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Synthetic Reproduction and Augmentation of COVID-19 Case Reporting Data by Agent-Based Simulation Cover

Synthetic Reproduction and Augmentation of COVID-19 Case Reporting Data by Agent-Based Simulation

Open Access
|Apr 2021

Abstract

We generate synthetic data documenting COVID-19 cases in Austria by the means of an agent-based simulation model. The model simulates the transmission of the SARS-CoV-2 virus in a statistical replica of the population and reproduces typical patient pathways on an individual basis while simultaneously integrating historical data on the implementation and expiration of population-wide countermeasures. The resulting data semantically and statistically aligns with an official epidemiological case reporting data set and provides an easily accessible, consistent and augmented alternative. Our synthetic data set provides additional insight into the spread of the epidemic by synthesizing information that cannot be recorded in reality.

Language: English
Submitted on: Nov 10, 2020
Accepted on: Mar 13, 2021
Published on: Apr 27, 2021
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2021 Nikolas Popper, Melanie Zechmeister, Dominik Brunmeir, Claire Rippinger, Nadine Weibrecht, Christoph Urach, Martin Bicher, Günter Schneckenreither, Andreas Rauber, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.