4.3 Article

A Cost-Effectiveness Analysis of Alternative HIV Retesting Strategies in Sub-Saharan Africa

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出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/QAI.0b013e3182118f8c

关键词

HIV counseling and testing; retesting; cost-effectiveness; guidelines; sub-Saharan Africa

资金

  1. Fogarty International Center [D43 PA-03-018]
  2. Duke Clinical Trials Unit and Clinical Research Sites [U01 AI069484-01]
  3. International Studies on AIDS Associated Co- infections award [U01 AI-03-036]
  4. Center for HIV/AIDS Vaccine Immunology [U01 AI067854]
  5. Duke University Center for AIDS Research [P30 AI 64518]

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Background: Guidelines in sub-Saharan Africa on when HIV-seronegative persons should retest range from never to annually for lower-risk populations and from annually to every 3 months for high-risk populations. Methods: We designed a mathematical model to compare the cost-effectiveness of alternative HIV retesting frequencies. Cost of HIV counseling and testing, linkage to care, treatment costs, disease progression, and mortality, and HIV transmission are modeled for three hypothetical cohorts with posited annual HIV incidence of 0.8%, 1.3%, and 4.0%, respectively. The model compared costs, quality-adjusted life-years gained, and secondary infections averted from testing intervals ranging from 3 months to 30 years. Input parameters from sub-Saharan Africa were used and explored in sensitivity analyses. Results: Accounting for secondary infections averted, the most cost-effective testing frequency was every 7.5 years for 0.8% incidence, every 5 years for 1.3% incidence, and every 2 years for 4.0% incidence. Optimal testing strategies and their relative cost-effectiveness were most sensitive to assumptions about HIV counseling and testing and treatment costs, rates of CD4 decline, rates of HIV transmission, and whether tertiary infections averted were taken into account. Conclusions: While higher risk populations merit more frequent HIV testing than low risk populations, regular retesting is beneficial even in low-risk populations. Our data demonstrate benefits of tailoring testing intervals to resource constraints and local HIV incidence rates.

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