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Dtsch. Med. Wochenschr. · Jan 2021
Historical Article[The early phase of the COVID-19 pandemic in Bavaria, Germany].
- Matthias Wjst.
- Institut für Lungenbiologie (iLBD), Helmholtz-Zentrum München, German Research Center for Environmental Health (GmbH), München-Neuherberg.
- Dtsch. Med. Wochenschr. 2021 Jan 1; 146 (1): e1e9e1-e9.
IntroductionThe effect of non pharmacological interventions (NPIs) during an epidemic disease outbreak is well accepted dating back to historical events. NPIs involve numerous measurements like hygiene rules or contact restriction that are applied during given situations, while so far only limited quantitative data exist to rate the overall effectiveness.MethodsUsing the official counts of Robert Koch Institute in Berlin/Germany, press reports and Twitter messages, the early phase of the current COVID-19/Sars-CoV2 in Bavaria is being reconstructed.ResultsThe first cases have been observed in Munich by the end of January 2020. While the initial outbreak could be sufficiently covered using isolation and quarantine measurements, the consecutive early spreading falls into three phases, starting with winter school holidays at the end of February, a number of beer festivals in the following week, and general elections on March, 15. The disaster plan on March, 16 indicates the end of the early phase. Using the official case counts, a rather coherent picture evolves although representative epidemiological studies are still missing. The epidemic started with a few cases during the winter holidays, increased exponentially afterwards including significant more cases by beer festivals and another significant excess of cases following the election that occurred in Bavaria only. Compared to other German countries, Bavaria reached the highest prevalence which could not be reversed by even the most restrictive containment measurements.ConclusionTo be effective, NPIs need to applied early, if possible even before the beginning of the exponential phase.The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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