COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach

Michał Burzyński; Joël Machado; Atte Aalto; Michel Beine; Jorge Goncalves; Tom Haas; Françoise Kemp; Stefano Magni; Laurent Mombaerts; Pierre Picard; Daniele Proverbio; Alexander Skupin; Frédéric Docquier

doi:10.1016/j.ehb.2021.101051

COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach

Michał Burzyński, Joël Machado, Atte Aalto, Michel Beine, Jorge Goncalves, Tom Haas, Françoise Kemp, Stefano Magni, Laurent Mombaerts, Pierre Picard, Daniele Proverbio, Alexander Skupin, Frédéric Docquier

Research output: Contribution to journal › Article › peer-review

Abstract

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021.

Original language	English
Article number	101051
Journal	Economics and Human Biology
Volume	43
Early online date	31 Jul 2021
DOIs	https://doi.org/10.1016/j.ehb.2021.101051
Publication status	Published - Dec 2021

Bibliographical note

We acknowledge financial support from the Luxembourg National Research Fund (FNR) under the COVID-19 Fast Track-2 programme (MODVid project – ref. 14854549). This paper was prepared to assist the Task Force for the Coordination of the Public Research Sector in the Context of the COVID-19 Pandemic (Work Package 7 on the socio-economic impact of the crisis, led by Aline Muller). Atte Aalto is supported by FNR (Project code: 13684479). Jorge Goncalves is partly supported by the 111 Project on Computational Intelligence and Intelligent Control (ref B18024). Françoise Kemp is supported by the FNR PRIDE17/12244779/PARK-QC. Stefano Magni and Daniele Proverbio are supported by the FNR PRIDE DTU CriTiCS (ref 10907093). The findings in this paper do not necessarily represent the views of the FNR and the Luxembourg COVID-19 Task Force. Any errors or omissions are the authors’ responsibility.

Keywords

Coronavirus
Growth
Lockdown
Productivity
Public health
COVID-19

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10.1016/j.ehb.2021.101051

Cite this

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title = "COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach",

abstract = "We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021.",

keywords = "Coronavirus, Growth, Lockdown, Productivity, Public health, COVID-19",

author = "Micha{\l} Burzy{\'n}ski and Jo{\"e}l Machado and Atte Aalto and Michel Beine and Jorge Goncalves and Tom Haas and Fran{\c c}oise Kemp and Stefano Magni and Laurent Mombaerts and Pierre Picard and Daniele Proverbio and Alexander Skupin and Fr{\'e}d{\'e}ric Docquier",

note = "We acknowledge financial support from the Luxembourg National Research Fund (FNR) under the COVID-19 Fast Track-2 programme (MODVid project – ref. 14854549). This paper was prepared to assist the Task Force for the Coordination of the Public Research Sector in the Context of the COVID-19 Pandemic (Work Package 7 on the socio-economic impact of the crisis, led by Aline Muller). Atte Aalto is supported by FNR (Project code: 13684479). Jorge Goncalves is partly supported by the 111 Project on Computational Intelligence and Intelligent Control (ref B18024). Fran{\c c}oise Kemp is supported by the FNR PRIDE17/12244779/PARK-QC. Stefano Magni and Daniele Proverbio are supported by the FNR PRIDE DTU CriTiCS (ref 10907093). The findings in this paper do not necessarily represent the views of the FNR and the Luxembourg COVID-19 Task Force. Any errors or omissions are the authors{\textquoteright} responsibility. ",

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doi = "10.1016/j.ehb.2021.101051",

language = "English",

volume = "43",

journal = "Economics and Human Biology",

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AU - Burzyński, Michał

AU - Machado, Joël

AU - Aalto, Atte

AU - Beine, Michel

AU - Goncalves, Jorge

AU - Haas, Tom

AU - Kemp, Françoise

AU - Magni, Stefano

AU - Mombaerts, Laurent

AU - Picard, Pierre

AU - Proverbio, Daniele

AU - Skupin, Alexander

AU - Docquier, Frédéric

N1 - We acknowledge financial support from the Luxembourg National Research Fund (FNR) under the COVID-19 Fast Track-2 programme (MODVid project – ref. 14854549). This paper was prepared to assist the Task Force for the Coordination of the Public Research Sector in the Context of the COVID-19 Pandemic (Work Package 7 on the socio-economic impact of the crisis, led by Aline Muller). Atte Aalto is supported by FNR (Project code: 13684479). Jorge Goncalves is partly supported by the 111 Project on Computational Intelligence and Intelligent Control (ref B18024). Françoise Kemp is supported by the FNR PRIDE17/12244779/PARK-QC. Stefano Magni and Daniele Proverbio are supported by the FNR PRIDE DTU CriTiCS (ref 10907093). The findings in this paper do not necessarily represent the views of the FNR and the Luxembourg COVID-19 Task Force. Any errors or omissions are the authors’ responsibility.

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AB - We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021.

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KW - Lockdown

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JO - Economics and Human Biology

JF - Economics and Human Biology

M1 - 101051

ER -

COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach

Abstract

Bibliographical note

Keywords

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MODVid: Modeling the macroeconomic and distributional effects of COVID-19 and restarting scenarios

Cite this

COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Projects

MODVid: Modeling the macroeconomic and distributional effects of COVID-19 and restarting scenarios

Cite this