Mathematics of Planet Earth

Watch the video of Dr. Dominici’s lecture

Abstract

Over the next century, climate change is expected to lead to an increase in the intensity and frequency of extreme weather events such as heat waves.  Climate change is also expected to impact air pollution, such as ozone and particulate matter. The public health impact of climate change is poorly understood, in part because of numerous factors exhibiting a wide range of uncertainty that underlies estimates of future health risk. To mitigate the public health consequences of climate change we need a comprehensive understanding of how changes in all of the environmental exposures will affect vulnerability in a changing climate.

In this talk, I will review statistical modeling for estimating the public health impact of air pollution and extreme heat both using historical data and climate change future projections. We will link and analyze massive data sets on weather, air pollution, health, and socio-demographic characteristics that are collected at different spatial and temporal resolution. We will also present ongoing statistical modeling approaches to address the following challenges; 1) ambient air pollution levels (e.g., ozone and particulate matter) will change in response to the altered meteorological conditions arising from climate change; and 2) the health effects of combined exposure to degraded air quality and heat could be more severe than expected based on the individual exposures (i.e., synergism).

Biography

Francesca Dominici, Ph.D., is Professor of Biostatistics in the Harvard School of Public Health and Associate Dean of Information Technology. Dr. Dominici received her Ph.D. in Statistics at the University of Padua in 1997. From 1997 to 2009 she was at the Bloomberg School of Public at Johns Hopkins University and in 2009 moved to the School of Public Health at Harvard University.

Dr. Dominici’s research has focused on the development of statistical methods for the integration of large data to assess and monitor health risks associated to air pollution and climate change.  She has developed statistical methods for the analysis of large databases on air pollution and health. She has gained experience with the analysis of Medicare data and their linkage by geography and time to other data sources, such us air pollution, weather, and socioeconomic status. She has developed statistical methods for the adjustment of measured and unmeasured confounders, Bayesian hierarchical models, causal inference methods, and missing data methods.

Dr. Dominici is the recipient of the first Walter A. Rosenblith Young Investigator Award from The Health Effects Institute, Boston, MA; the Diversity Recognition Award, from Johns Hopkins University, 2009; of the Myrto Lefkopoulou Distinguished Lectureship Award, from the Department of Biostatistics, School of Public Health, Harvard University, 2007, and of the Mortimer Spiegelman Award, from Statistics Section of the American Public Health Association, 2006. Dr. Dominici is also a Fellow of the American Statistical Association.

Dr. Dominici has served on a number of National Academies’ committees including the Committee on Gulf War and Health: Review of the Medical Literature Relative to Gulf War Veterans’ Health; the Committee to Assess Potential Health Effects from Exposures to PAVE PAWS Low-level Phased-array Radiofrequency Energy; the Committee on The Utility of Proximity-Based Herbicide Exposure Assessment in Epidemiologic Studies of Vietnam Veterans, and the Committee to Review ATSDR’s Great Lakes Reports, the committee to  Review the Federal Response to the Health Effects Associated with the Gulf of Mexico Oil Spill; committee on Long-Term Health Consequences of Exposure to Burn Pits in Iraq and Afghanistan; committee on Secondhand Smoke Exposure and Acute Coronary Events;  committee on Making Best Use of the Agent Orange Exposure Reconstruction Model.

The MPE2013 Simons Public Lecture Series is funded by