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A Computer-Simulation Model Attempts to Reframe Costs, Solutions to Ending HIV in the United States

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To effectively end the HIV epidemic in the United States, combination strategies should be tailored according to need, backed by evidence-based interventions, and scaled according to location, report study results in The Lancet HIV.

To effectively end the HIV epidemic in the United States, combination strategies should be tailored according to need, backed by evidence-based interventions, and scaled according to location, report study results in The Lancet HIV on a 6-city computer-simulation economic model developed by researchers for the Localized HIV Modeling Study Group.

The authors’ viewpoint is that instead of 1 homogeneous epidemic in the United States, the HIV epidemic is heterogeneous and is composed of diverse local microepidemics that suffer from “fundamental differences in health system infrastructure, funding, and HIV-related laws and policies between the regions.”

These 6 cities that the authors based their model on were Atlanta, Georgia; Baltimore, Maryland; Los Angeles, California; Miami, Florida; New York, New York; and Seattle, Washington, because they contain close to 25% of all people in the United States who have HIV. They looked at 23,040 combinations of 16 possible evidence-based interventions that focused on HIV prevention, testing, treatment, engagement, and re-engagement for those providing optimal health benefits that were cost-effective.

Results show that program strategies comprising 9 to 13 interventions could produce the best results in health benefits gained and were the most cost-effective. These so-structured solutions could lead to a reduction in HIV incidence from 30.7% (95% credible interval [CrI], 19.1%-43.7%) in Seattle to 50.1% (95% CrI, 41.5%-58.0%) in New York by 2030 and save up to $95,416 per quality-adjusted life-year gained, also in Seattle.

The total costs for program implementation could reach $559 million for each city, or $3.51 billion overall through 2030, but the long-term reductions in new HIV infections, as well as gains in delayed disease progression, offset that amount over 20 years.

To aid their model, the authors fed it 1517 city-specific parameters and 150 parameters that the 6 cities had in common. They also combined evidence from 11 primary databases, 59 peer-reviewed publications, and 24 public health and surveillance reports to fashion these parameters and each city’s model.

Their results also show that under ideal conditions, combination strategies that address 3 of the 4 pillars of the United States’ Ending the HIV Epidemic strategy—prevent, diagnose, and treat—could reduce the incidence of new HIV infections by an average 63.5% overall for their 6 cities, approaching both the 5-year target of 75% and the 10-year target of 90%.

Among the cities, Baltimore could see the biggest reductions but Seattle, the least:

  • Baltimore: 83.6% (95% CrI, 70.8%-87.0%)
  • Miami: 78.3% (95% CrI, 51.5%-86.9%)
  • Atlanta: 74.4% (95% CrI, 67.0%-80.7%)
  • New York: 58.1% (95% CrI, 48.1%-66.9%)
  • Los Angeles: 41.5% (95% CrI, 30.5%-56.1%)
  • Seattle: 39.5% (95% CrI, 26.3%-53.8%)

“Our projections suggest that implementing combinations of evidence-based interventions can provide public health and economic value and approach national incidence reduction targets in some settings,” the authors concluded. “However, complementary strategies to overcome social and structural barriers to HIV care will be required to reach national targets of the ending the HIV epidemic initiative by 2030.”

Their suggestions include expanding HIV partner services, high-risk population testing, and health literacy programs; reducing HIV-related stigmatization; and improving the collection of high-quality surveillance data to better inform interventions that show promise but have not been extensively studied.

Reference

Nosyk B, Zang X, Krebs E, at al. Ending the HIV epidemic in the USA: an economic modelling study in six cities. Lancet HIV. 2020;7(7):e491-e503. doi:10.1016/S2352-3018(20)30033-3

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