Baylor College of Medicine and Texas Children's Hospital, Section of Immunology Allergy and Retrovirology, Houston, TX.
Baylor Saint Luke's Medical Center, Houston, TX.
Am J Infect Control. 2021 Jun;49(6):678-684. doi: 10.1016/j.ajic.2020.12.009. Epub 2020 Dec 19.
Like most of the world, the United States' public health and economy are impacted by the COVID19 pandemic. However, discrete pandemic effects may not be fully realized on the macro-scale. With this perspective, our goal is to visualize spread of the pandemic and measure county-level features which may portend vulnerability.
We accessed the New York Times GitHub repository COVID19 data and 2018 United States Census data for all United States Counties. The disparate datasets were merged and filtered to allow for visualization and assessments about case fatality rate (CFR%) and associated demographic, ethnic and economic features.
Our results suggest that county-level COVID19 fatality rates are related to advanced population age (P < .001) and less diversity as evidenced by higher proportion of Caucasians in High CFR% counties (P < .001). Also, lower CFR% counties had a greater proportion of the population reporting has having 2 or more races (P < .001). We noted no significant differences between High and Low CFR% counties with respect to mean income or poverty rate.
Unique COVID19 impacts are realized at the county level. Use of public datasets, data science skills and information visualization can yield helpful insights to drive understanding about community-level vulnerability.
与世界上大多数国家一样，美国的公共卫生和经济受到了 COVID19 大流行的影响。然而，大流行在宏观层面上的具体影响可能尚未完全显现。基于这一观点，我们的目标是可视化大流行的传播，并衡量可能预示脆弱性的县级特征。
我们访问了《纽约时报》的 GitHub 存储库 COVID19 数据和 2018 年美国人口普查数据，获取了所有美国县的数据。将这些不同的数据集进行合并和筛选，以实现对病死率（CFR%）和相关人口统计学、种族和经济特征的可视化和评估。
我们的研究结果表明，县级 COVID19 死亡率与人口老龄化程度较高有关（P<0.001），而且高 CFR%县的白种人比例较高，表明其多样性较低（P<0.001）。此外，低 CFR%县报告有两种或更多种族的人口比例更高（P<0.001）。在平均收入或贫困率方面，我们没有发现高 CFR%县和低 CFR%县之间有显著差异。
COVID19 在县级层面上产生了独特的影响。使用公共数据集、数据科学技能和信息可视化可以提供有帮助的见解，以推动对社区脆弱性的理解。
