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Risk of disease and willingness to vaccinate in the United States: A population-based survey
BACKGROUND: Vaccination complacency occurs when perceived risks of vaccine-preventable diseases are sufficiently low so that vaccination is no longer perceived as a necessary precaution. Disease outbreaks can once again increase perceptions of risk, thereby decrease vaccine complacency, and in turn...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561115/ https://www.ncbi.nlm.nih.gov/pubmed/33057373 http://dx.doi.org/10.1371/journal.pmed.1003354 |
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author | Baumgaertner, Bert Ridenhour, Benjamin J. Justwan, Florian Carlisle, Juliet E. Miller, Craig R. |
author_facet | Baumgaertner, Bert Ridenhour, Benjamin J. Justwan, Florian Carlisle, Juliet E. Miller, Craig R. |
author_sort | Baumgaertner, Bert |
collection | PubMed |
description | BACKGROUND: Vaccination complacency occurs when perceived risks of vaccine-preventable diseases are sufficiently low so that vaccination is no longer perceived as a necessary precaution. Disease outbreaks can once again increase perceptions of risk, thereby decrease vaccine complacency, and in turn decrease vaccine hesitancy. It is not well understood, however, how change in perceived risk translates into change in vaccine hesitancy. We advance the concept of vaccine propensity, which relates a change in willingness to vaccinate with a change in perceived risk of infection—holding fixed other considerations such as vaccine confidence and convenience. METHODS AND FINDINGS: We used an original survey instrument that presents 7 vaccine-preventable “new” diseases to gather demographically diverse sample data from the United States in 2018 (N = 2,411). Our survey was conducted online between January 25, 2018, and February 2, 2018, and was structured in 3 parts. First, we collected information concerning the places participants live and visit in a typical week. Second, participants were presented with one of 7 hypothetical disease outbreaks and asked how they would respond. Third, we collected sociodemographic information. The survey was designed to match population parameters in the US on 5 major dimensions: age, sex, income, race, and census region. We also were able to closely match education. The aggregate demographic details for study participants were a mean age of 43.80 years, 47% male and 53% female, 38.5% with a college degree, and 24% nonwhite. We found an overall change of at least 30% in proportion willing to vaccinate as risk of infection increases. When considering morbidity information, the proportion willing to vaccinate went from 0.476 (0.449–0.503) at 0 local cases of disease to 0.871 (0.852–0.888) at 100 local cases (upper and lower 95% confidence intervals). When considering mortality information, the proportion went from 0.526 (0.494–0.557) at 0 local cases of disease to 0.916 (0.897–0.931) at 100 local cases. In addition, we ffound that the risk of mortality invokes a larger proportion willing to vaccinate than mere morbidity (P = 0.0002), that older populations are more willing than younger (P<0.0001), that the highest income bracket (>$90,000) is more willing than all others (P = 0.0001), that men are more willing than women (P = 0.0011), and that the proportion willing to vaccinate is related to both ideology and the level of risk (P = 0.004). Limitations of this study include that it does not consider how other factors (such as social influence) interact with local case counts in people’s vaccine decision-making, it cannot determine whether different degrees of severity in morbidity or mortality failed to be statistically significant because of survey design or because participants use heuristically driven decision-making that glosses over degrees, and the study does not capture the part of the US that is not online. CONCLUSIONS: In this study, we found that different degrees of risk (in terms of local cases of disease) correspond with different proportions of populations willing to vaccinate. We also identified several sociodemographic aspects of vaccine propensity. Understanding how vaccine propensity is affected by sociodemographic factors is invaluable for predicting where outbreaks are more likely to occur and their expected size, even with the resulting cascade of changing vaccination rates and the respective feedback on potential outbreaks. |
format | Online Article Text |
id | pubmed-7561115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75611152020-10-21 Risk of disease and willingness to vaccinate in the United States: A population-based survey Baumgaertner, Bert Ridenhour, Benjamin J. Justwan, Florian Carlisle, Juliet E. Miller, Craig R. PLoS Med Research Article BACKGROUND: Vaccination complacency occurs when perceived risks of vaccine-preventable diseases are sufficiently low so that vaccination is no longer perceived as a necessary precaution. Disease outbreaks can once again increase perceptions of risk, thereby decrease vaccine complacency, and in turn decrease vaccine hesitancy. It is not well understood, however, how change in perceived risk translates into change in vaccine hesitancy. We advance the concept of vaccine propensity, which relates a change in willingness to vaccinate with a change in perceived risk of infection—holding fixed other considerations such as vaccine confidence and convenience. METHODS AND FINDINGS: We used an original survey instrument that presents 7 vaccine-preventable “new” diseases to gather demographically diverse sample data from the United States in 2018 (N = 2,411). Our survey was conducted online between January 25, 2018, and February 2, 2018, and was structured in 3 parts. First, we collected information concerning the places participants live and visit in a typical week. Second, participants were presented with one of 7 hypothetical disease outbreaks and asked how they would respond. Third, we collected sociodemographic information. The survey was designed to match population parameters in the US on 5 major dimensions: age, sex, income, race, and census region. We also were able to closely match education. The aggregate demographic details for study participants were a mean age of 43.80 years, 47% male and 53% female, 38.5% with a college degree, and 24% nonwhite. We found an overall change of at least 30% in proportion willing to vaccinate as risk of infection increases. When considering morbidity information, the proportion willing to vaccinate went from 0.476 (0.449–0.503) at 0 local cases of disease to 0.871 (0.852–0.888) at 100 local cases (upper and lower 95% confidence intervals). When considering mortality information, the proportion went from 0.526 (0.494–0.557) at 0 local cases of disease to 0.916 (0.897–0.931) at 100 local cases. In addition, we ffound that the risk of mortality invokes a larger proportion willing to vaccinate than mere morbidity (P = 0.0002), that older populations are more willing than younger (P<0.0001), that the highest income bracket (>$90,000) is more willing than all others (P = 0.0001), that men are more willing than women (P = 0.0011), and that the proportion willing to vaccinate is related to both ideology and the level of risk (P = 0.004). Limitations of this study include that it does not consider how other factors (such as social influence) interact with local case counts in people’s vaccine decision-making, it cannot determine whether different degrees of severity in morbidity or mortality failed to be statistically significant because of survey design or because participants use heuristically driven decision-making that glosses over degrees, and the study does not capture the part of the US that is not online. CONCLUSIONS: In this study, we found that different degrees of risk (in terms of local cases of disease) correspond with different proportions of populations willing to vaccinate. We also identified several sociodemographic aspects of vaccine propensity. Understanding how vaccine propensity is affected by sociodemographic factors is invaluable for predicting where outbreaks are more likely to occur and their expected size, even with the resulting cascade of changing vaccination rates and the respective feedback on potential outbreaks. Public Library of Science 2020-10-15 /pmc/articles/PMC7561115/ /pubmed/33057373 http://dx.doi.org/10.1371/journal.pmed.1003354 Text en © 2020 Baumgaertner et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Baumgaertner, Bert Ridenhour, Benjamin J. Justwan, Florian Carlisle, Juliet E. Miller, Craig R. Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title | Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title_full | Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title_fullStr | Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title_full_unstemmed | Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title_short | Risk of disease and willingness to vaccinate in the United States: A population-based survey |
title_sort | risk of disease and willingness to vaccinate in the united states: a population-based survey |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561115/ https://www.ncbi.nlm.nih.gov/pubmed/33057373 http://dx.doi.org/10.1371/journal.pmed.1003354 |
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