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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.

Analysis of PHE covid19 data for weekly SPI-M reports

Repository containing the Covid19UK pipeline

Add-on classes for Tensorflow Probability provided by GEM. This is a transitional repo, intended to be incorporated into GEM eventually.

This project has been migrated to https://gitlab.com/gem-epidemics/gemlib

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

The DRUM agent-based model.

Grabs ISO8601 date-named folders from an SFTP server.

Pseudomarginal inference on SIR and SIS models, motivated by Rebecca Lester's community study...hence the package name.

Examples of epidemic likelihood functions

Language examples for epidemic modelling language

Algorithm examples for GEM project

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