Identifying US County-level characteristics associated with high COVID-19 burden.
Identifying US County-level characteristics associated with high COVID-19 burden.
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DOI：
10.1186/s12889-021-11060-9
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发表时间：
2021-05-28
影响因子：
4.5
通讯作者：
Lin X
中科院分区：
文献类型：
--
作者：
Li D;Gaynor SM;Quick C;Chen JT;Stephenson BJK;Coull BA;Lin X
确定与2019冠状病毒（COVID-19）高负担相关的县级特征有助于以数据为导向，公平分配公共卫生干预资源，并减轻医疗保健系统的负担。综合来自美国所有3142个县的各种政府和非营利机构的数据，我们研究了截至2020年12月21日与累积和每周病例和死亡率相关的县级特征。我们使用广义线性混合模型对累积和每周（每个县40次重复测量）病例和死亡进行建模。累积和每周模型包括州固定效应和县特异性随机效应。每周模型还允许协变量效应随季节变化，并包括美国人口普查区域特定的B样条来调整时间趋势。农村县、少数民族和白色/非白色种族隔离较多的县，以及没有高中文凭和患有医学合并症的人较多的县与COVID-19累积病例和死亡率较高相关。在春季，城市县和少数民族较多的县以及白色/非白色隔离与每周病例和死亡率的增加有关。在秋季，农村县与较大的每周病例和死亡率有关。在春季、夏季和秋季，具有更多社会经济劣势和医疗合并症的居民的县与更高的每周病例和死亡率相关。这些县级关联基于全国完整的数据，来自一个单一的模型框架，纵向分析了美国县级的COVID-19疫情，并适用于指导美国不同县的政府资源分配政策。在线版本包含补充材料，可通过10.1186/s12889-021-11060-9获得。
Identifying county-level characteristics associated with high coronavirus 2019 (COVID-19) burden can help allow for data-driven, equitable allocation of public health intervention resources and reduce burdens on health care systems. Synthesizing data from various government and nonprofit institutions for all 3142 United States (US) counties, we studied county-level characteristics that were associated with cumulative and weekly case and death rates through 12/21/2020. We used generalized linear mixed models to model cumulative and weekly (40 repeated measures per county) cases and deaths. Cumulative and weekly models included state fixed effects and county-specific random effects. Weekly models additionally allowed covariate effects to vary by season and included US Census region-specific B-splines to adjust for temporal trends. Rural counties, counties with more minorities and white/non-white segregation, and counties with more people with no high school diploma and with medical comorbidities were associated with higher cumulative COVID-19 case and death rates. In the spring, urban counties and counties with more minorities and white/non-white segregation were associated with increased weekly case and death rates. In the fall, rural counties were associated with larger weekly case and death rates. In the spring, summer, and fall, counties with more residents with socioeconomic disadvantage and medical comorbidities were associated greater weekly case and death rates. These county-level associations are based off complete data from the entire country, come from a single modeling framework that longitudinally analyzes the US COVID-19 pandemic at the county-level, and are applicable to guiding government resource allocation policies to different US counties. The online version contains supplementary material available at 10.1186/s12889-021-11060-9.
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DOI：
10.1073/pnas.2019378118
发表时间：
2021-01-05
影响因子：
11.1
作者：
Mueller, J. Tom;McConnell, Kathryn;Farrell, Justin
通讯作者：
Farrell, Justin
影响因子：
6.3
作者：
Farrell, Timothy W.;Ferrante, Lauren E.;Saliba, Debra
通讯作者：
Saliba, Debra
影响因子：
10.4
作者：
Boronow, Katherine E.;Perovich, Laura J.;Brody, Julia Green
通讯作者：
Brody, Julia Green
影响因子：
8
作者：
Laventhal, Naomi;Basak, Ratna;Macauley, Robert
通讯作者：
Macauley, Robert
影响因子：
--
作者：
Block, Ray Jr;Berg, Arthur;Nunez-Smith, Marcella
通讯作者：
Nunez-Smith, Marcella