Metadata-Version: 2.1
Name: epistoch
Version: 0.1.13
Summary: Epidemics Models with Random Infectious Period
Home-page: https://github.com/griano/epistoch
Author: Germán Riaño
Author-email: griano@germanriano.com
License: MIT license
Description: 
        ========
        EpiStoch
        ========
        
        
        .. image:: https://img.shields.io/pypi/v/epistoch.svg
                :target: https://pypi.python.org/pypi/epistoch
        
        .. image:: https://travis-ci.com/griano/epistoch.svg?branch=master
            :target: https://travis-ci.com/griano/epistoch
        
        .. image:: https://readthedocs.org/projects/epistoch/badge/?version=latest
                :target: https://epistoch.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        
        
        
        Epidemics Models with Random Infectious Period
        ----------------------------------------------
        
        This software allows you to model epidemics with general random distribution for the infectious period.
        
        Traditional epidemiology models, like SIR, do not take into account the distribution for the length of
        the infectious period. In this software, we include three functions that compute these type of models
        using other distributions.
        
        .. image:: https://github.com/griano/epistoch/raw/master/docs/_static/DIVOC-SIR-comp.png
        
        In this graph you can see how different the predictions are for the regular SIR model with respect to SIR-G
        that actually uses a more realistic distribution for the infectious period.
        In SIR-G case the peak of infection occurs before, and has a bigger intensity.
        The number of individuals that eventually get infected, however, remains the same for both models
        
        
        Models
        ------
        * `SIR <https://epistoch.readthedocs.io/en/latest/epistoch.html#epistoch.sir_g.sir_classical>`_: Classical SIR model, with (implied) exponential infectious period.
        * `SIR_G <https://epistoch.readthedocs.io/en/latest/epistoch.html#epistoch.sir_g.sir_g>`_: Like the classical SIR model, but with an arbitrary distribution.
        * `SIR-PHG <https://epistoch.readthedocs.io/en/latest/epistoch.html#epistoch.sir_phg.sir_phg>`_: A SIR model with Phase-Type distributions for the infectious period.
        * `SEIRD <https://epistoch.readthedocs.io/en/latest/epistoch.html#epistoch.seird_ph.seird_ph>`_: A SEIRD Model with hase-Type distributions for each stage.
        
        Notes
        -----
        
        * The theoretical foundation of the method is explained in this paper_.
        * Documentation: https://epistoch.readthedocs.io.
        * Source Code: https://github.com/griano/epistoch.
        * Free software: MIT license. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
          EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
          FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
        
        
        
        
        .. _paper: https://github.com/griano/epistoch/blob/master/paper/epistoch/epi_stoch.pdf
        
        
        =======
        History
        =======
        
        1.0 (2020-05-01)
        ------------------
        
        * First release on PyPI.
        
Keywords: epistoch
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
