Clinical Methods Sub-core

Dr. Kyriakides collaborates with clinical researchers on numerous research projects and he provides statistical consulting on numerous research protocols. He has been an abstract mentor for young researchers at the International AIDS Conferences since 2012, leads the VACSPCC internship program and is a statistical reviewer for high-impact medical journals (Lancet Infectious Diseases and the Lancet Gastroenterology & Hepatology).He is the Director at the Department of Veterans' Affairs Cooperative Studies Program (VACSPCC-West Haven) and has worked, as a Senior Biostatistician, on pivotal clinical trials (The OPTIMA Trial, a multi-national HIV/AIDS treatment clinical trial; a surgical clinical trial (The OVER Trial); and a PTSD clinical trial (The VIP-STAR Trial). Even though his primary research focus is in the area of infectious diseases with particular emphasis on HIV/AIDS and its treatment, he has an interest in the history of medicine, social determinants of health and the socio-cultural dimension of the benefits of Greek/Mediterranean nutrition. He has recently been certified as an Olive Oil Sommelier by the International Culinary Center and the Olive Oil Education Lab in NY City. He is the co-proponent for the establishment of a Yale institute dedicated to the olive tree, its products and their impact on human and planetary health.

Ruth Ríos Motta, PhD (Methods Sub-Core Co-Director) is a graduate of UPR and John Hopkins (PhD in Health Services Research/Health Policy) whose biostatistical and health policy expertise has been applied to nutrition, cancer survival, use of alternative medicine, and ZIKA virus, among other topics that have synergy with challenges in the HIV field. She is a perfect complement to Drs. Kyriakides and Spiegelman in Methods co-leadership.

Donna Spiegelman was appointed the Susan Dwight Bliss Professor of Biostatistics at the Yale School of Public Health in 2018; she is also Professor of Statistics and Data Science at Yale University. Dr. Spiegelman founded and directs the Yale Center for Methods in Implementation and Prevention Science (CMIPS) and she also leads the Global Oncology program at Yale Cancer Center. As one of the few people in the world with a joint doctorate in biostatistics and epidemiology, she can freely speak the languages of both disciplines and switches between these two professional cultures, playing the role of interlocutor for each. She is interested in problems arising in epidemiology that require resolution, at least in part, through biostatistics. The emerging field of implementation science is among Dr. Spiegelman's major areas of interest. This field examines barriers to the implementation of evidence-based interventions, as well as the factors that facilitate uptake of these tools. She founded CMIPS to develop tools for implementation science as well as to further the field's deployment to improve public health. The Center comprises 4 tenure-track full-time faculty members in biostatistics, social science and health economics; many additional faculty at YSPH and YSM; and PhD students, post-doctoral fellows, and master's degree students. With colleagues at CMIPS, she studies the design and conduct of implementation studies and pragmatic trials. Topics include stepped-wedge and cluster randomized trials; positive spillover effects; two-stage designs; causal inference for large-scale public health interventions, including causal mediation analysis; correction for biases related to non-adherence and measurement error; and external generalizability; among others. CMIPS also focuses on developing methodsfor learning health care systems. One of CMIPS' primary goals is to develop new statistical methods for implementation science. One such innovation is the Learn as You Go (LAGO) design, which allows researchers to repeatedly adapt ongoing trials in response to new trial data. Such designs help to prevent “failed trials." They can also optimize combination treatment regimens and inform cost-effective health promotion programs. Other biostatistical methods Dr. Spiegelman has developed relate to a wide range of topics, including meta-analysis, measurement error and misclassification, gene-environment and other interactions, smoothing, study design, and population-attributable risk. Before coming to Yale, she served as professor, mentor, and expert statistician at the Harvard T.H. Chan School of Public Health for nearly 30 years.