Christian Testa

I am a statistical data analyst at the Harvard T.H. Chan School of Public Health working with the Public Health Disparities Geocoding Project. I received my Bachelors of Science in Mathematics from Tufts University in 2017.

Research Interests

My research interests focus on mathematical modeling techniques and their public health applications.

Techniques I have been working with recently include:

  • Causal inference
  • Bayesian methods
  • Spatial statistics
  • Model selection
  • Differential equations modeling

My recent work has focused on applying these techniques to understand disparities in COVID-19 outcomes, how discrimination throughout the lifecourse is manifested through changes in epigenetic markers as it relates to epigenetic aging, and how experiences of multifactorial types of discrimination impact people’s health.

My previous work with the Prevention Policy Modeling Lab focused on using dynamic models of infectious diseases to estimate optimal intervention strategies.


Feel free to check out my publications or Google Scholar page.