Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36556
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dc.contributor.authorValckx, Sara-
dc.contributor.authorCREVECOEUR, Jonas-
dc.contributor.authorVerelst, Frederik-
dc.contributor.authorVRANCKX, Maren-
dc.contributor.authorHendrickx, Greet-
dc.contributor.authorHENS, Niel-
dc.contributor.authorVan Damme , Pierre-
dc.contributor.authorPepermans, Koen-
dc.contributor.authorBeutels, Philippe-
dc.contributor.authorNEYENS, Thomas-
dc.date.accessioned2022-01-20T16:00:27Z-
dc.date.available2022-01-20T16:00:27Z-
dc.date.issued2022-
dc.date.submitted2022-01-17T05:42:42Z-
dc.identifier.citationVaccine, 40 (1) , p. 151 -161-
dc.identifier.urihttp://hdl.handle.net/1942/36556-
dc.description.abstractBackground: A year after the start of the COVID-19 outbreak, the global rollout of vaccines gives us hope of ending the pandemic. Lack of vaccine confidence, however, poses a threat to vaccination campaigns. This study aims at identifying individuals' characteristics that explain vaccine willingness in Flanders (Belgium), while also describing trends over time (July-December 2020). Methods: The analysis included data of 10 survey waves of the Great Corona Survey, a large-scale online survey that was open to the general public and had 17,722-32,219 respondents per wave. Uni-and multivariable general additive models were fitted to associate vaccine willingness with socio-demographic and behavioral variables, while correcting for temporal and geographical variability. Results: We found 84.2% of the respondents willing to be vaccinated, i.e., respondents answering that they were definitely (61.2%) or probably (23.0%) willing to get a COVID-19 vaccine, while 9.8% indicated maybe, 3.9% probably not and 2.2% definitely not. In Flanders, vaccine willingness was highest in July 2020 (90.0%), decreased over the summer period to 80.2% and started to increase again from late September, reaching 85.9% at the end of December 2020. Vaccine willingness was significantly associated with respondents' characteristics: previous survey participation, age, gender, province, educational attainment, household size, financial situation, employment sector, underlying medical conditions, mental well-being, government trust, knowing someone with severe COVID-19 symptoms and compliance with restrictive measures. These variables could explain much, but not all, variation in vaccine willingness. Conclusions: Both the timing and location of data collection influence vaccine willingness results, emphasizing that comparing data from different regions, countries and/or timepoints should be done with caution. To maximize COVID-19 vaccination coverage, vaccination campaigns should focus on (a combination of) subpopulations: aged 31-50, females, low educational attainment, large households, difficult financial situation, low mental well-being and labourers, unemployed and self-employed citizens. (c) 2021 Elsevier Ltd. All rights reserved.-
dc.description.sponsorshipThe Great Corona Survey is supported by the Research Foundation Flanders (Grant G0G1920N, 2020) and the University of Antwerp Fund. Authors FV, NH and PB acknowledge funding from the European Union’s Horizon 2020 research and innovation programme (Project EpiPose - No. 101003688, 2020). All VAXINFECTIO authors acknowledge funding as part of the Methusalem-Centre of Excellence consortium VAX–IDEA. Support from the Methusalem finance programme of the Flemish Government is gratefully acknowledged. These funding sources had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The authors acknowledge the expert assistance of Linguapolis for linguistical support (for the Great Corona Survey) and Peter De Meyer for distributing news and media items to promote participation in the Great Corona Survey.-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.rights2021 Elsevier Ltd. All rights reserved.-
dc.subject.otherVaccine willingness-
dc.subject.otherVaccine hesitancy-
dc.subject.otherTrust-
dc.subject.otherCOVID-19-
dc.subject.otherSocio-demographics-
dc.subject.otherOnline survey-
dc.titleIndividual factors influencing COVID-19 vaccine acceptance in between and during pandemic waves (July–December 2020)-
dc.typeJournal Contribution-
dc.identifier.epage161-
dc.identifier.issue1-
dc.identifier.spage151-
dc.identifier.volume40-
local.format.pages11-
local.bibliographicCitation.jcatA1-
dc.description.notesValckx, S (corresponding author), Univ Antwerp, Univ Pl 1,DS2-51, BE-2610 Antwerp, Belgium.-
dc.description.notessara.valckx@uantwerpen.be; jonas.crevecoeur@kuleuven.be;-
dc.description.notesfrederik.Verelst@uantwerpen.be; maren.vranckx@uhasselt.be;-
dc.description.notesgreet.hendrickx@uantwerpen.be; niel.hens@uantwerpen.be;-
dc.description.notespierre.vandamme@uantwerpen.be; koen.pepermans@uantwerpen.be;-
dc.description.notesphilippe.beutels@uantwerpen.be; thomas.neyens@uhasselt.be-
local.publisher.placeTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.type.programmeH2020-
local.relation.h2020101003688-
dc.identifier.doi10.1016/j.vaccine.2021.10.073-
dc.identifier.pmid34863621-
dc.identifier.isiWOS:000731299800022-
dc.contributor.orcidNeyens, Thomas/0000-0003-2364-7555-
local.provider.typewosris-
local.description.affiliation[Valckx, Sara; Hendrickx, Greet; Van Damme, Pierre] Univ Antwerp, Fac Med & Hlth Sci, Ctr Evaluat Vaccinat, VAXINFECTIO, B-2000 Antwerp, Belgium.-
local.description.affiliation[Crevecoeur, Jonas; Neyens, Thomas] Katholieke Univ Leuven, Leuven Biostat & Stat Bioinformat Ctr L BioStat, Fac Med, Kapucijnenvoer 35,Bldg D,Box 7001, B-3000 Leuven, Belgium.-
local.description.affiliation[Verelst, Frederik; Hens, Niel; Beutels, Philippe] Univ Antwerp, Fac Med & Hlth Sci, Ctr Hlth Econ Res & Modelling Infect Dis, VAXINFECTIO, B-2000 Antwerp, Belgium.-
local.description.affiliation[Crevecoeur, Jonas; Vranckx, Maren; Hens, Niel; Neyens, Thomas] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Data Sci Inst, Martelarenlaan 42, B-3500 Hasselt, Belgium.-
local.description.affiliation[Pepermans, Koen] Univ Antwerp, Fac Social Sci, Sint Jacobstr 2, B-2000 Antwerp, Belgium.-
local.uhasselt.internationalno-
item.contributorValckx, Sara-
item.contributorCREVECOEUR, Jonas-
item.contributorVerelst, Frederik-
item.contributorVRANCKX, Maren-
item.contributorHendrickx, Greet-
item.contributorHENS, Niel-
item.contributorVan Damme , Pierre-
item.contributorPepermans, Koen-
item.contributorBeutels, Philippe-
item.contributorNEYENS, Thomas-
item.validationecoom 2023-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.fullcitationValckx, Sara; CREVECOEUR, Jonas; Verelst, Frederik; VRANCKX, Maren; Hendrickx, Greet; HENS, Niel; Van Damme , Pierre; Pepermans, Koen; Beutels, Philippe & NEYENS, Thomas (2022) Individual factors influencing COVID-19 vaccine acceptance in between and during pandemic waves (July–December 2020). In: Vaccine, 40 (1) , p. 151 -161.-
crisitem.journal.issn0264-410X-
crisitem.journal.eissn1873-2518-
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