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Choice of time horizon critical in estimating costs and effects of changes to HIV programmes

Author

Listed:
  • Nicky McCreesh
  • Ioannis Andrianakis
  • Rebecca N Nsubuga
  • Mark Strong
  • Ian Vernon
  • Trevelyan J McKinley
  • Jeremy E Oakley
  • Michael Goldstein
  • Richard Hayes
  • Richard G White

Abstract

Background: Uganda changed its antiretroviral therapy guidelines in 2014, increasing the CD4 threshold for antiretroviral therapy initiation from 350 cells/μl to 500 cells/μl. We investigate what effect this change in policy is likely to have on HIV incidence, morbidity, and programme costs, and estimate the cost-effectiveness of the change over different time horizons. Methods: We used a complex individual-based model of HIV transmission and antiretroviral therapy scale-up in Uganda. 100 model fits were generated by fitting the model to 51 demographic, sexual behaviour, and epidemiological calibration targets, varying 96 input parameters, using history matching with model emulation. An additional 19 cost and disability weight parameters were varied during the analysis of the model results. For each model fit, the model was run to 2030, with and without the change in threshold to 500 cells/μl. Results: The change in threshold led to a 9.7% (90% plausible range: 4.3%-15.0%) reduction in incidence in 2030, and averted 278,944 (118,452–502,790) DALYs, at a total cost of $28M (-$142M to +$195M). The cost per disability adjusted life year (DALY) averted fell over time, from $3238 (-$125 to +$29,969) in 2014 to $100 (-$499 to +$785) in 2030. The change in threshold was cost-effective (cost

Suggested Citation

  • Nicky McCreesh & Ioannis Andrianakis & Rebecca N Nsubuga & Mark Strong & Ian Vernon & Trevelyan J McKinley & Jeremy E Oakley & Michael Goldstein & Richard Hayes & Richard G White, 2018. "Choice of time horizon critical in estimating costs and effects of changes to HIV programmes," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-10, May.
  • Handle: RePEc:plo:pone00:0196480
    DOI: 10.1371/journal.pone.0196480
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    References listed on IDEAS

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    1. Ioannis Andrianakis & Ian R Vernon & Nicky McCreesh & Trevelyan J McKinley & Jeremy E Oakley & Rebecca N Nsubuga & Michael Goldstein & Richard G White, 2015. "Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda," PLOS Computational Biology, Public Library of Science, vol. 11(1), pages 1-18, January.
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