Donna Spiegelman

Professor of Epidemiologic Methods

Department of Epidemiology
Department of Biostatistics
Department of Nutrition

677 Huntington Avenue
Kresge Building, Room 802
Boston, Massachusetts 02115
Phone: 617.432.0205

Recent News

May 26, 2015 – Spiegelman & colleagues’ work strengthens the causal evidence for the health effects of chronic exposure to air pollution by eliminating uncertainty due to exposure measurement error

October 6, 2014 – Donna Spiegelman has received a Director’s Pioneer Award from the National Institutes of Health (NIH) for $500,000/year of direct costs for the next 5 years.

Read more in News.


I am one of the few people in the world with a joint doctorate in Biostatistics and Epidemiology. As a result, I can freely speak the languages of both disciplines, and switch between these two professional cultures, playing the role of interlocutor for either. My research is motivated by problems which arise in epidemiology and require biostatistical solutions. In particular but by no means exclusively, I have focused on methods for study design and data analysis which reduce bias in estimation and inference due to measurement error or misclassification in the exposure variable. I am currently completing an extensive project of methods development and re- and new analysis of several major studies of the effects of long-term exposure to constituents of air pollution on the risk of overall, cardiovascular and lung cancer mortality, collaborating with epidemiologists, statisticians and environmental scientists in the Netherlands, Israel, and the University of Washington in Seattle. The goal is to substantially reduce, if not eliminate, exposure measurement error as a major source of bias in the available results to date, and involves solving challenging mathematical and computational problems in the realm of survival data analysis. We will soon be publishing revised estimates of the health impact of exposure to air pollution constituents in the Netherlands and in the U.S., adjusted for bias due to measurement error.

My website is one of the most visited at the Harvard Chan School, because it contains much user-friendly and well-documented freeware implementing non-standard methods useful in epidemiologic research (see software). I am the statistician for the Nurses’ Health Study 2, the Health Professionals Follow-Up Study, and the Harvard PEPFAR greater Dar es Salaam site, and a multitude of spawn of these efforts.

My most recent interest has been to work actively with others in Epidemiology, Nutrition, Environmental Health, and Global Health and Population, to greatly increase global public health efforts at the Harvard Chan School. In particular, I am interested in developing, testing and implementing public health oriented preventive interventions for achieving Millennium Development Goals 4 & 5, to complement health systems strengthening efforts of great interest currently; developing, testing, and implementing preventive interventions to abate the global diabetes and cardiovascular disease epidemics; and developing new methodology to better evaluate the individual and population-level impact of efforts in Sub-Saharan Africa to end the AIDs epidemic through prevention. Expertise in the methodology of project monitoring and evaluation, and for randomized and observational implementation science endeavors, are a critical specific contribution that I bring to the table in these endeavors. For example, in the area of diabetes prevention, I provide leadership to a large group of researchers throughout the world as part of the Global Nutrition and Epidemiologic Transition Initiative.