epysurv: Epidemiological Surveillance in Python¶
epysurv is a pythonic wrapper around the R surveillance package.
It’s main goal is to predict disease outbreaks, right
now focusing on univariate count time series.
epsurv operates on pandas
DataFrames and strives to implement a scikit-learn like API.
epysurv supports two problem formalizations of outbreak detection: time point classification and time series classification.
This documentation mainly explains the usage of
epysurv and the ideas behind the problem formalizations. For more
details about the algorithms have a look at the vignette
of the R surveillance package or the literature references in the model docstrings.
This package was originally developed at the Robert Koch Institute in the Signale Project .