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Lee Kennedy-Shaffer, PhD

he/him/his
Assistant Professor of Biostatistics
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Education

PhD
Harvard University, Biostatistics (2020)


MA
Harvard University, Biostatistics


About

Titles

Assistant Professor of Biostatistics

Biography

Lee Kennedy-Shaffer is an Assistant Professor (Educator-Scholar Track) in Biostatistics. Lee received his PhD in Biostatistics under Dr. Michael Hughes in the Harvard T.H. Chan School of Public Health and conducted epidemiologic research there with Drs. Marc Lipsitch and Michael Mina in the Center for Communicable Disease Dynamics. He was an Assistant Professor in the Vassar College Department of Mathematics and Statistics from 2020–2024.

His research focuses on randomized and observational study designs and methods for the analysis of infectious disease interventions. This includes mathematical modeling, cluster-randomized trials, and quasi-experimental designs, all with an eye toward broader population health impacts than are usually addressed by individually randomized trials. He has worked on COVID-19 data collection and analysis as well, in particular accounting for the timing and correlation of infections in interpreting test results. This work has been published in journals such as Science, Statistics in Medicine, Clinical Trials, the American Journal of Epidemiology, and the American Journal of Public Health, among others. In addition, he has written on the history of statistics, FDA policy, statistics education, and causal inference in baseball.

Appointments

Other Departments & Organizations

Education & Training

Postdoctoral Fellow
Harvard T.H. Chan School of Public Health
PhD
Harvard University, Biostatistics (2020)
MA
Harvard University, Biostatistics
BS
Yale University, Mathematics

Research

Overview

Infectious disease studies face many statistical and epidemiological challenges, of which three of the most significant and unique are: (1) clustering and correlation of outcomes among individuals; (2) high spatiotemporal variation, especially in outbreak and epidemic settings; and (3) different estimands at individual and population levels. These make common statistical assumptions—including independence, parallel trends, exchangeability, and homogeneous effects—unlikely to hold for a variety of exposures and outcomes. Understanding infectious disease interventions thus requires the development of new study designs and new methods for analysis, or the modification of existing ones to address these challenges. These engender tradeoffs, however, on the epidemiological, statistical, and policy levels.

Specific areas of research include:

  • Developing cluster-randomized trial and stepped-wedge trial designs and analysis methods,
    Quantifying and using spatiotemporal variation in infectious disease outbreaks to improve surveillance and studies of interventions,
    Designing studies to understand the full spectrum of effects of vaccines and other infectious disease interventions,
    The communication, education, and history of statistics, and
    Exploring the policy implications of statistical methods.

Medical Research Interests

Biostatistics; Communicable Diseases; Data Science; Drug Evaluation; Epidemiologic Methods; Models, Statistical; Regression Analysis; Vaccine-Preventable Diseases

Public Health Interests

Randomized Trials; Infectious Diseases; History of Medicine and Science; Epidemiology Methods; COVID-19; Clinical Trials

Research at a Glance

Research Interests

Research topics Lee Kennedy-Shaffer is interested in exploring.

Publications

Featured Publications

Academic Achievements & Community Involvement

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    Nature Medicine

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    Epidemiologic Methods

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    Quasi-experiments in epidemiology: Difference-in-differences, synthetic control, and staggered adoption designs

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    Teaching the difficult past of statistics to improve the future

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    Vaccine Efficacy Against Transmission: Statistical and Epidemiological Considerations

Get In Touch

Contacts

Academic Office Number

Locations

  • 300 George Street

    Academic Office

    Ste 501, Rm 529b

    New Haven, CT 06511