Mission Hall - 3rd Floor - Room 3700
CAPS Town Hall presents: Vincent Muturi-Kioi, MBChB, DTM&H, MS -- African Centered Science, Engagement and Testing: The Road to an HIV Vaccine and Other Solutions for Global Health Challenges
Dr. Vincent Muturi-Kioi is Medical Director at International AIDS Vaccine Initiative (IAVI), stationed at the IAVI Africa regional office in Kenya. In this role, Dr. Muturi-Kioi is responsible for medical monitoring of clinical trials in Africa and involved in the design and implementation of epidemiological studies aimed at providing data to be used for the design of efficacy trials. He also participates in the development and implementation of training activities with clinical partners.
CAPS Town Hall presents: Lindsay Young, PhD -- Social Network Analysis and Machine Learning: Computational Partners in the Study of HIV Prevention and Risk Online
As transmitters of information and progenitors of behavioral norms, social networks are critical mechanisms of HIV prevention and risk in impacted populations like men who have sex with men (MSM), people who inject drugs (PWID), and homeless youth. Today, widespread use of online social networking technologies (e.g., Facebook, Instagram, Twitter) yield unprecedented amounts of relational and communication data far richer than anything previously collected in offline (physical) network settings.
Harsha Thirumurthy is Associate Professor in the Department of Medical Ethics an Health Policy at the University of Pennsylvania. He is also Associate Director at the Center for Health Incentives and Behavioral Economics, where he leads global initiatives and a Research Associate at Penn's Population Studies Center. Professor Thirumurthy's interest lie at the intersecton of economics and public health.
CAPS Methods Core presents: Maya Petersen, MD, PhD, Co-Chair, Graduate Group in Biostatistics, UC Berkeley
Abstract: Targeted Maximum Likelihood Estimation (TMLE) provides an approach for estimating the causal effects of longitudinal interventions with several attractive properties. TMLE uses estimates of both the propensity score (as used in inverse probability weighting) and of a series of outcome regressions (as can be used in parametric G-computation). Machine-learning methods, such as Super Learning (an ensemble approach) can be used to estimate both the propensity score and outcome regressions.
CAPS Community Town Hall presents: Jesse Brooks -- HIV Support with Black Men: "The Brothers Groups"
Jesse Brooks is a longtime activist raised in Oakland, California. He is currently Co-Chair of the Bay Area State of Emergency Coalition (BASE), Advocacy Coordinator of the AIDS Healthcare Foundation of Northern California, and Co-Chair of UCSF/CAPS Research Community Advisory Board, and a Weekly Columnist for the largest African American paper in the Bay Area, “Post News Group,” reaching over 80,000 readers.
CAPS I&I Core and CAPS Town Hall present: Exploring the New Common Rule -- How the New Regulations Affect Human Subjects Research
Don Operario is Professor of Public Health in the Department of Behavior and Social Sciences and Associate Dean for Academic Affairs in the School of Public Health.
He was trained as a Social and Health Psychologist (BA, UCLA; MS, PhD, UMass Amherst; Postdoctoral Fellow, UC San Francisco). He was previously on the faculty of the University of Oxford (Department of Social Policy and Social Work) and before that was at the University of California San Francisco (Center for AIDS Prevention Studies - Department of Medicine).
CAPS Community Town Hall presents: Naina Khanna -- Meaningful Involvement of People Living with HIV/AIDS (MIPA) Toolkit
Please join us for this Community Town Hall on the Meaningful Involvement of People Living with HIV/AIDS (MIPA) Toolkit, shared by Naina Khanna of the Positive Women's Network.
Spotlight on Newly Funded Research Projects at CAPS: PrEP Messaging for Spanish-speaking Transgender Latinas & Couples-based Prevention for Transgender Women
Optimizing PrEP Messaging for Monolingual Spanish-speaking Transgender Latina Women.