Abstract
Objective: Here we investigate public preferences for coronavirus disease 2019 (COVID-19) certificates in the Netherlands, and whether these preferences differ between subgroups in the population. Methods: A survey including a discrete choice experiment was administered to 1500 members of the adult population of the Netherlands. Each participant was asked to choose between hypothetical COVID-19 certificates that differed in seven attributes: the starting date, and whether the certificate allowed gathering with multiple people, shopping without appointment, visiting bars and restaurants, visiting cinemas and theatres, attending events, and practising indoor sports. Latent class models (LCMs) were used to determine the attribute relative importance and predicted acceptance rate of hypothetical certificates. Results: Three classes of preference patterns were identified in the LCM. One class a priori opposed a certificate (only two attributes influencing preferences), another class was relatively neutral and included all attributes in their decision making, and the final class was positive towards a certificate. Respondents aged > 65 years and those who plan to get vaccinated were more likely to belong to the latter two classes. Being allowed to shop without appointment and to visit bars and restaurants was most important to all respondents, increasing predicted acceptance rate by 12 percentage points. Conclusions: Preferences for introduction of a COVID-19 certificate are mixed. A certificate that allows for shopping without appointment and visiting bars and restaurants is likely to increase acceptance. The support of younger citizens and those who plan to get vaccinated seems most sensitive to the specific freedoms granted by a COVID-19 certificate.
Original language | English |
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Pages (from-to) | 603-614 |
Number of pages | 12 |
Journal | Applied Health Economics and Health Policy |
Volume | 21 |
Issue number | 4 |
Early online date | 8 May 2023 |
DOIs | |
Publication status | Published - Jul 2023 |
Bibliographical note
Funding:The data collection was sponsored by the TU Delft COVID-19 Response fund.
Publisher Copyright: © 2023, The Author(s).