Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread
David Kerkmann, Sascha Korf, Khoa Nguyen, Daniel Abele, Alain Schengen, Carlotta Gerstein, Jens Henrik G\"obbert, Achim Basermann, Martin J. K\"uhn, Michael Meyer-Hermann

TL;DR
This paper introduces a detailed agent-based model to simulate human mobility and contact behavior for evaluating COVID-19 mitigation strategies, emphasizing testing and quarantine policies' effectiveness.
Contribution
The model's modular design and regional mobility data enable realistic simulation of disease spread and intervention impacts at various scales.
Findings
Symptom-independent testing has limited mitigation impact with high asymptomatic cases.
Quarantine length influences disease control more than quarantine efficiency.
Short quarantines can be effective with sufficient symptomatic control.
Abstract
Agent-based models have proven to be useful tools in supporting decision-making processes in different application domains. The advent of modern computers and supercomputers has enabled these bottom-up approaches to realistically model human mobility and contact behavior. The COVID-19 pandemic showcased the urgent need for detailed and informative models that can answer research questions on transmission dynamics. We present a sophisticated agent-based model to simulate the spread of respiratory diseases. The model is highly modularized and can be used on various scales, from a small collection of buildings up to cities or countries. Although not being the focus of this paper, the model has undergone performance engineering on a single core and provides an efficient intra- and inter-simulation parallelization for time-critical decision-making processes. In order to allow answering…
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Taxonomy
TopicsCOVID-19 epidemiological studies
