I've built open-source data science tools for epidemiologists and public health teams, primarily in R. Much of this work was funded by the CDC's Center for Forecasting and Outbreak Analytics and focuses on making disease surveillance, modeling, and reporting faster and more accessible.
An R package for generating disease surveillance reports from EpiTrax, the central repository for epidemiological data used by many public health departments. epitraxr makes it fast and flexible to manipulate EpiTrax exports, tailor reports for internal or public audiences, and publish them as CSV, Excel, or PDF.
A fast framework for agent-based epidemiological models. The core epiworld C++ library can simulate tens of millions of agents per second. The epiworldR package (and epiworldRShiny app) brings that speed to R for prototyping outbreaks, transmission dynamics, and mitigation policies.
An R package for keeping an organization's R projects visually consistent and accessible. rbranding manages branding assets and organization-wide themes via the brand.yml standard, and sets up new Quarto, Shiny, and R Markdown projects with correct branding and accessibility defaults from the start.
A template for fully automated disease forecasting. epiworld-forecasts combines epiworldR, GitHub Actions, and Docker to produce forecasts that rebuild and republish themselves on a schedule. The included example forecasts COVID-19 case counts in Utah. The template is designed to be adapted to other diseases and regions with minimal changes.