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Recent Releases of epiabm

epiabm - Epiabm v1.2.1

Small updates to the reporting process for the serial interval, and a bugfix to ensure age group labels are updated concurrently with ages.

What's Changed

  • Recording the serial interval by @mghosh00 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/267
  • Adding the Northern Ireland simulation by @mghosh00 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/274
  • Kc gallagher patch 1 by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/275
  • Age groups by @laraherriott in https://github.com/SABS-R3-Epidemiology/epiabm/pull/276

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/compare/v1.2.0...v1.2.1

- C++
Published by KCGallagher 8 months ago

epiabm - Epiabm v1.2.0

Implementation of waning immunity and new reporting features to allow individual level reporting of infection status and immunity. These reporting features are compatible with EpiOS, which handles various sampling methods for simulated ground-truth data from agent-based models.

What's Changed

  • Docs style bugfix by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/244
  • Add base citation file (#245) by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/246
  • Csv writing by @abbie-evans in https://github.com/SABS-R3-Epidemiology/epiabm/pull/249
  • Testing py2c subpackage by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/234
  • Compression of infection history csv files by @abbie-evans in https://github.com/SABS-R3-Epidemiology/epiabm/pull/252
  • Waning immunity by @tomcodewizard in https://github.com/SABS-R3-Epidemiology/epiabm/pull/253
  • Reviewer comments by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/257
  • Rate multipliers and IgG count by @mghosh00 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/260
  • Secondary infections by @mghosh00 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/263
  • Record the number of people in each age group and cell by @mghosh00 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/265
  • Default workflows bugfix by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/270

New Contributors

  • @mghosh00 made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/247
  • @abbie-evans made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/249
  • @tomcodewizard made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/253

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/compare/v1.1.0...v1.2.0

- C++
Published by KCGallagher over 1 year ago

epiabm - Epiabm v1.1.0

Complete implementation of both pharmaceutical and non-pharmaceutical interventions in pyEpiabm, completed by the SABS cohort 2022. Spatial transmission models have been updated with new sampling procedures, and profile of cell-wise sampling in infection sweeps has resulted in significant performance increases.

What's Changed

  • Care homes by @laraherriott in https://github.com/SABS-R3-Epidemiology/epiabm/pull/162
  • Interventions setup by @jiayuanz3 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/173
  • Vaccination by @laraherriott in https://github.com/SABS-R3-Epidemiology/epiabm/pull/180
  • Disease testing by @laraherriott in https://github.com/SABS-R3-Epidemiology/epiabm/pull/193
  • Functional testing class by @KCGallagher in https://github.com/SABS-R3-Epidemiology/epiabm/pull/199
  • Travel interventions by @HenrietteCapel in https://github.com/SABS-R3-Epidemiology/epiabm/pull/209
  • NZ simulation params by @jiayuanz3 in https://github.com/SABS-R3-Epidemiology/epiabm/pull/232
  • Rt inference by @laraherriott in https://github.com/SABS-R3-Epidemiology/epiabm/pull/239

New Contributors

  • @njs59 made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/167
  • @laraherriott made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/162
  • @jiayuanz3 made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/173
  • @HenrietteCapel made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/190
  • @Ellmen made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/195

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/compare/v1.0.1...v1.1.0

- C++
Published by KCGallagher over 2 years ago

epiabm - Zenodo Release

Release for preservation repository Zenodo

- C++
Published by KCGallagher over 3 years ago

epiabm - Public Release

Public Release

Model State

Both python and C++ backends have full functionality (excluding interventions), with household, spatial and place infection mechanisms as well as internal host progression. Example workflows are provided for varying degrees of simulation complexity, up to and including a national simulation on the state of Gibraltar in both backends, used for benchmarking against CovidSim.

Both backends have fully logging and seed determinism capabilities, and the cEpiabm backend may be called through python bindings, operating on populations constructed in python. Full documentation is available online for both backends (linked in the README), as well as comprehensive parameter documentation being available on our Wiki.

What's Changed

  • C++ and Python updated spatial sweep and kernel
  • C++ and Python reconfigured place sweep
  • C++ and Python complete Gibraltar simulation
  • C++ and Python new cases reporting

  • C++ python bindings
    .

  • Python updated spatial kernel

  • Python updated household storage and allocation

  • Python logging and profiling functionality

  • Python functional and integration testing

  • Python age dependence on infection and host progression
    .

  • Updated workflow examples for varying degrees of complexity

  • Complete documentation for both backends

  • Updated guidance for open-source software contributions

New Contributors

  • @lukedtc made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/71
  • @I-Bouros made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/87
  • @Saketkr21 made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/116
  • @patricia-lamy made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/106
  • @rccreswell made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/129
  • @pitmonticone made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/138

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/compare/v0.0.2...v1.0.0

- C++
Published by KCGallagher over 3 years ago

epiabm - Spatial Transmission

Model State

This version of the software is capable of a full simulation, output and visualisation with spatial dependence and visualisation. It does not have complete implementation of place-wise infection, nor complete within-host progression. It may be used as a basic agent-based model, within the framework of the Ferguson model, for benchmarking further additions to the code. It is not intended as a public release, not a complete implementation of the Ferguson model.

What's Changed

This includes: * Definition of a cells' location, and methods to set this (on an individual and population-wide basis) * A spatial sweep to allow cross-infection between cells, with weighting by distance between the cells * An output logger that outputs .csv files, with subsequent example plotting routines * A plotter capable of representing spatial dependence (to show transmission between cells) using Voronoi tessellation * Capability to read in a population from an input .csv file (and also output the current population) * Ability to set the random seed for a simulation, to aid reproducibility

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/compare/v0.0.1...v0.0.2

- C++
Published by KCGallagher almost 4 years ago

epiabm - Initial Simulation - pyEpiabm

Model State

This is the first state of the software that is capable of a full simulation, output and visualisation. It has no spatial dependence/visualisation and relies on basic transmission through households. It may be used as a basic SEIR model, within the framework of the Ferguson model, for benchmarking further additions to the code. It is not intended as a public release, not a complete implementation of the Ferguson model.

New Contributors

  • @Elizabeth-Hayman made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/4
  • @KCGallagher made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/5
  • @NicholasFan235 made their first contribution in https://github.com/SABS-R3-Epidemiology/epiabm/pull/8

Full Changelog: https://github.com/SABS-R3-Epidemiology/epiabm/commits/v0.0.1

- C++
Published by KCGallagher about 4 years ago