Understanding the determinants of acceptance of COVID-19 vaccines: a challenge in a fast-moving situation
Notice bibliographique
Résumé
Michaël Schwarzinger and colleagues' study1Schwarzinger M Watson V Arwidson P Alla F Luchini S COVID-19 vaccine hesitancy in a representative working-age population in France: a survey experiment based on vaccine characteristics.Lancet Public Health. 2021; (published online Feb 5.)https://doi.org/10.1016/S2468-2667(21)00012-8Summary Full Text Full Text PDF PubMed Scopus (510) Google Scholar on the determinants of COVID-19 vaccine acceptance or refusal, published in The Lancet Public Health, provides an interesting novel perspective that differs from those of the many general population surveys thus far reported.2Lin C Tu P Beitsch LM Confidence and Receptivity for COVID-19 Vaccines: A Rapid Systematic Review.Vaccines (Basel). 2020; 9: e16Crossref PubMed Scopus (548) Google Scholar The authors' experiment, conducted in July, 2020, assessed the effects of various scenarios on participants' intentions to be vaccinated against COVID-19. These scenarios were constructed by varying the characteristics of hypothetical COVID-19 vaccines (efficacy, risk of severe side-effects, and country of manufacturer) and vaccination strategies (herd immunity target and place of vaccine administration). This design enabled them to distinguish between systematic outright rejection of future COVID-19 vaccines (regardless of their characteristics) and vaccine hesitancy, which was sensitive to these characteristics. Their results might therefore be important in terms of vaccination strategy. One of the most notable results of this study is that, assuming a campaign of vaccination administered at mass vaccination centres and with communication about the benefits of herd immunity, the investigators' behavioural model predicted that 29·4% (95% CI 28·6–30·2) of the French working-age population were likely to refuse COVID-19 vaccination outright, while vaccine hesitancy ranged from 9·3% to 43·2% depending on vaccine characteristics. Schwarzinger and colleagues show that the margin of variation of vaccine hesitancy depends on the potential vaccine characteristics and point out that obtaining sufficient COVID-19 vaccine coverage in working-age adults will be key if the goal is herd immunity—a question still under debate.3Science Media CentreExpert reaction to a preprint on vaccines and heard immunity.https://www.sciencemediacentre.org/expert-reaction-to-a-preprint-on-vaccines-and-herd-immunityDate: Jan 21, 2021Date accessed: January 30, 2021Google Scholar Comparison of the results of their study with the efficacy and safety of the marketed mRNA vaccines4Polack FP Thomas SJ Kitchin N et al.Safety and efficacy of the BNT162b2 mRNA COVID-19 vaccine.N Engl J Med. 2020; 383: 2603-2615Crossref PubMed Scopus (9742) Google Scholar suggests the features of these vaccines will favourably affect vaccine hesitancy. Nonetheless, the authors showed that this effect might partly be offset by access constraints. The results regarding the location of a vaccine's manufacturer (the EU, the USA, or China) are also topical given the current shortage of vaccine doses, but also more difficult to use to anticipate population behaviour in view of the rapidly changing situation. For example, the agreement signed with Sanofi in late January, 2021, to make its factories in Europe available for bottling the Pfizer vaccine could reassure some individuals who are hesitant about vaccination. Another important result about vaccination strategy is that the study shows a high a priori acceptance of COVID-19 vaccines among the youngest individuals (aged 18–24 years), even though they are likely to be the least affected by the health consequences of COVID-19. Evidence from the international literature regarding this finding is conflicting.2Lin C Tu P Beitsch LM Confidence and Receptivity for COVID-19 Vaccines: A Rapid Systematic Review.Vaccines (Basel). 2020; 9: e16Crossref PubMed Scopus (548) Google Scholar This high acceptability in young people, although perhaps counterintuitive from the perspective of a somatic benefit–risk analysis, is understandable from the vantage point of social factors and mental health—consequences that are likely to be most pronounced in this age group, whose lives have been drastically disrupted by the pandemic.5Peretti-Watel P Alleaume C Léger D Beck F Verger P Anxiety, depression and sleep problems: a second wave of COVID-19.Gen Psychiatr. 2020; 33e100299Crossref PubMed Scopus (47) Google Scholar, 6Beck F Léger D Fressard L Peretti-Watel P Verger P COVID-19 health crisis and lockdown associated with high level of sleep complaints and hypnotic uptake at the population level.J Sleep Res. 2021; 30e13119Crossref PubMed Scopus (135) Google Scholar Vaccination could be an unexpected source of hope for them, evoking the possibility of a return to normal life. Because vaccination of young people might be an effective path to herd immunity, it is essential to understand this group's attitudes towards vaccination against COVID-19. Importantly, the study provides evidence to suggest that messages highlighting the benefits in terms of herd immunity might reduce hesitation about COVID-19 vaccines. This is an important finding that could guide communication to promote the vaccination campaign (provided that vaccination is shown to reduce transmission). This type of communication strategy should, nonetheless, be tested in the field first because adhering to collective objectives in theoretical exercises might not translate into real-life behaviour. Moreover, this line of communication should be done concurrently with other strategies, particularly those—which appear promising—aimed at tackling and debunking the false information that thrives in these times of crisis.7Freeman D Waite F Rosebrock L et al.Coronavirus conspiracy beliefs, mistrust, and compliance with government guidelines in England.Psychol Med. 2020; 21: 1-13Google Scholar, 8Lewandowsky S Cook J Schmid P et al.The COVID-19 vaccine communication handbook: a practical guide for improving vaccine communication and fighting misinformation.https://rri-tools.eu/-/the-covid-19-vaccine-communication-handbook-a-practical-guide-for-improving-vaccine-communication-and-fighting-misinformationDate: Jan 7, 2021Date accessed: January 30, 2021Google Scholar Finally, this study shows that most people are probably not absolutely for or against COVID-19 vaccines. Depending on their own profile and preferences, and on the characteristics of the vaccines available, vaccine-hesitant individuals might consider taking the vaccine or delay it to get another vaccine. Health authorities must anticipate these behaviours, especially since the characteristics that influence them could change over time (eg, from efficacy, technology used, and availability date early on in campaigns, to effectiveness against variants and post-vaccination transmission as more evidence emerges). To understand what will influence behaviours in the months to come, quasi-experimental designs are likely to remain useful, but additional tools are required. Longitudinal approaches based on cohort follow-up would be more powerful than cross-sectional surveys to analyse the drivers of people's decisions to accept or reject COVID-19 vaccines. It is also essential to include health professionals among those whose opinions and attitudes are monitored, given their influence on patients' decisions, because they are also subject to uncertainty about COVID-19 vaccines.9Verger P Scronias D Dauby N et al.Attitudes of healthcare workers towards COVID-19 vaccination: a survey in France and French-speaking parts of Belgium and Canada, 2020.Euro Surveill. 2021; 262002047Crossref PubMed Scopus (264) Google Scholar We declare no competing interests. COVID-19 vaccine hesitancy in a representative working-age population in France: a survey experiment based on vaccine characteristicsCOVID-19 vaccine acceptance depends on the characteristics of new vaccines and the national vaccination strategy, among various other factors, in the working-age population in France. Full-Text PDF Open Access
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».