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@SABS-R3-Epidemiology

SABS-R3-Epidemiology

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SABS Epidemiology

This organization page contains the software packages and research outputs which are being developed and released by the Epidemiology Project affiliated with the SABS:R3 Center for Doctoral Training at the University of Oxford. Our goal is to combine rigorous, project-based training in academic software engineering with important and high-impact epidemiological modelling research. Our work has been inspired by collaborations with industry partners, and some of our primary interests include agent-based modelling, Bayesian inference in epidemiology, effective reproduction numbers, and agile research software development.

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  1. branchpro branchpro Public

    Using branching processes to estimate the time-dependent reproduction number of a disease with imported cases

    Jupyter Notebook 5 2

  2. epiabm epiabm Public

    Epidemiological agent-based modelling packages in both python and C++. Published at: https://doi.org/10.5334/jors.449.

    C++ 20 5

  3. seirmo seirmo Public

    This is a project to model the outbreak of an infectious disease with the SEIR model.

    Python 2 2

  4. epicluster-results epicluster-results Public

    Results for learning changes in disease transmission using Bayesian nonparametrics

    Jupyter Notebook 2

  5. EpiGeoPop EpiGeoPop Public

    Snakemake workflow to generate country-specific population density data, for use in epidemiological modeling

    Python 3

  6. EpiOS EpiOS Public

    Software for optimising sampling strategies using Epiabm output

    Python 1

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