Landscape of HIV Implementation Research Funded by the National Institutes of Health: A Mapping Review of Project Abstracts.

In 2019, the requisite biomedical and behavioral interventions to eliminate new HIV infections exist. "Ending the HIV Epidemic" now becomes primarily a challenge of will and implementation. This review maps the extent to which implementation research (IR) has been integrated into HIV research by reviewing the recent funding portfolio of the NIH. We searched NIH RePORTER for HIV and IR-related research projects funded from January 2013 to March 2018. The 4629 unique studies identified were screened using machine learning and manual methods. 216 abstracts met the eligibility criteria of HIV and IR. Key study characteristics were then abstracted. NIH currently funds HIV studies that are either formally IR (n = 109) or preparatory for IR (n = 107). Few (13%) projects mentioned a guiding implementation model, theory, or framework, and only 56% of all studies explicitly mentioned measuring an implementation outcome. Considering the study aims along an IR continuum, 18 (8%) studies examined barriers and facilitators, 43 (20%) developed implementation strategies, 46 (21%) piloted strategies, 73 (34%) tested a single strategy, and 35 (16%) compared strategies. A higher proportion of formal IR projects involved established interventions (e.g., integrated services) compared to newer interventions (e.g., pre-exposure prophylaxis). Prioritizing HIV-related IR in NIH and other federal funding opportunity announcements and expanded training in implementation science could have a substantial impact on ending the HIV pandemic. This review serves as a baseline by which to compare funding patterns and the sophistication of IR in HIV research over time.

Adjunctive interventions: change methods directed at recipients that support uptake and use of health innovations.

BACKGROUND: Implementation science groups change methods into two categories: (1) clinical, behavioral, or biomedical intervention targeting recipient's health outcomes and (2) implementation strategies targeting the delivery system. Differentiating interventions from strategies based on their intended functions is critical to accurately attributing their effects to health or implementation outcomes. However, in coordinating 200+ HIV implementation research projects and conducting systematic reviews, we identified change methods that had characteristics of both interventions and strategies that were inconsistently categorized. To alleviate confusion and improve change method specification, we propose that implementation science should adopt an extant but rarely used term-adjunctive interventions-to classify change methods that are distinct from the common intervention/strategy taxonomy. MAIN TEXT: Adjunctive interventions as change methods that target recipients (e.g., patients, participants) of a health intervention but are designed to increase recipients' motivation, self-efficacy, or capacity for initiating, adhering to, complying with, or engaging with the health intervention over time. In two of our published reviews on implementation of HIV interventions, 25 out of 45 coded change methods fell into this gray area between strategy and intervention. We also noted instances in which the same change method was labelled as the intervention ("the thing"), as an adjunctive intervention, or an implementation strategy in different studies-further muddying the waters. Adjunctive interventions are distinguished from other change methods by their intended targets, desired outcomes, and theory of action and causal processes. Whereas health interventions target recipients and have a direct, causal effect on the health outcome, adjunctive interventions enhance recipients' attitudes and behaviors to engage with the intervention and have an indirect causal link to the health outcome via increasing the probability of recipients' utilization and adherence to the intervention. Adjunctive interventions are incapable of directly producing the health outcome and will themselves require implementation strategies to effectively impact sustained uptake, utilization, and adherence. Case examples, logic modeling, and considerations (e.g., relationship to consumer engagement strategies) for adjunctive intervention research are provided. CONCLUSION: Conceptualizing adjunctive interventions as a separate type of change method will advance implementation research by improving tests of effectiveness, and the specification of mechanisms and outcomes.

The HIV Treat Pillar: An Update and Summary of Promising Approaches.

The Treat pillar of the Ending the HIV Epidemic in the U.S. plan calls for comprehensive strategies to enhance linkage to, and engagement in, HIV medical care to improve viral suppression among people with HIV and achieve the goal of 95% viral suppression by 2025. The U.S. has seen large increases in the proportion of people with HIV who have a suppressed viral load. Viral suppression has increased 41%, from 46% in 2010 to 65% in 2018. An additional increase of 46% is needed to meet the Ending the HIV Epidemic in the U.S. goal. The rate of viral suppression among those in care increased to 85% in 2018, highlighting the need to ensure sustained care for people with HIV. Greater increases in all steps along the HIV care continuum are needed for those disproportionately impacted by HIV, especially the young, sexual and racial/ethnic minorities, people experiencing homelessness, and people who inject drugs. Informed by systematic reviews and current research findings, this paper describes more recent promising practices that suggest an impact on HIV care outcomes. It highlights rapid linkage and treatment interventions; interventions that identify and re-engage people in HIV care through new collaborations among health departments, providers, and hospital systems; coordinated care and low-barrier clinic models; and telemedicine-delivered HIV care approaches. The interventions presented in this paper provide additional approaches that state and local jurisdictions can use to reach their local HIV elimination plans' goals and the ambitious Ending the HIV Epidemic in the U.S. Treat pillar targets by 2030.

County-level factors affecting Latino HIV disparities in the United States.

OBJECTIVE: To determine which county-level social, economic, demographic, epidemiologic and access to care factors are associated with Latino/non-Latino White disparities in prevalence of diagnosed HIV infection. METHODS AND FINDINGS: We used 2016 county-level prevalence rates of diagnosed HIV infection rates for Latinos and non-Latino Whites obtained from the National HIV Surveillance System and factors obtained from multiple publicly available datasets. We used mixed effects Poisson modeling of observed HIV prevalence at the county-level to identify county-level factors that explained homogeneous effects across race/ethnicity and differential effects for Latinos and NL-Whites. Overall, the median Latinos disparity in HIV prevalence is 2.4; 94% of the counties have higher rates for Latinos than non-Latinos, and one-quarter of the counties' disparities exceeded 10. Of the 41 county-level factors examined, 24 showed significant effect modification when examined individually. In multi-variable modeling, 11 county-level factors were found that significantly affected disparities. Factors that increased disparity with higher, compared to lower values included proportion of HIV diagnoses due to injection drug use, percent Latino living in poverty, percent not English proficient, and percent Puerto Rican. Latino disparities increased with decreasing percent severe housing, drug overdose mortality rate, percent rural, female prevalence rate, social association rate, percent change in Latino population, and Latino to NL-White proportion of the population. These factors while significant had minimal effects on diminishing disparity, but did substantially reduce the variance in disparity rates. CONCLUSIONS: Large differences in HIV prevalence rates persist across almost all counties even after controlling for county-level factors. Counties that are more rural, have fewer Latinos, or have lower NL-White prevalence rates tend to have higher disparities. There is also higher disparity when community risk is low.