To read the updated National HIV/AIDS Strategy, please click here.
For more info, visit www.aids.gov.
Please click here for a copy of the event program.
Please click here for a copy of the keynote presentation by Dr. Stefan Baral of Johns Hopkins School of Public Health. Click here to view video.
Please click here for a copy of the afternoon presentation by Ayako Miyashita, JD, of the UCLA Williams Institute. Click here to view video.]]>
Ecological momentary assessment (EMA) is an increasingly popular assessment method in the behavioral sciences that aims to capture events, emotions, and cognitions in real time, usually repeatedly throughout the day. Because EMA typically involves more intensive monitoring than traditional assessment methods, missing data is commonly an issue and this missingness may bias results. EMA can involve two types of missing data: known missingness, arising from non-response to scheduled prompts, and hidden missingness, arising from non-reporting of focal events (e.g. an urge to smoke or a meal). Prior research on missing data in EMA has focused almost exclusively on non-response to scheduled prompts. In this talk, I introduce a scaled inverse probability weighting approach to adjust for event non-reporting, which can bias estimates of event frequency and characteristics or response to events. In the proposed approach, the inverse probability is the estimated probability of compliance with random prompts, from a model that uses participant and contextual factors to predict this compliance, and a scaling factor that adjusts for factors specific to event- reporting (in this case, the fatigue of reporting over time). I demonstrate the utility of the proposed method with the Tracking and Recording Alcohol Communications Study, an EMA study of adolescent exposure to alcohol advertising, and discuss its broader applicability to the measurement of other habitual events, such as addictive behaviors or treatment adherence.]]>
Yvonne Bryson MD
Distinguished Professor and Chief
Global Pediatric Infectious Disease
DGSOM at UCLA, Mattel Children’s
“HIV Prevalence Rates, Risk Factors and Health Disparities Among Transgender Persons”
on Thursday, July 9, 2015 at 9:30am at St. Anne’s Maternity Home.
Click here to download a flyer. (41)]]>
UCLA CHIPTS proudly took part in this great event. To see the full CSW press release and list of other coalition members, click here.]]>
Dr. Shoptaw is working with his colleagues in leadership at HPTN to bring focused attention to the contributions to the HIV epidemic made by people who use non-injection substances, including binge drinking. Dr. Landovitz is the Protocol Team Leader for HPTN 083, A Phase 2b/3 Double Blind Efficacy Study Of Quarterly Injectable Cabotegravir Compared to Daily Oral Tenofovir Disoproxil.
Congratulations to Drs. Shoptaw and Landovitz for representing UCLA.
Romas Geleziunas, PhD
Director, Clinical Virology
Gilead Sciences, Inc.
“Strategies to Achieve ART-free HIV Remission: An Industry Perspective.”
Grand Rounds This monthly lecture series, which is offered by the UCLA CFAR / AIDS Institute, consists of hour-long lunchtime lectures, delivered by invited guests or distinguished members of the Institute faculty, on a broad range of subjects. The aims of the program are to highlight important developments in AIDS-related research, encourage collaborations between UCLA investigators and invited speakers, interest young investigators in AIDS research, and provide information about new findings and new funding opportunities.]]>
Jacob Konikoff, Ph.D. candidate
Department of Biostatistics
UCLA Fielding School of Public Health
Tracking and surveillance of the HIV epidemic depend on accurate estimation of the number of new infections in the population. The rate at which these infections occur, known as the incidence, is also critical for effectively designing, targeting, and evaluating prevention efforts. This talk focuses on recent advances in estimating HIV incidence through cross-sectional surveys. These studies do not require longitudinal follow-up of individuals. We develop and discuss biomarker-based sequential classification algorithms that mark individuals in an early disease stage as recent infections. Our findings show both the limitations and growing promise of cross-sectional methods for estimating HIV incidence.