Lifetime cost of HIV management in Australia: an economic model

Megumi Lim, Angela Devine, Richard T. Gray, Jisoo A. Kwon, Jolie L. Hutchinson, Jason J. Ong

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2 Citations (Scopus)


Background: Antiretroviral therapy (ART) for HIV has significantly reduced morbidity and mortality, but the drugs can be expensive. This study aimed to estimate the lifetime cost of HIV management from the Australian healthcare perspective. Methods: A Markov cohort model, consisting of 21 health states based on CD4 count and line of ART, simulated disease progression over the lifetime of persons living with HIV. We reported costs using 2019 Australian dollars (A$) at a discount rate of 3.5% per annum. One-way sensitivity analysis was used to assess the impact of model inputs, and probabilistic sensitivity analyses were conducted to calculate the 95% confidence intervals for the lifetime cost estimate. Results: The average discounted lifetime cost of HIV management was A$282 093 (95% CI: $194 198-421 615). The largest proportion of lifetime cost was due to ART (92%). The lifetime cost was most sensitive to third- and second-line ART costs, followed by the probability of failing third-line therapy for those with a CD4 count of <200 cells/μL. A 20% or 50% reduction in patented ART costs would reduce the lifetime cost to A$243 638 and A$161 400, respectively. Replacing patented ART drugs with currently available generic equivalents reduced the lifetime cost to A$141 345. Conclusion: The relatively high lifetime costs for managing HIV mean that ongoing investment will be required to provide care and treatment to people living with HIV, and supports the urgent need to avert new infections. Reducing the price of ARTs (including consideration of generic drugs) would have the most significant impact on lifetime costs.

Original languageEnglish
Pages (from-to)517–524
Number of pages8
JournalSexual Health
Issue number6
Publication statusPublished - 2022


  • antiretroviral therapy
  • Australia
  • health economics
  • lifetime cost
  • living with HIV
  • management cost
  • mathematical models

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