The COVID-19 pandemic has adversely affected US public health, resulting in over a hundred million cases and more than one million deaths. Vaccination is the key intervention against the COVID-19 pandemic. Multiple COVID-19 vaccines are now available for human use. However, a number of factors, including socio-demographic variables, impact the uptake of COVID-19 vaccines. In this study, we apply a Bayesian mixed-effects model to assess different socio-demographic and spatial factors that influence the acceptance of COVID-19 vaccines in the US. The fitted mixed-effects model provides the probabilistic inference about the vaccine acceptance determinants with uncertainty quantification.

翻译：COVID-19大流行对美国公共卫生造成了不利影响，导致超过一亿例病例和一百多万例死亡。疫苗接种是应对COVID-19大流行的关键干预措施。目前已有多种COVID-19疫苗可供人类使用。然而，包括社会人口学变量在内的多种因素影响着COVID-19疫苗的接种率。在本研究中，我们应用一种贝叶斯混合效应模型来评估影响美国COVID-19疫苗接受度的不同社会人口学因素和空间因素。拟合的混合效应模型提供了关于疫苗接受度决定因素的概率推断，并进行了不确定性量化。