GitLab

This project contains the Python code for the PhD thesis titled "Joint epidemic and spatio-temporal approach for modelling disease outbreaks" at Lancaster University supervised by Dr. Chris Jewell and Prof. Dr. Peter Neal.

It provides an extension to the Python probabilistic programming library PyMC3 with a sampler to effectively impute missing infection and removal time data. Furthermore, it integrates a mechanistic modeling approach into an epidemiological modeling setting.

BIOL132 Introductory Biostats for 1st year biology students.

This is the repository for the main InFER (Inference for Epidemic Risk) package.

R package to read InFER HDF5-format MCMC output files

GPU implementation of a variogram, wrapped as an R package.

A Bayesian ZIP model which uses covariates on both the Poisson and Binomial parts.

sourceR R package to fit source attribution models

Scripts for reproducing the results in our paper on high-dimensional prediction over subgroups.

Notes from a seminar on RHDF5.

GEM epidemic modelling software base -- https://gem.readthedocs.io/en/latest/

Experiments with ZigZag on SIR epidemic models.

Algorithm examples for GEM project

An R package implementing a modified Reynolds 1986 flocking algorithm.

Language examples for epidemic modelling language

Network epidemic package.