Professor of Epidemiologic Methods
Our team was recently showcased by the Harvard Multi-media team for our work in Environmental Epidemiology, supported by NIH Grant R01 ES 09411. For more information about our validation study of particulate matter ambient (PM2.5), click here.
Epi 515 – Measurement Error and Misclassifcation Epidemiology
For the Fall 1 quarter for 2015, Dr. Spiegelman is teaching Epi 515 “Measurement Error and Misclassfication Epidemiology.” This class will be co-taught with Dr. Molin Wang, with assistance from their doctoral student TA Sarah Peskoe. Please click here for more information.
Current Post Doctoral Fellow Opening:
Dr. Spiegelman is actively searching for a post doctoral fellow to join her group. This position will work in collaboration with Dr. Spiegelman and her colleagues in the Departments of Epidemiology, Biostatistics, Nutrition, Global Health and Health Policy and Management. It is envisioned that this position will focus on some or all of the following:
- Evaluation of health outcomes in relation to the roll-out of the Affordable Care Act in a “Big Data” context
- Proposal development of cervical cancer vaccine implementation trials in domestic and global settings
- Evaluation of cervical cancer screening and treatment programs in Dar Essex Salaam, Tanzania
- Co-editing a book or monograph on Implementation science and translational epidemiology, focusing on methods
- Co-developing a short course on implementation science methodology
Background in the above areas is not necessarily required but is a plus. Competitive candidates should, however, demonstrate keen interest in one or more of the above topics
If interested, please visit here for the full job description as well as steps to apply.
September 2015 – Two New Post-Doctoral Fellow joins Dr. Spiegelman’s group:
Dr. Xin Zhou joins Dr. Spiegelman’s group as a post-doctoral fellow to work on developing optimal screening algorithms for colorectal cancer prevention after completing his PhD in Biostatistics from the University of North Carolina at Chapel Hill. His dissertation focused on using machine learning techniques to develop optimal treatment regimes for precision medicine. His research interests include machine learning, optimal treatment regimes, dynamic treatment regimes and high dimensional data analysis.
Xin likes sports such as soccer, badminton and cycling. He also enjoys travelling and sight-seeing with his family.
Dr. Daniel Nevo has completed his PhD in statistics from the Hebrew University of Jerusalem under the supervision of Prof. Ya’acov Ritov. His thesis involved both theoretical challenges and applications in biostatistics. He worked on model selection in high-dimensional regression and on Bayesian robust regression when the number of predictors and the number of samples grow in a similar rate. His research also involved the development of methods to account for measurement error in biomarkers and misclassification of subtypes in the analysis of tumor data. Daniel also worked on construction of reference charts for fetal measurements.
As a post-doctoral fellow in Dr. Spiegelman’s group, Daniel will work on statistical methods for implementation science and the analysis of tumor subtype data using biomarkers. Daniel likes hanging out with his family (wife, daughter, cat), sports, statistics, and learning new things.
August 2015 – New Post-Doctoral Fellow joins Dr. Spiegelman’s group:
Dr. Archana Shrestha completed her PhD in Epidemiology from the University of Washington. Her dissertation was focused on exploring dietary patterns and their association with Type II diabetes and obesity in urban Nepal. She is interested in developing, testing, and implementing preventive interventions to reduce the impact of global diabetes and cardiovascular disease epidemics in low and middle-income countries. She will work on a worksite-based diabetes and cardiovascular disease prevention program in India contributing to study design, project management, data analysis, and manuscript development under Dr. Spiegelman’s supervision and in collaboration with colleagues at Emory University and the Public Health Foundation of India, Delhi (PHFI). The context of the research is an ongoing global effort to prevent diabetes and cardiovascular disease through primary prevention, including dietary and activity changes. Apart from indulging in data, she likes to swim, dance, paint, and walk.
July 2015 – New Post-Doctoral Fellow joins Dr. Spiegelman’s group:
Dr. Claudia Rivera joined Dr. Spiegelman’s team after completing her PhD in Biostatistics at the University of Auckland in New Zealand under the supervisor of Dr. Thomas Lumley. In her dissertation, she focused on applying survey-sampling methods to improve efficiency of proportional hazard models under two phase sampling designs induced by risk-set samples. The methods make use of information on the entire cohort. She is also interested in efficiency of estimators when the sampling mechanism is not independent such as risk-set sampling designs. In her new positions as a postdoctoral fellow at the in the Departments of Epidemiology and Biostatistics, Claudia is investigating methods that yield better estimates under two-phase sampling designs when the auxiliary information is only marginal. Claudia is a vegan and runner that loves sustainability programs. She likes traveling (especially Asia) and getting to know other cultures and people.
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.