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Health Crisis Measures and Standards for Fair Decision-Making: A Normative and Empirical-Based Account of the Interplay Between Science, Politics and Courts

Published online by Cambridge University Press:  15 June 2021

Full Professor, Law and Government, University of Antwerp, Belgium; email:
Postdoctoral researcher at the Department of Political Science, University of Antwerp, Belgium.
Full Professor, Faculty of Economic Science, University of Antwerp, Belgium.
Postdoctoral researcher, GOVTRUST Centre of Excellence, Research Group Politics and Public Governance (Faculty of Social Sciences) and Research Group Government and Law (Faculty of Law), University of Antwerp, Belgium.
Professor, Politics and Public Governance, University of Antwerp, Belgium.


This paper examines, in the light of the COVID-19 crisis, the room for judicial oversight of health crisis measures based on the public’s expectations of how governments should act in the interplay with experts. The paper explains how trust theory and procedural rationality review help to address concerns related to legitimacy and expertise. The paper argues that courts should distinguish between two stages. In the initial stage, fear as a driver for government support based on expertise justifies that the proportionality test is limited to the question of whether measures were based on virologist expert advice. In the next stage, people expect the government to take expert-informed decisions, but also require that the government takes into account societal needs. Procedural rationality review in this stage demands that courts examine whether the decision was based on an informed balance of rights and interests.

© The Author(s), 2021. Published by Cambridge University Press

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This paper is an output of the GOVTRUST Centre of Excellence and a project funded by the University of Antwerp Research Council (BOF COVID-19 project).


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56 Response categories for news interest varied from daily to less than once per week. Because the responses were strongly right-skewed towards the daily category, the choice was made to recode the variable into daily versus less than daily.

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58 While ordinary least squares estimation with robust standard errors yielded the same results, it does not take into account the ordinal nature of the dependent variable. We therefore present ordered logistic results here, with ordinary least squares results being available upon request.

59 Using exploratory factor analyses with oblique promax(3) rotation (as factors are likely to be correlated). Factor loadings were used to generate regression-based indices.

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