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A choice experiment assessment of stated early response to COVID-19 vaccines in the USA

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  • Ricardo A. Daziano

    (School of Civil and Environmental Engineering, Cornell University)

Abstract

Background Using choice microdata (N=2723) across the USA, this paper analyzes elicited acceptance of hypothetical COVID-19 vaccines. Methods The hypothetical vaccines in a choice experiment were described in terms of effectiveness, days for antibodies to develop, duration of protection, risk of both mild and severe side effects, which health agency mainly supports the vaccine, country of origin, and when the vaccine was developed. Out-of-pocket cost was also considered as characteristic of the vaccines to derive welfare measures. Results All vaccine attributes had expected signs with significant estimates. Vaccines developed in the USA and the UK were preferred to a hypothetical German vaccine, whereas a Chinese origin was very negatively perceived. Since the choice scenarios also gave the option to opt out from taking the vaccine, odds ratios were derived to characterize the segments that are more and less likely to accept vaccination. More likely to opt out were found to be those who stated to be against vaccination in general, African Americans, individuals without health insurance, and older people. Males, democrats, those who took the flu vaccine appear as more willing to accept vaccination. Conclusions Estimates of the fitted choice models in this study are informative for current and future immunization programs.

Suggested Citation

  • Ricardo A. Daziano, 2022. "A choice experiment assessment of stated early response to COVID-19 vaccines in the USA," Health Economics Review, Springer, vol. 12(1), pages 1-16, December.
    • Handle: RePEc:spr:hecrev:v:12:y:2022:i:1:d:10.1186_s13561-022-00368-w
    DOI: 10.1186/s13561-022-00368-w
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    1. David A Hensher & William H Greene & John M Rose, 2006. "Deriving Willingness-to-Pay Estimates of Travel-Time Savings from Individual-Based Parameters," Environment and Planning A, , vol. 38(12), pages 2365-2376, December.
    2. Vikas Soekhai & Esther W. Bekker-Grob & Alan R. Ellis & Caroline M. Vass, 2019. "Discrete Choice Experiments in Health Economics: Past, Present and Future," PharmacoEconomics, Springer, vol. 37(2), pages 201-226, February.
    3. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    4. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    5. David Revelt and Kenneth Train., 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Economics Working Papers E00-274, University of California at Berkeley.
    6. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    7. Riccardo Scarpa & Mara Thiene, 2005. "Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences," Land Economics, University of Wisconsin Press, vol. 81(3).
    8. Chandra R. Bhat, 1997. "An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel," Transportation Science, INFORMS, vol. 31(1), pages 34-48, February.
    9. Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.
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    1. Daziano, Ricardo & Budziński, Wiktor, 2023. "Evolution of preferences for COVID-19 vaccine throughout the pandemic – The choice experiment approach," Social Science & Medicine, Elsevier, vol. 332(C).
    2. Krueger, Rico & Daziano, Ricardo A., 2022. "Stated choice analysis of preferences for COVID-19 vaccines using the Choquet integral," Journal of choice modelling, Elsevier, vol. 45(C).

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