Biostatistics, Bioinformatics and Epidemiology (BBE) researchers use mathematical modeling, computational biology, epidemiology and statistics to determine how infectious diseases such as COVID-19, HIV, tuberculosis, malaria and Ebola are spread and contained. Our researchers collaborate across multiple research areas and work with network colleagues — such as the HIV Vaccine Trials Network, HIV Prevention Trials Network and COVID-19 Prevention Trials Network — to incorporate biostatistics, bioinformatics and population modeling throughout vaccine design, development, evaluation and deployment.
Our researchers are applying their extensive experience in statistics and mathematics to the design, implementation and conduct of treatment and prevention clinical trials. Specific areas of research focus include:
Fred Hutch researchers worked with colleagues at the University of Basel to track changes in the SARS-CoV2 virus genetic code as it spread from person to person. This information helps researchers chart the viruses progression.
Dr. Raphael Gottardo develops statistical methods and software tools for the analysis of high throughput biological data with an emphasis on immunology and vaccine research. In collaboration with bench scientists and clinicians, he investigates severe diseases such HIV, malaria and cancer, to ultimately help develop vaccines and cures.
Dr. Ying Huang develops statistical methods for design and analysis of biomarker studies for disease screening, surrogate endpoint identification and treatment selection in cancer and infectious diseases. His group studies how to efficiently select biomarkers among high-dimensional candidates and derive marker-based individualized rules, using data from randomized trials and observational studies.
Dr. Elizabeth Halloran researches study designs and analytic methods for evaluating vaccines in populations. Research includes developing new methods as well as applying existing methods to novel applications. Going beyond the direct protective effects, she uses a variety of analytic methods to understand the indirect and overall effects of vaccination programs.
Dr. Trevor Bedford studies the dynamics of virus populations to understand how strains evolve and spread throughout the world. His team is particularly interested in how viruses mutate in response to host immune responses as well as the factors that make certain strains more virulent and infectious.
Dr. Youyi Fong uses biostatistical modeling and computational methods to analyze the effectiveness of vaccine candidates in clinical trials. His team collaborates with clinical research teams striving to eliminate HIV, dengue and cholera.
Dr. Peter Gilbert researches the statistical design and analysis of HIV vaccine efficacy trials, with emphasis on assessing immune correlates of vaccine-induced protection. Though focused on HIV vaccine trials, his research contributes to general areas of statistical methods research including surrogate endpoint assessment, causal inference, survival analysis, and efficient randomized trial design.
Dr. Elizabeth Brown is a biostatistician engaged in the design and analysis of clinical trials for a number of infectious diseases, including COVID-19 and HIV.
Dr. Ollivier Hyrien applies advanced technologies such as machine learning and dynamic modeling to address problems in laboratory experiments and clinical studies.
Dr. Deborah Donnell has shaped pivotal trials in many areas of HIV prevention research and has included interventions to stop mother-to-child transmission; the treatment of opiate addiction; treatment as prevention in HIV-infected persons; and the use of pre-exposure prophylaxis, or PrEP — a once-a-day antiretroviral pill to prevent infection in those who are at high risk.
Dr. Holly Janes is a biostatistician working on the design and analysis of vaccine studies, with a particular expertise in HIV prevention and vaccine science.
Dr. Fei Gao develops novel statistical methods for survival analysis and semiparametric inference.