COVID-19 Vaccine Preferences in General Populations in Canada, Germany, the United Kingdom, and the United States: Discrete Choice Experiment.


Journal

JMIR public health and surveillance
ISSN: 2369-2960
Titre abrégé: JMIR Public Health Surveill
Pays: Canada
ID NLM: 101669345

Informations de publication

Date de publication:
16 Oct 2024
Historique:
received: 09 02 2024
accepted: 03 08 2024
revised: 25 07 2024
medline: 16 10 2024
pubmed: 16 10 2024
entrez: 16 10 2024
Statut: epublish

Résumé

Despite strong evidence supporting COVID-19 vaccine efficacy and safety, a proportion of the population remains hesitant to receive immunization. Discrete choice experiments (DCEs) can help assess preferences and decision-making drivers. We aim to (1) elicit preferences for COVID-19 vaccines in Canada, Germany, the United Kingdom, and the United States; (2) understand which vaccine attributes people there value; and (3) gain insight into the choices that different population subgroups make regarding COVID-19 vaccines. Participants in the 2019nCoV-408 study were aged ≥18 years; self-reported antivaccinationists were excluded. A DCE with a series of 2 hypothetical vaccine options was embedded into a survey to determine participant treatment preferences (primary objective). Survey questions covered vaccine preference, previous COVID-19 experiences, and demographics, which were summarized using descriptive statistics to understand the study participants' backgrounds. In the DCE, participants were provided choice pairs: 1 set with and 1 without an "opt-out" option. Each participant viewed 11 unique vaccine profiles. Vaccine attributes consisted of type (messenger RNA or protein), level of protection against any or severe COVID-19, risk of side effects (common and serious), and potential coadministration of COVID-19 and influenza vaccines. Attribute level selections were included for protection and safety (degree of effectiveness and side effect risk, respectively). Participants were stratified by vaccination status (unvaccinated, or partially or fully vaccinated) and disease risk group (high-risk or non-high-risk). A conditional logit model was used to analyze DCE data to estimate preferences of vaccine attributes, with the percentage relative importance calculated to allow for its ranking. Each model was run twice to account for sets with and without the opt-out options. The mean age of participants (N=2000) was 48 (SD 18.8) years, and 51.25% (1025/2000) were male. The DCE revealed that the most important COVID-19 vaccine attributes were protection against severe COVID-19 or any severity of COVID-19 and common side effects. Protection against severe COVID-19 was the most important attribute for fully vaccinated participants, which significantly differed from the unvaccinated or partially vaccinated subgroup (relative importance 34.8% vs 30.6%; P=.049). Avoiding serious vaccine side effects was a significantly higher priority for the unvaccinated or partially versus fully vaccinated subgroup (relative importance 10.7% vs 8.2%; P=.044). Attributes with significant differences in the relative importance between the high-risk versus non-high-risk subgroups were protection against severe COVID-19 (38.2% vs 31.5%; P<.000), avoiding common vaccine side effects (12% vs 20.5%; P<.000), and avoiding serious vaccine side effects (9.7% vs 7.5%; P=.002). This DCE identified COVID-19 vaccine attributes, such as protection against severe COVID-19, that may influence preference and drive choice and can inform vaccine strategies. The high ranking of common and serious vaccine side effects suggests that, when the efficacy of 2 vaccines is comparable, safety is a key decision-making factor.

Sections du résumé

BACKGROUND BACKGROUND
Despite strong evidence supporting COVID-19 vaccine efficacy and safety, a proportion of the population remains hesitant to receive immunization. Discrete choice experiments (DCEs) can help assess preferences and decision-making drivers.
OBJECTIVE OBJECTIVE
We aim to (1) elicit preferences for COVID-19 vaccines in Canada, Germany, the United Kingdom, and the United States; (2) understand which vaccine attributes people there value; and (3) gain insight into the choices that different population subgroups make regarding COVID-19 vaccines.
METHODS METHODS
Participants in the 2019nCoV-408 study were aged ≥18 years; self-reported antivaccinationists were excluded. A DCE with a series of 2 hypothetical vaccine options was embedded into a survey to determine participant treatment preferences (primary objective). Survey questions covered vaccine preference, previous COVID-19 experiences, and demographics, which were summarized using descriptive statistics to understand the study participants' backgrounds. In the DCE, participants were provided choice pairs: 1 set with and 1 without an "opt-out" option. Each participant viewed 11 unique vaccine profiles. Vaccine attributes consisted of type (messenger RNA or protein), level of protection against any or severe COVID-19, risk of side effects (common and serious), and potential coadministration of COVID-19 and influenza vaccines. Attribute level selections were included for protection and safety (degree of effectiveness and side effect risk, respectively). Participants were stratified by vaccination status (unvaccinated, or partially or fully vaccinated) and disease risk group (high-risk or non-high-risk). A conditional logit model was used to analyze DCE data to estimate preferences of vaccine attributes, with the percentage relative importance calculated to allow for its ranking. Each model was run twice to account for sets with and without the opt-out options.
RESULTS RESULTS
The mean age of participants (N=2000) was 48 (SD 18.8) years, and 51.25% (1025/2000) were male. The DCE revealed that the most important COVID-19 vaccine attributes were protection against severe COVID-19 or any severity of COVID-19 and common side effects. Protection against severe COVID-19 was the most important attribute for fully vaccinated participants, which significantly differed from the unvaccinated or partially vaccinated subgroup (relative importance 34.8% vs 30.6%; P=.049). Avoiding serious vaccine side effects was a significantly higher priority for the unvaccinated or partially versus fully vaccinated subgroup (relative importance 10.7% vs 8.2%; P=.044). Attributes with significant differences in the relative importance between the high-risk versus non-high-risk subgroups were protection against severe COVID-19 (38.2% vs 31.5%; P<.000), avoiding common vaccine side effects (12% vs 20.5%; P<.000), and avoiding serious vaccine side effects (9.7% vs 7.5%; P=.002).
CONCLUSIONS CONCLUSIONS
This DCE identified COVID-19 vaccine attributes, such as protection against severe COVID-19, that may influence preference and drive choice and can inform vaccine strategies. The high ranking of common and serious vaccine side effects suggests that, when the efficacy of 2 vaccines is comparable, safety is a key decision-making factor.

Identifiants

pubmed: 39412841
pii: v10i1e57242
doi: 10.2196/57242
doi:

Substances chimiques

COVID-19 Vaccines 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e57242

Informations de copyright

©David Salisbury, Jeffrey V Lazarus, Nancy Waite, Clara Lehmann, Sumitra Sri Bhashyam, Marie de la Cruz, Beth Hahn, Matthew D Rousculp, Paolo Bonanni. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 16.10.2024.

Auteurs

David Salisbury (D)

Programme for Global Health, Royal Institute of International Affairs, Chatham House, London, United Kingdom.

Jeffrey V Lazarus (JV)

Graduate School of Public Health and Health Policy (CUNY SPH), City University of New York, New York, NY, United States.
Barcelona Institute for Global Health (ISGlobal), Hospital Clinic, University of Barcelona, Barcelona, Spain.

Nancy Waite (N)

School of Pharmacy, University of Waterloo, Ontario, ON, Canada.

Clara Lehmann (C)

Department of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Cologne, Germany.

Sumitra Sri Bhashyam (S)

ICON Insights, Evidence and Value-Patient Centered Outcomes, Reading, United Kingdom.

Marie de la Cruz (M)

ICON Insights, Evidence and Value-Patient Centered Outcomes, Raleigh, NC, United States.

Beth Hahn (B)

Novavax, Inc, Gaithersburg, MD, United States.

Matthew D Rousculp (MD)

Novavax, Inc, Gaithersburg, MD, United States.

Paolo Bonanni (P)

Department of Health Services, University of Florence, Florence, Italy.

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