Simulating the End of AIDS in New York: Using Participatory Dynamic Modeling to Improve Implementation of the Ending the Epidemic Initiative

Examining Concordance Between Self-Report and Biomedical HIV Viral Load Data: A Scoping Review

Assessment of HIV viral load based on laboratory results is the gold standard in HIV care and research. However, blood assay or accessing medical records is not always possible due to research or service contexts and constraints. Self-report of viral load test results expands data resources, is a convenient method of collecting data in both research and service settings, and is useful for HIV surveillance. The purpose of this scoping review was to identify existing literature on the validity of self-reported viral load data compared to blood assay or medical record review. We found that the existing literature is limited, with varied data collection methods, self-report measures, and study designs, as well as predictors of accuracy. Concordance between self-reported viral load and biomedical data varied across studies but appeared to be more consistent among samples recruited from clinical populations that reported engagement in HIV care. While it is difficult to draw definitive conclusions about the validity of self-reported viral load across existing studies, there is a need for a standardized measure and method of collection that can be utilized across diverse populations living with HIV.

Intersectionality-informed analysis of durable viral suppression disparities in people with HIV

OBJECTIVE

The aim of this study was to examine drivers of durable viral suppression (DVS) disparities among people with HIV (PWH) using quantitative intersectional approaches.

DESIGN

A retrospective cohort analysis from electronic health records informed by intersectionality to better capture the concept of interlocking and interacting systems of oppression.

METHODS

We analyzed data of PWH seen at a LGBTQ federally qualified health center in Chicago (2012-2019) with at least three viral loads. We identified PWH who achieved DVS using latent trajectory analysis and examined disparities using three intersectional approaches: Adding interactions, latent class analysis (LCA), and qualitative comparative analysis (QCA). Findings were compared with main effects only regression.

RESULTS

Among 5967 PWH, 90% showed viral trajectories consistent with DVS. Main effects regression showed that substance use [odds ratio (OR) 0.56, 0.46-0.68] and socioeconomic status like being unhoused (OR: 0.39, 0.29-0.53), but not sexual orientation or gender identity (SOGI) were associated with DVS. Adding interactions, we found that race and ethnicity modified the association between insurance and DVS ( P for interaction <0.05). With LCA, we uncovered four social position categories influenced by SOGI with varying rates of DVS. For example, the transgender women-majority class had worse DVS rates versus the class of mostly nonpoor white cisgender gay men (82 vs. 95%). QCA showed that combinations, rather than single factors alone, were important for achieving DVS. Combinations vary with marginalized populations (e.g. black gay/lesbian transgender women) having distinct sufficient combinations compared with historically privileged groups (e.g. white cisgender gay men).

CONCLUSION

Social factors likely interact to produce DVS disparities. Intersectionality-informed analysis uncover nuance that can inform solutions.

Evaluation of Trends in Preexposure Prophylaxis Prescriptions During the First 6 Months of the COVID-19 Pandemic in New York State

This cohort study uses time-series models to estimate preexposure prophylaxis prescription trends during the first 6 months of the COVID-19 pandemic in New York State in 2020.