Stephen A. Lauer



I am a postdoctoral researcher in the Infectious Disease Dynamics Group at Johns Hopkins Bloomberg School of Public Health. My current research focuses on estimating the burden and distribution of cholera in Bangladesh based on serological biomarkers. As a side project, I have estimated some of the epidemiological parameters of the recent 2019-nCoV outbreak.

During my PhD at UMass, I worked with the Thailand Ministry of Public Health to forecast dengue fever incidence at short and long time scales. During my time as a grad student, I developed a number of Shiny web applications for various projects (SEIGMA, dengue predictions, and ALERT).

Outside of the office, my interests include sports, travel, economics, voting reform, transportation issues, and video games. Check out my full bio for more details!


  • Probabilistic Forecasting
  • Causal Inference
  • Data Analysis and Visualization


  • PhD in Biostatistics, 2019

    University of Massachusetts, Amherst

  • MS in Biostatistics, 2014

    University of Massachusetts, Amherst

  • BS in Business, Operations Management, 2009

    University of Maryland, College Park



Postdoctoral Researcher

Johns Hopkins Bloomberg School of Public Health

Apr 2019 – Present Baltimore, MD

  • Estimate the seroincidence rate of cholera in Bangladesh using Bayesian hierarchical models (compiled in Stan)
  • Make geospatial maps based on clustered data using integrated nested Laplace approximations (INLA)
  • Fit a random forest model to cohort data and use it to predict cholera seropositivity
  • Model the decay in the sensitivity of diagnostic tests based on serological biomarkers over time

Research Assistant

University of Massachusetts

Jan 2013 – Feb 2019 Amherst, MA

  • Built and cross-validated forecasting models for annual dengue fever incidence
  • Developed a causal inference technique for estimating the effect of an event on an outcome
  • Assisted in development of the ALERT algorithm for determining the onset of the flu season
  • Built an R package and a Shiny web app in support of the ALERT algorithm
  • Developed a series of Shiny web apps to measure social statistics for SEIGMA project

Leadership, Mentoring, & Teaching

Kristina Yamkovoy

Lecturer, Introduction to Statistical Computing in R

Graduate Student Senator

Co-founder and Treasurer, Graduate Researchers in Data (GRiD)


Elected to Rho Chapter of Delta Omega Honorary Society

First Place Award for Outstanding Research Articles in Biosurveillance

Dean’s PhD Fellowship

Academic Honors

More about me

Won March Madness Pool

Created an algorithm that correctly predicted March Madness winners to win a March Madness pool with 432 applicants

Back-to-Back Fantasy Football League Champion

Developed an R program to guide draft strategy and a Shiny app to make live decisions

Taught English in China

Learned to speak Mandarin (conversational fluency) and traveled around China

NFL Analytics Intern

Contributed to Football Outsiders Almanac 2009

Olympic Flash Quotes Reporter

Interviewed handball players and met the USA basketball team

NCAA Media Relations

Recorded statistics and interviewed athletes/coaches for University of Maryland sports teams (water polo, volleyball, baseball); also served as the mascot to promote a bowl game

Recent Publications

The incubation period of 2019-nCoV from publicly reported confirmed cases: estimation and application

A novel human coronavirus (2019-nCoV) was identified in China in December, 2019. There is limited support for many of its key …

Infectious disease prediction with kernel conditional density estimation

Creating statistical models that generate accurate predictions of infectious disease incidence is a challenging problem whose solution …

Recent Posts

Reflecting back on the old travel blog

Out with the old, in with the new