Assessing the Impact of COVID-19 on HIV Outcomes in the United States: A Modeling Study.

BACKGROUND: The COVID-19 pandemic impacted sexual behaviors and the HIV continuum of care in the United States, reducing HIV testing and diagnosis, and use of preexposure prophylaxis and antiretroviral therapy. We aimed to understand the future implications of these effects through a modeling study. METHODS: We first ran our compartmental model of HIV transmission in the United States accounting for pandemic-related short-term changes in transmission behavior and HIV prevention and care provision in 2020 to 2021 only. We then ran a comparison scenario that did not apply pandemic effects but assumed a continuation of past HIV prevention and care trends. We compared results from the 2 scenarios through 2024. RESULTS: HIV incidence was 4·4% lower in 2020 to 2021 for the pandemic scenario compared with the no-pandemic scenario because of reduced levels of transmission behavior, despite reductions in HIV prevention and care caused by the pandemic. However, reduced care led to less viral load suppression among people with HIV in 2020, and in turn, our model resulted in a slightly greater incidence of 2·0% from 2022 to 2024 in the COVID-19 scenario, as compared with the non-COVID scenario. DISCUSSION: Disruptions in HIV prevention and care services during COVID-19 may lead to somewhat higher postpandemic HIV incidence than assuming prepandemic trends in HIV care and prevention continued. These results underscore the importance of continuing to increase HIV prevention and care efforts in the coming years.

Selecting Evidence-Based HIV Prevention Behavioral Interventions for HIV-Negative Persons for National Dissemination.

This paper describes the development of a formula to determine which evidence-based behavioral interventions (EBIs) targeting HIV-negative persons would be cost-saving in comparison to the lifetime cost of HIV treatment and the process by which this formula was used to prioritize those with greatest potential impact for continued dissemination. We developed a prevention benefit index (PBI) to rank risk-reduction EBIs for HIV-negative persons based on their estimated cost for achieving the behavior change per one would-be incident infection of HIV. Inputs for calculating the PBI included the mean estimated cost-per-client served, EBI effect size for the behavior change, and the HIV incidence per 100,000 persons in the target population. EBIs for which the PBI was ≤ $402,000, the estimated lifetime cost of HIV care, were considered cost-saving. We were able to calculate a PBI for 35 EBI and target population combinations. Ten EBIs were cost-saving having a PBI below $402,000. One EBI did not move forward for dissemination due to high start-up dissemination costs. DHAP now supports the dissemination of 9 unique EBIs targeting 13 populations of HIV-negative persons. The application of a process, such as the PBI, may assist other health-field policymakers when making decisions about how to select and fund implementation of EBIs.