Department of Applied & Computational Mathematics & Statistics, University of Notre Dame, Notre Dame, IN 46556, USA.
Int J Environ Res Public Health. 2024 Jul 9;21(7):892. doi: 10.3390/ijerph21070892.
The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.
新冠疫苗接种运动导致美国各地的疫苗接种率不均衡,尤其是在农村地区、社会经济弱势群体聚集地区以及存在疫苗犹豫行为的人群中。本研究旨在调查 2021 年印第安纳州每月的县一级社会人口统计学和政治归属特征如何对 COVID-19 疫苗接种模式产生不同影响。我们将 2016-2020 年美国社区调查五年估计中的县一级人口统计数据与印第安纳州选举结果数据库中的县一级政治归属特征与印第安纳州卫生部门的 COVID-19 疫苗接种数据相联系。然后,我们创建了 12 个每月线性回归模型,以评估根据赤池信息量准则(AIC)和调整后的 R 平方值,哪些变量被一致选择。疫苗接种模型显示与拥有学士学位的居民比例、40-59 岁居民比例、民主党派投票居民比例呈正相关,与未参保居民和失业居民、生活在贫困线以下的居民、无法上网的居民和其他种族居民呈负相关。总体而言,4 月之后,选择的变量是一致的,COVID-19 累计疫苗接种模型的高调整 R 值表明,县一级社会人口统计学和政治归属特征可以解释大部分疫苗接种差异。将县一级社会人口统计学和政治归属特征与印第安纳州的 COVID-19 疫苗接种情况联系起来,揭示了不同社会人口统计学群体之间疫苗覆盖范围存在固有的不平等。通过有针对性的信息传递,未来可以提高疫苗接种率,为不太可能接种疫苗的群体提供具有文化相关性的广告宣传活动,并为农村、资源匮乏和服务不足的人群增加疫苗接种机会。