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Expanded HIV Screening in the United States: Effect on Clinical Outcomes, HIV Transmission, and Costs


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Table 1. Summary of Key Model Input Parameters and Sources for Efficacy of Antiretroviral Therapy and Rapid Test Protocol*

 

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Table 2. Summary of Key Model Input Parameters and Sources for Target Population Characteristics and Effect of Patient Care on HIV Transmission*

 

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Table 3. Mechanisms of Detection through Alternative Screening Practices, Baseline Population Scenario*

 

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Table 4. Survival, Cost, and Cost-Effectiveness Results for HIV Screening Strategies in the Baseline Population*

 

Figure 1
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Figure 1. Recommended strategy regions: $50 000 per quality-adjusted life-year threshold.

The figure recommends an HIV screening policy as a function of both the HIV prevalence in the target population (vertical axis) and the impact of HIV patient care on secondary transmission, {Delta}R0 (horizontal axis). {Delta}R0 can be interpreted as the lifetime number of secondary HIV infections averted when an HIV-infected person in a susceptible population is identified, counseled, and linked to treatment via HIV screening. Each prevalence value is associated with a specific incidence assumption (see Methods section for details). The figure recommends HIV screening policies, assuming that society is prepared to pay up to $50 000 per additional quality-adjusted life-year of health for its citizens. The dotted lines represent the 3 transmission impact scenarios described in Table 2: "favorable impact," "no effect of screening and treatment on transmission impact," and "adverse impact." The curves denote the circumstances under which a given HIV screening strategy is preferred. For example, assuming no impact on secondary transmission, a one-time screening is recommended for prevalences greater than 0.28% (solid circle). Assuming a favorable transmission impact, the one-time screening threshold falls to 0.20% (solid square); with an adverse transmission impact, it increases to 0.40% (solid triangle). The threshold population for screening every 5 years (assuming favorable transmission impact) is HIV prevalence of 0.45% and annual incidence of 0.0075% (solid diamond).

 

Figure 2
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Figure 2. One-time screening versus no specific screening program: sensitivity to cost-effectiveness threshold.

The figure identifies the evolution of the boundary between current practice (that is, no specific screening program) and one-time HIV screening as a function of 3 factors: 1) the prevalence of HIV in the target population (vertical axis); 2) the impact of care on secondary transmission, {Delta}R0 (horizontal axis); and 3) the value that society is prepared to pay to purchase an additional quality-adjusted life-year (QALY) of health for its citizens (as measured by the threshold cost-effectiveness ratio). Each prevalence value is associated with a specific incidence assumption (see Methods section for details). The figure reports results for threshold cost-effectiveness ratios ranging from $25 000 to $100 000 per QALY. The dotted lines represent the 3 transmission impact scenarios described in Table 2: "favorable impact," "no effect of screening and treatment on transmission," and "adverse impact." The curves represent the borders of regions over which a given HIV screening strategy is preferred. For example, assuming that society is willing to pay up to $50 000/QALY and an adverse transmission impact, one-time screening is recommended for prevalences above 0.40% (solid circle); if society is willing to pay even more (up to $75 000/QALY), one-time screening is recommended for prevalences above 0.15% (solid square). Assuming no effect of screening and treatment on transmission and a societal willingness to pay $75 000 per additional QALY, one-time screening is recommended for prevalences above 0.10% (solid triangle). At a societal willingness to pay of $100 000/QALY, one-time screening is preferred under almost all plausible scenarios.

 

Figure 1
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Appendix Figure. Study flow diagram.{webonly}

 

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Appendix Table 1. Incremental Effects of Model Updates: Individual-Patient–Level Analysis*{webonly}

 

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Appendix Table 2. Incremental Effects of Model Updates: Population-Level Analysis*{webonly}

 

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Appendix Table 3. Effects of Data Updates*{webonly}

 

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Appendix Table 4. Effects of Biennial HIV Screening*{webonly}

 





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