Quantifying population preferences around vaccination against severe but rare diseases: A conjoint analysis among French university students, 2016 |
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| Affiliation: | 1. EHESP French School of Public Health, Sorbonne Paris Cité, Paris, France;2. Aix-Marseille Université, CNRS, EHESS, Centrale Marseille, AMSE, France;3. Institute for Public Health, Charité-Universitätsmedizin Berlin, Germany;4. Service inter-universitaire de médecine préventive et de promotion de la santé, Rennes, France;5. UMR 190 EPV “Emergence des Pathologies Virales” (Aix-Marseille University, IRD 190, INSERM 1207, EHESP), Marseille, France;6. UMR “Processus Infectieux en Milieu Insulaire Tropical” (INSERM 1187, CNRS 9192, IRD 249, Université de La Réunion), Réunion, France;7. Institut Pasteur, Paris, France;1. Department of Infectious Diseases, St. Jude Children''s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA;2. Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, USA;1. Department of Public Health and Epidemiology, Faculty of Pharmaceutical Sciences, Meiji Pharmaceutical University, 2-522-1 Noshio, Kiyose, Tokyo 204-8588, Japan;2. Department of Health Care Policy and Health Economics, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 3058577, Japan;1. Department of Economics, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand;2. Factor-Inwentash Faculty of Social Work, University of Toronto, 246 Bloor St W, Toronto, Ontario, Canada M5S 1V4;3. Faculty of Science and Technology, Rajamangala University of Technology Phra Nakhon, 138 Phibulsongkram, Bang Sue, Bangkok 10800, Thailand;4. Centre for the Study of Choice, University of Technology Sydney, New South Wales, Australia;1. Robinson Research Institute, and School of Paediatrics and Reproductive Health, University of Adelaide, South Australia 5006, Australia;2. Flinders Health Economics Group, Flinders University, South Australia 5041, Australia;3. Vaccinology and Immunology Research Trials Unit, Women''s and Children''s Health Network, Adelaide, South Australia 5006, Australia;1. Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi''an Jiaotong University, China;2. Center for Drug Safety and Policy Research, Xi''an Jiaotong University, China;3. Shaanxi Center for Health Reform and Development Research, Xi''an Jiaotong University, China;4. Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China’s Western Technological Innovation Harbor, Xi’an, China |
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| Abstract: | BackgroundSeveral concepts are available to explain vaccine decision making by individual and inter-individual factors, including risk perception, social conformism and altruism. However, only a few studies have quantified the weight of these determinants in vaccine acceptance. Using a conjoint analysis tool, we aimed at eliciting preferences in a student population regarding vaccination against a rare, severe and rapidly evolving hypothetical disease, similar to meningococcal serogroup C meningitis or measles.MethodsDuring March-May 2016, we conducted an emailing survey among university students aged 18–24 years (N = 775) in Rennes, France. Participants were asked to decide for or against immediate vaccination in 24 hypothetical scenarios, containing various levels of four attributes: epidemic situation, adverse events, information on vaccination coverage, and potential for indirect protection. Data were analysed using random effect estimator logit models.ResultsParticipants accepted on average 52% of scenarios and all attributes significantly impacted vaccination acceptance. The highest positive effects were seen with an epidemic situation (OR 3.81, 95%-CI 3.46–4.19), 90% coverage in the community (3.64, 3.15–4.20) and potential for disease elimination from the community (2.87, 2.53–3.26). Information on “insufficient coverage” was dissuasive (vs. none of friends vaccinated: 0.65, 0.56–0.75). Controversy had a significantly greater negative effect than a confirmed risk of severe adverse events (OR 0.05 vs. 0.22). In models including participant characteristics, preference weights were unchanged, while trust in health authorities and vaccination perceptions strongly influenced acceptance themselves. The greatest significant variation of preference weights between subgroups was observed with controversy among students using alternative medicine daily (OR 0.28) and among students relying on scientific vaccine information (OR 0.02).ConclusionsAmong young adults, potential for indirect protection and factual information on coverage in the community and potential side effects positively impact theoretical vaccine acceptance. Conjoint analyses should be conducted to understand vaccine hesitancy in specific vaccination programs. |
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| Keywords: | Conjoint analysis Discrete choice experiment Vaccine acceptance Vaccine hesitancy Meningococcal vaccine Measles vaccine |
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