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Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Author

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  • Abolfazl Mollalo

    (Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH 44017, USA)

  • Moosa Tatar

    (Matheson Center for Health Care Studies, University of Utah, Salt Lake City, UT 84108, USA)

Abstract

Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.

Suggested Citation

  • Abolfazl Mollalo & Moosa Tatar, 2021. "Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States," IJERPH, MDPI, vol. 18(18), pages 1-14, September.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9488-:d:631717
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    References listed on IDEAS

    as
    1. Jacobs, D.E., 2011. "Environmental health disparities in housing," American Journal of Public Health, American Public Health Association, vol. 101(SUPPL. 1), pages 115-122.
    2. Oshan, Taylor M. & Smith, Jordan & Fotheringham, Alexander Stewart, 2020. "Targeting the spatial context of obesity determinants via multiscale geographically weighted regression," OSF Preprints u7j29, Center for Open Science.
    3. Juhn, Young J. & Sauver, Jennifer St. & Katusic, Slavica & Vargas, Delfino & Weaver, Amy & Yunginger, John, 2005. "The influence of neighborhood environment on the incidence of childhood asthma: a multilevel approach," Social Science & Medicine, Elsevier, vol. 60(11), pages 2453-2464, June.
    4. Luc Anselin & Daniel Arribas-Bel, 2013. "Spatial fixed effects and spatial dependence in a single cross-section," Papers in Regional Science, Wiley Blackwell, vol. 92(1), pages 3-17, March.
    5. Jinting Zhang & Xiu Wu & T. Edwin Chow, 2021. "Space-Time Cluster’s Detection and Geographical Weighted Regression Analysis of COVID-19 Mortality on Texas Counties," IJERPH, MDPI, vol. 18(11), pages 1-21, May.
    6. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    7. Abolfazl Mollalo & Kiara M. Rivera & Behzad Vahedi, 2020. "Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
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    Cited by:

    1. Zhong, Yan & Sang, Huiyan & Cook, Scott J. & Kellstedt, Paul M., 2023. "Sparse spatially clustered coefficient model via adaptive regularization," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    2. Petrovici, Norbert & Belbe, Stefana (Ștefana) & Mare, Codruta (Codruța) & Cotoi, Calin (Călin), 2023. "Hybrid health regimes: Access to primary care physicians and COVID-19 vaccine uptake across municipalities in Romania," Social Science & Medicine, Elsevier, vol. 337(C).
    3. June L. Gin & Michelle D. Balut & Aram Dobalian, 2022. "COVID-19 Vaccine Hesitancy among U.S. Veterans Experiencing Homelessness in Transitional Housing," IJERPH, MDPI, vol. 19(23), pages 1-12, November.
    4. Abolfazl Mollalo & Alireza Mohammadi & Sara Mavaddati & Behzad Kiani, 2021. "Spatial Analysis of COVID-19 Vaccination: A Scoping Review," IJERPH, MDPI, vol. 18(22), pages 1-14, November.
    5. Daniel Badell & Jesica de Armas & Albert Julià, 2022. "Impact of Socioeconomic Environment on Home Social Care Service Demand and Dependent Users," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    6. Basim Aljohani & Randolph Hall, 2024. "Optimizing the Selection of Mass Vaccination Sites: Access and Equity Consideration," IJERPH, MDPI, vol. 21(4), pages 1-19, April.
    7. Aloyce R. Kaliba & Donald R. Andrews, 2023. "The Impact of Meso-Level Factors on SARS-CoV-2 Vaccine Early Hesitancy in the United States," IJERPH, MDPI, vol. 20(13), pages 1-27, July.
    8. Cory Anderson & Shuai Zhou & Guangqing Chi, 2023. "Population-Wide Vaccination Hesitancy among the Amish: A County-Level Study of COVID-19 Vaccine Adoption and Implications for Public Health Policy and Practice," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(4), pages 1-24, August.
    9. Giuseppe Pangan & Victoria Woodard, 2024. "A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana," IJERPH, MDPI, vol. 21(7), pages 1-19, July.

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