Epidemic forecasting in Python¶
Welcome to the epifx documentation. This package uses a bootstrap particle filter (pypfilt) to generate forecasts of infectious disease epidemics.
Note
This documentation assumes that you are already familiar with the pypfilt package. If this is not the case, please read the pypfilt Getting Started tutorial before proceeding.
The epifx package provides a number of new components and features on top of those provided by the pypfilt package, including:
- Epidemic models
- Observation models for case count data
- Epidemic summary statistics
- Fitting flexible model prior distributions
- Running forecasts from the command-line (todo: worked TOML example)
Installation¶
You can install epifx using pip
, preferably in a
virtual environment:
pip install epifx
See the pypfilt documentation for further details about installation.
License¶
The code is distributed under the terms of the BSD 3-Clause license (see
LICENSE
), and the documentation is distributed under the terms of the
Creative Commons BY-SA 4.0 license.
- Contributing to epifx
- Testing with tox
- Release process
- Change Log
- 0.6.1 (2020-10-20)
- 0.6.0 (2020-08-13)
- 0.5.8 (2020-04-03)
- 0.5.7 (2020-03-28)
- 0.5.6 (2018-06-07)
- 0.5.5 (2017-10-26)
- 0.5.4 (2017-08-17)
- 0.5.3 (2017-08-16)
- 0.5.2 (2017-08-16)
- 0.5.1 (2017-06-15)
- 0.5.0 (2017-05-10)
- 0.4.3 (2016-09-16)
- 0.4.2 (2016-06-16)
- 0.4.1 (2016-04-22)
- 0.4.0 (2016-04-22)
- 0.3.1 (2016-02-25)
- 0.3.0 (2016-02-23)
- 0.2.0 (2015-11-17)
- 0.1.10 (2015-07-09)
- 0.1.9 (2015-07-06)
- 0.1.8 (2015-06-18)
- 0.1.7 (2015-06-18)
- 0.1.6 (2015-06-08)
- 0.1.5 (2015-06-04)
- 0.1.4 (2015-06-03)
- 0.1.3 (2015-06-01)
- 0.1.2 (2015-06-01)
- 0.1.1 (2015-05-29)
- 0.1.0 (2015-05-29)