser
  • Michael Pickles
  • Anne Cori

Abstract

Rapid diagnostic tools have been shown to improve linkage of patients to care. In the context of infectious diseases, assessing the impact and cost-effectiveness of such tools at the population level, accounting for both direct and indirect effects, is key to informing adoption of these tools. Point-of-care (POC) CD4 testing has been shown to be highly effective in increasing the proportion of HIV positive patients who initiate ART. We assess the impact and cost-effectiveness of introducing POC CD4 testing at the population level in South Africa in a range of care contexts, using a dynamic compartmental model of HIV transmission, calibrated to the South African HIV epidemic. We performed a meta-analysis to quantify the differences between POC and laboratory CD4 testing on the proportion linking to care following CD4 testing. Cumulative infections averted and incremental cost-effectiveness ratios (ICERs) were estimated over one and three years. We estimated that POC CD4 testing introduced in the current South African care context can prevent 1.7% (95% CI: 0.4% - 4.3%) of new HIV infections over 1 year. In that context, POC CD4 testing was cost-effective 99.8% of the time after 1 year with a median estimated ICER of US$4,468/DALY averted. In healthcare contexts with expanded HIV testing and improved retention in care, POC CD4 testing only became cost-effective after 3 years. The results were similar when, in addition, ART was offered irrespective of CD4 count, and CD4 testing was used for clinical assessment. Our findings suggest that even if ART is expanded to all HIV positive individuals and HIV testing efforts are increased in the near future, POC CD4 testing is a cost-effective tool, even within a short time horizon. Our study also illustrates the importance of evaluating the potential impact of such diagnostic technologies at the population level, so that indirect benefits and costs can be incorporated into estimations of cost-effectiveness.

Suggested Citation

  • Alastair Heffernan & Ella Barber & Ranjeeta Thomas & Christophe Fraser & Michael Pickles & Anne Cori, 2016. "Impact and Cost-Effectiveness of Point-Of-Care CD4 Testing on the HIV Epidemic in South Africa," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-12, July.
    • Handle: RePEc:plo:pone00:0158303
    DOI: 10.1371/journal.pone.0158303
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    References listed on IDEAS

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    1. J. C. Helton & F. J. Davis, 2002. "Illustration of Sampling‐Based Methods for Uncertainty and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 591-622, June.
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    Cited by:

    1. Elizabeth R Stevens & Lingfeng Li & Kimberly A Nucifora & Qinlian Zhou & Margaret L McNairy & Averie Gachuhi & Matthew R Lamb & Harriet Nuwagaba-Biribonwoha & Ruben Sahabo & Velephi Okello & Wafaa M E, 2018. "Cost-effectiveness of a combination strategy to enhance the HIV care continuum in Swaziland: Link4Health," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-17, September.
    2. Sarah J Girdwood & Brooke E Nichols & Crispin Moyo & Thomas Crompton & Dorman Chimhamhiwa & Sydney Rosen, 2019. "Optimizing viral load testing access for the last mile: Geospatial cost model for point of care instrument placement," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-13, August.

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