Software Open Access
# Digital Contact Tracing
This package provides the simulation, analysis, and figure code for
the manuscript "Digital contact tracing contributes little to COVID-19
outbreak containment" by A. Burdinski, D. Brockmann, and B. F. Maier.
The analysis code was used and tested for Python 3.8 on CentOS, Ubuntu, and MacOS.
In order to run code in this collection, first install the requirements:
pip install -r requirements.txt
Models are implemented using [epipack](github.com/benmaier/epipack). To run
large-scale simulations, we use [qsuite](github.com/benmaier/qsuite), a CLI
to facilitate simulations on HPC clusters. `qsuite` will be installed when
dependencies are installed from `requirements.txt`.
## Main model
The main model, including an example configuration,
can be found in directory `main_model/`.
To run the simulation, do
Almost all simulations and analyses performed in the paper
can be found in `analysis_collection/tracing_sim/`.
All extracted (summarized) data can be found in
Code to produce the figures in the main text from distilled analysis
results and analyses for the locally clustered network with
exponential degree distribution can be found in
Code for plots in the SI can be found in
`analysis_collection/tools.py` except for Fig. S7-S8-- those can
be found in the respective directories
In order to replicate the simulations, change to the directory containing the
respective analysis and run `qsuite local`, e.g.
An illustration to justify the choice of `beta = 10^(-6)` as the long range
redistribution parameter beta can be found by running