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Vaccine. 2019 Apr 3;37(15):2079-2089. doi: 10.1016/j.vaccine.2019.02.056. Epub 2019 Mar 8.

Drivers of vaccine decision-making in South Africa: A discrete choice experiment.

Author information

1
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Antwerp), Belgium. Electronic address: frederik.verelst@uantwerp.be.
2
Department of Economics & Flemish Research Foundation (FWO), University of Antwerp, Prinsstraat 13, 2000 Antwerp, Belgium; School of Economics, University of Amsterdam, PO Box 15867, 1001 NJ Amsterdam, the Netherlands.
3
International Centre for Reproductive Health, Ghent University, C. Heymanslaan 10, 9000 Ghent, Belgium; The South African Department of Science and Technology-National Research Foundation (DST-NRF) Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Matieland, Stellenbosch 7602, South Africa; Center for Statistics, Hasselt University, Martelarenlaan 42, 3500 Hasselt, Belgium; Rega Institute for Medical Research, KU Leuven, Herestraat 49, 3000 Leuven, Belgium; Department of Global Health Faculty of Medicine and Health Sciences, Stellenbosch University, Matieland, Stellenbosch 7602, South Africa.
4
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Antwerp), Belgium; School of Public Health and Community Medicine, The University of New South Wales, UNSW Medicine, NSW 2052, Australia.
5
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Antwerp), Belgium.

Abstract

To increase vaccination coverage, it is essential to understand the vaccine decision-making process. High population coverage is required to obtain herd immunity and to protect vulnerable groups in terms of age (e.g. the very young) or health (e.g. immunodeficiency). Vaccine confidence and coverage in South Africa are relatively low, opening the window for sustained outbreaks of vaccine-preventable diseases in a country facing one of the most severe HIV epidemics in the world. To capture the vaccine-related decision-making process in South Africa, we performed a discrete choice experiment with 1200 participants in December 2017. We asked for their preferences with respect to (1) vaccine effectiveness, (2) vaccine-preventable burden of disease, (3) accessibility of the vaccine in terms of co-payment and prescription requirements, (4) frequency of mild vaccine-related side-effects, (5) population vaccination coverage and (6) local vaccination coverage. We distinguished between decision-making for vaccines administered to the participant, and for vaccines administered to their youngest child. We analyzed the data for each of these groups using a panel mixed logit model and found similar results for decisions to vaccinate oneself or one's child. Vaccine effectiveness was the most important attribute followed by population coverage and burden of disease. Local coverage and accessibility were also important determinants of vaccination behavior, but to a lesser extent. Regarding population and local coverage, we observed a positive effect on vaccine utility indicating the potential of peer influence. As such, social normative influence could be exploited to increase vaccination confidence and coverage. With respect to vaccine-preventable burden of the disease, the marginal utilities showed disease severity to be more important than frequency of disease. Policymakers and health care workers should stress the effectiveness of vaccines together with the severity of vaccine-preventable diseases.

KEYWORDS:

Behavior; Decision-making criteria; Discrete choice experiment; Free-riding; South Africa; Vaccination

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