What explains spatial variations of COVID-19 vaccine hesitancy?: a social-ecological-technological systems approach

Arun Pallathadka, Heejun Chang, Daikwon Han
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引用次数: 14

Abstract

While COVID-19 vaccines have been available since December 2020 and efforts have been made to vaccinate the maximum population, a large number of people are continuing to be hesitant, prolonging the pandemic in the US. While most previous studies investigated social, economic, and demographic variables that are associated with COVID-19 vaccine hesitancy, we added ecological and technological variables to better understand the spatial variations of vaccine rates in the contiguous United States using spatial regression and geographically weighted regression (GWR) models. We aim to identify spatially varying social, ecological, and technological factors that are associated with COVID-19 vaccination rates, which can aid in identifying and strengthening the public health system and vaccination programs that can eventually facilitate and overcome vaccination hesitancy. We found six statistically significant predictors; two predictors, % Republican voters (r = 0.507, p < .001) and % Black population (r = −0.360, p < .001) were negatively correlated with the vaccination rates, whereas four remaining predictors, % Population with college degree (r = 0.229, p < 001), NRI Score (r = 0.131, p < .001), % Population with broadband access (r = 0.020, p < 001), and Health facilities per 10 000 population (r = 0.424, p < 001) were positively correlated with the vaccination rates at the county level. GWR results show spatially varying relationships between vaccination rate and explanatory variables, indicating the need for regional-specific public health policy. To achieve widespread vaccination, addressing social, ecological, and technological factors will be essential. We draw particular attention to the spatial variances even among positively and negatively associated factors. This research also calls for a reexamination of existing practices, including vaccination communication and other public health policies, local and national public health organizations, telecommunications agents, and mobilization of resources by the public and private sectors.
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如何解释COVID-19疫苗犹豫的空间差异?社会-生态-技术系统方法
虽然自2020年12月以来已经有了COVID-19疫苗,并且已经努力为最大限度的人口接种疫苗,但许多人仍然犹豫不决,延长了美国的大流行。虽然之前的大多数研究调查了与COVID-19疫苗犹豫相关的社会、经济和人口变量,但我们添加了生态和技术变量,以便使用空间回归和地理加权回归(GWR)模型更好地了解美国邻近地区疫苗接种率的空间变化。我们的目标是确定与COVID-19疫苗接种率相关的空间差异的社会、生态和技术因素,这有助于确定和加强公共卫生系统和疫苗接种计划,最终促进和克服疫苗接种犹豫不决。我们发现了六个统计上显著的预测因子;两个预测因子,%共和党选民(r = 0.507, p <措施)和%黑人(r =−0.360,p <措施)负相关疫苗接种率,剩余四个预测因子,而%人口与大学学位(r = 0.229, p < 001),新名词评分(r = 0.131, p <措施),%的人口与宽带接入(r = 0.020, p < 001),每000人口和卫生设施(r = 0.424, p < 001)呈正相关疫苗接种率县级。GWR结果显示疫苗接种率与解释变量之间的关系存在空间差异,表明有必要制定针对特定区域的公共卫生政策。为了实现广泛的疫苗接种,解决社会、生态和技术因素将是必不可少的。我们特别注意空间差异,甚至在积极和消极相关的因素。这项研究还要求重新审查现有做法,包括疫苗接种宣传和其他公共卫生政策、地方和国家公共卫生组织、电信代理以及公共和私营部门调动资源。
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