Suzanne M. Dufault, PhD

Postdoctoral Scholar in Biostatistics

University of California, San Francisco


I am a biostatistics postdoctoral researcher and TB RAMP scholar at the University of California, San Francisco’s Division of Pulmonary and Critical Care Medicine. Working in close collaboration with UNITE4TB, my current research explores statistical approaches for decision-making in multi-arm regimen-building Phase IIB trials.

I continue to collaborate with the World Mosquito Program to develop and apply novel statistical methodology for the analysis of data from (quasi-)experimental trial designs aimed at assessing the effectiveness of Wolbachia in the control of dengue.

Through consultancies and shorter-term research opportunities, I have also gained experience working with occupational cohort data, survey data, and biomedical big data.


  • biostatistics
  • epidemiology
  • social epidemiology
  • cluster randomized trials
  • phase IIB trials
  • test negative design
  • infectious diseases
  • reproducible research
  • innovative approaches to teaching


  • PhD in Biostatistics, 2020

    University of California, Berkeley

  • MA in Biostatistics, 2017

    University of California, Berkeley

  • BA in Applied Mathematics and Statistics, 2015

    Macalester College

Recent Publications

Suicide, overdose and worker exit in a cohort of Michigan autoworkers

US suicide and overdose mortality rates are rising for working-age adults with no college education. Manufacturing has been declining …

Recent Media

Notable Articles of 2021

Our article (Utarini et al) reporting the primary results from the Applying Wolbachia to Eliminate Dengue (AWED) study was highlighted by the NEJM as one of the thirteen most clinically important articles published in the journal in 2021.

Breaking New Ground in Biostatistics

Suzanne Dufault ‘15 applies a biostatistics lens to pressing public health problems including dengue fever.

Les annees lumieres: Wolbachia, une alliee microscopique dans la lutte contre les virus.

Lutter contre la dengue avec une bacterie: Les details avec Renaud Manuguerra.

Study Shows Efficacy of Method for Reducing Dengue Fever Incidence

They found that using the Wolbachia method reduced the occurrence of dengue in the treated population by 77%, according to Jewell. This method involves introducing Wolbachia, a type of bacteria, into populations of Aedes aegypti, the mosquito species responsible for spreading dengue, according to Dufault.



Deaths of Despair

Working with Ellen Eisen, ScD at the University of California, Berkeley, we used an iconic occupational cohort database to explore the …

Statistical Methods for Clinical Trials of TB Therapeutics

My postdoctoral research at UCSF has focused on the development of a Bayesian-supported framework for decision-making in adaptive Phase …

Breast Cancer Research

Working with Mark Powell, MD MPH at the Buck Institute, I help examine genotype and blood biomarkers and their associations with …

Statistical Methods for Vector-Borne Disease Prevention

Vector-borne diseases are a growing threat to global health. I help develop statistical methods to rigorously evaluate the impact of …

Awards and Certificates

Chin Long Chiang Award for Outstanding Doctoral Student

UC Dissertation-Year Fellowship

Statistical Significance Poster Award Runner Up

Joint Statistical Meetings Student Travel Award

Outstanding Graduate Student Instructor

Group 1 Biomedical Research Investigators Certification

See certificate

Research Aspects of HIPAA

Reshetko Family Scholarship in Honor of Chin Long Chiang