“The WHI has been remarkably productive in pursuing a broad range of scientific questions important to women,” said Garnet Anderson (PhD ’89) director of the Hutch's Public Health Sciences division and principal investigator of the Women’s Health Initiative (WHI) clinical coordinating center. Anderson is also an affiliate professor of biostatistics with the University of Washington School of Public Health.

Writing in the New England Journal of Medicine that they “do not believe that ignoring race will reduce health disparities” but rather that “such an approach is a form of naive ‘color blindness’ that is more likely to perpetuate and potentially exacerbate disparities,” five Black geneticists set out to explain the pitfalls of leaving race out of medicine. UW news reached out to co-author Timothy Thornton from Biostatistics to learn more. 

Through continued intentional collaboration between engineers, data scientists, nurses, health-care providers, philanthropists, and patients' families, new skin-integrated systems offer the promise of raising the standard of neonatal monitoring by improving outcomes and humanizing care worldwide. Amy Sarah Ginsburg with the UW Clinical Trial Center, based out of the Department of Biostatistics, is a co-author

When COVID-19 burst onto the scene last winter, and Tony Fauci, head of the National Institute of Allergy and Infectious Diseases, was looking for a way to run massive, credible and rigorous trials of potential vaccines, he turned to experts at the HIV Vaccine Trials Network (HVTN) based at the Fred Hutchinson Cancer Research Center. Co-principal investigators of the HVTN Statistics and Data Management Center include three researchers who are also University of Washington School of Public Health faculty: Peter Gilbert (Biostat), Holly Janes (Biostat), and Yunda Huang (Global Health).

Jonathan Wakefield, professor of biostatistics and statistics, is co-author of this paper that describes four extensions to previous work: (i) combining summary birth history data with full birth history data, (ii) modeling on a yearly scale, to combine data on a yearly scale with data at coarser time scales, (iii) adjusting direct estimates in Admin‐2 areas where we do not observe any deaths due to small sample sizes, (iv) acknowledge differences in data sources by modeling potential bias arising from the various data sources.