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

Tutorials to learn real-time analysis that includes accessing epidemiological delays, estimating transmission metrics, forecasting, and severity from aggregated incidence data, superspreading from line list and contact data, and simulating transmission chains.

Tutorials to learn accessing and analyzing social contact matrices, scenario modelling to simulate disease spread and investigate interventions, and modelling disease burden.

Tutorials to learn reading, cleaning and validating case data, and converting line list data to incidence for visualizing epidemic curves.

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