Political decision making in the COVID-19 pandemic: The case of germany from the perspective of risk management

GND
130030538
ORCID
0000-0001-8649-8695
Affiliation
Faculty of Social and Behavioural Sciences, Friedrich Schiller University Jena
Daumann, Frank;
ORCID
0000-0002-6253-9322
Affiliation
Faculty of Management, Seeburg Castle University
Follert, Florian;
ORCID
0000-0002-6246-7840
Affiliation
Faculty of Business and Economics, Technical University Dresden
Gleißner, Werner;
Affiliation
FutureValue Group AG, 70771 Leinfelden-Echterdingen
Kamarás, Endre;
Affiliation
Dornbach GmbH, 66113 Saarbrücken
Naumann, Chantal

The COVID-19 pandemic is permanently changing modern social and economic coexistence. Most governments have declared infection control to be their top priority while citizens face great restrictions on their civil rights. A pandemic is an exemplary scenario in which political actors must decide about future, and thus uncertain, events. This paper tries to present a tool well established in the field of entrepreneurial and management decision making which could also be a first benchmark for political decisions. Our approach builds on the standard epidemiological SEIR model in combination with simulation techniques used in risk management. By our case study we want to demonstrate the opportunities that risk management techniques, especially risk analyses using Monte Carlo simulation, can provide to policy makers in general, and in a public health crisis in particular. Hence, our case study can be used as a framework for political decision making under incomplete information and uncertainty. Overall, we want to point out that a health policy that aims to provide comprehensive protection against infection should also be based on economic criteria. This is without prejudice to the integration of ethical considerations in the final political decision.

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License Holder: © 2021 by the authors.

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This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.