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Francesca Dominici is a numerical detective. By collecting and integrating disparate bits of data, she identifies key statistical patterns that reveal clues about health. Dominici is an expert at bringing together varied data (airborne particulate levels and hospitalization rates, for example) into a single analysis. She also compensates for differences in the ways data are gathered and for incomplete data.
She is putting her statistical prowess to the test now with a major new five-year project led by Jonathan Samet, MD, chair of Epidemiology. The project analyzes two years of Medicare patient care data, air pollution records, smoking surveys, weather data, and census data, integrating billions of pieces of information in the process. Dominici, who is in charge of the statistical assembly and analysis of the data, must develop newmethods to bring it all together.
“The novel statistical models Francesca develops will allow us to address critical public health questions about air pollution,” explains Scott Zeger, PhD, chair of Biostatistics. “These will include: Does air pollution, at the levels in cities in the developed world, cause heart disease, stroke, and death? What are the health costs associated with elevated air pollution? And who is susceptible—only the most frail?”
Dominici was a prominent contributor to the recently completed National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a major multi-year project on which she collaborated with Zeger, Samet, and others. NMMAPS found strong links between air pollution and mortality. The study made headlines around the world and led Dominici to testify before a committee of the Environmental Protection Agency.
The biostatistician says she was happy to rise to the challenge of public speaking and debate. “I want to push statistical results into the policy arena to have an impact and make change.”