2021-10-21 19:59:58

About me

  • Originally from Germany, moved to U.S. for graduate school - and never left 😄.
  • PhD in Physics at Georgia Tech, Postdoc in Computational Biology at Emory.
  • Since 2009, Assistant/Associate/Full Professor in Epidemiology & Biostatistics, University of Georgia.
  • Data analysis and modeling of infectious diseases on the population and individual host levels.
  • Mainly influenza and norovirus, some TB and other bugs. Recently also a lot of SARS-CoV-2.
  • More information:

Motivation for this talk

  • After 15+ years of basic science/research, I want to move towards more applied work.
  • To get that process started, I want to do a short term (approx. 8 month) industry “internship”.
  • This presentation is part of my looking for something effort.

Talk Overview

  • Part 1: Research on dosing for vaccines
  • Part 2: Various other projects (R packages, online courses)
  • Part 3: Q&A

Part 1 - Inoculum dose


  • Inoculum dose is an important determinant of infection and vaccination outcomes.
  • For infection, higher dose is often associated with greater risk of infection (ID50) and more severe outcomes (LD50).
  • For vaccines, dose is thought to impact both immunogenicity/efficacy and side effects (morbidity).

Important considerations I

  • Trade-offs between availability/safety and efficacy likely exist.
  • Impact of dose on vaccine efficacy might not be monotone.

Important considerations II

  • Impact of dose on homologous or heterologous protection might not be monotone.

Vaccine dose choice in practice

  • A few doses are explored in phase 1 and 2 trials.
  • Based on those data, one of the doses is chosen for phase 3 trials (and beyond) in a non-rigorous manner.

Claim: Knowing in more detail how dose impacts host response following vaccination might help optimize vaccines.

Assessing the impact of dose for influenza vaccines