Metadata-Version: 2.1
Name: epyestim
Version: 0.1
Summary: UNKNOWN
Home-page: https://github.com/lo-hfk/epyestim
License: MIT License
Description: # epyestim
        
        ## Introduction
        
        epyestim estimates the effective reproduction number
        from time series of reported case numbers of epidemics. It is a
        Python reimplementation of the method outlined by
        Huisman et al. [1], making use of the method by Cori et al. [2]
        to estimate the reproduction number R from infection data, 
        available in the R package EpiEstim [3].
        
        The main steps for estimation of the effective reproduction number are:
        
          * Bootstrapping the series of reported case numbers
          * Smoothing using a LOWESS filter
          * MLE of the infection incidence time series
            using an adaptation of the Richardson-Lucy deconvolution algorithm.
          * Bayesian estimation of the effective reproduction number using the
            method of Cori et al. [2]
            
        Aggregate estimates for the reproduction number are obtained by bootstrap
        aggregation (bagging).
        
        The user can choose to output either time-varying estimates or piecewise
        constant estimates on fixed arbitrary time intervals.
        
        ## How to install epyestim
        
        ```
        pip install epyestim
        ```
        
        ## How to use epyestim
        
        Basic usage of the epyestim package applied to COVID-19 data is explained
        in the [Jupyter tutorial notebook](https://github.com/lo-hfk/epyestim/blob/main/notebooks/covid_tutorial.ipynb).
        
        The core functions relevant for users are:
        
        * `epyestim.bagging_r` for the complete estimation process
          outlined above
        * `epyestim.covid19.r_covid` for the same function with default
          parameters for COVID-19
        * `epyestim.estimate_r.estimate_r` for the R estimation from
          infection numbers, based on the EpiEstim package
        
        ## Authors
        
        * [Lorenz Hilfiker](mailto:lorenz.hilfiker@gmail.com)
        * [Johannes Josi](mailto:johannes@josi.info)
        
        ## How to contribute
        
        Error reports and suggestions for improvements via GitHub issues
        are very welcome.
        
        ## References
        
        [1] Jana S. Huisman, Jeremie Scire, Daniel Angst, Richard Neher,
        Sebastian Bonhoeffer, Tanja Stadler: A method to monitor the effective
        reproductive number of SARS-CoV-2
        https://ibz-shiny.ethz.ch/covid-19-re/methods.pdf
        
        [2] Anne Cori, Neil M. Ferguson, Christophe Fraser, Simon Cauchemez:
        A New Framework and Software to Estimate Time-Varying Reproduction
        Numbers During Epidemics, American Journal of Epidemiology, Volume 178,
        Issue 9, 1 November 2013, Pages 1505–1512,
        https://doi.org/10.1093/aje/kwt133
        
        [3] EpiEstim CRAN package:
        https://cran.r-project.org/web/packages/EpiEstim/index.html
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: tests
