Tools to enable flexible and efficient hierarchical nowcasting of epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes.

Course on nowcasting and forecasting of infectious disease dynamcis

R package to estimate disease severity and under-reporting in real-time, accounting for reporting delays in epidemic time-series

R package for statistical and spatiotemporal modeling of epidemiological data for vector-borne diseases in Colombia

R package to calculate the final size of an SIR epidemic in populations with heterogeneity in social contacts and disease susceptibility

Understanding, evaluating, and improving forecasts of infectious disease burden

[Not published - under active development] A Store of Outbreak Analytics Pipelines Provided as Rmarkdown Report Templates

This project analyzes a cholera outbreak using Python, integrating environmental, historical, and climatic variables to create a predictive model for early detection and response.