mdsunivie / effdi

Python package to compute the effective dispersion index (EffDI).

Description

Python package to compute the effective dispersion index (EffDI).

Publication

G. Schneckenreither, L. Herrmann, R. Reisenhofer, N. Popper, P. Grohs
Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data
medRxiv 2022.02.21.22271241 (2022)
https://doi.org/10.1101/2022.02.21.22271241

Please consult Section 4.2 of this paper for technical explanations of the EffDI.

When you find this code useful for your own research, please cite the mentioned paper above.

Installation

Clone the repository and use

pip install -e EffDI/

to install the package.

Usage of EffDI

In the first step results for the evaluation of the EffDI are computed and stored in the results/ folder. In the second step, these results are visualized and stored in the plots/ folder.

In the example of COVID-19 reported cases based on the file time_series_covid19_confirmed_global.csv, using default parameters, EffDI for any country in this data file may be computed. Please download and store this at the location, from where EffDI called. Otherwise parse the location to the respective function calls. The following commands serve as an example of how to use EffDI.

Pre-compute the inverse and forward weights by

effdi pre_compute_weights

Compute results for EffDI for a selection of countries by

effdi compute --countries "Austria" "Italy" "Korea, South"

Create a detailed plot for any of the countries, where you computed results for, by

effdi demo_country --country "Austria"

Create a plot comparing a selection of countries, where you computed results for, by

effdi demo_countries --countries "Austria" "Italy" "Korea, South"

Contributions

The EffDI Python package was developed by Lukas Herrmann, Rafael Reisenhofer and Günter Schneckenreither.

If you have any questions, please contact [email protected].