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Marc Diederichs

Johannes Gutenberg University Mainz

Saarstr. 21

Jakob Welder-Weg 4

Mainz, 55122

Germany

  • Johannes Gutenberg University Mainz

SCHOLARLY PAPERS

3

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177

TOTAL CITATIONS

1

Scholarly Papers (3)

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1.

Schools Under Mandatory Testing Can Mitigate the Spread of Sars-Cov-2

IZA Discussion Paper No. 14844
Number of pages: 21 Posted: 02 Jun 2022 Last Revised: 30 Nov 2022
Ingo E. Isphording, Marc Diederichs, Reyn van Ewijk and Nico Pestel
IZA Institute of Labor Economics, Johannes Gutenberg University Mainz, Johannes Gutenberg University Mainz - Department of Economics and Maastricht University
Downloads 71 (875,328)

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COVID-19, schooling, education, Germany

2.

Is Large-Scale Rapid CoV-2 Testing a Substitute for Lockdowns?

Number of pages: 44 Posted: 26 Aug 2021
Marc Diederichs, René Glawion, Peter G. Kremsner, Timo Mitze, Gernot J. Müller, Dominik Papies, Felix Schulz and Klaus Wälde
Johannes Gutenberg University Mainz, University of Hamburg, Lambaréné Medical Research Center (CERMEL), Lambaréné, University of Southern Denmark, University of Tübingen - Department of Economics, University of Tübingen - Faculty of Economics and Social Sciences, Johannes Gutenberg University Mainz and Johannes Gutenberg University Mainz - Gutenberg School of Economics and Management
Downloads 56 (1,010,164)
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3.

Is Large-Scale Rapid Cov-2 Testing a Substitute for Lockdowns? The Case of Tuebingen

IZA Discussion Paper No. 14334
Number of pages: 42 Posted: 15 May 2021 Last Revised: 18 Nov 2021
Marc Diederichs, Peter Kremsner, Timo Mitze, Gernot J. Müller, Dominik Papies, Felix Schulz and Klaus Wälde
Johannes Gutenberg University Mainz, University of Tübingen, University of Southern Denmark, University of Tübingen - Department of Economics, University of Tübingen - Faculty of Economics and Social Sciences, Johannes Gutenberg University Mainz and Johannes Gutenberg University Mainz - Gutenberg School of Economics and Management
Downloads 50 (1,074,648)

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(correcting the) bias, COVID-19, reported number of CoV-2 infections, number of tests, SIR model, unbiased epidemiological severity index