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Tytuł:
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Risk factors associated with mortality of COVID-19 in 3125 counties of the United States.
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Autorzy:
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Tian T; School of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Zhang J; School of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Hu L; School of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Jiang Y; School of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Duan C; School of Mathematics, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Li Z; School of Management, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275, Guangdong, China.
Wang X; School of Statistics, Capital University of Economics and Business, 121 Zhangjialukou, Huaxiang Fengtai District, Beijing, 100070, China. .; School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, China. .
Zhang H; School of Public Health, Yale University, 60 College Street, New Haven, CT, 06520-8034, USA. .
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Źródło:
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Infectious diseases of poverty [Infect Dis Poverty] 2021 Jan 04; Vol. 10 (1), pp. 3. Date of Electronic Publication: 2021 Jan 04.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: London : BioMed Central, 2012-
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MeSH Terms:
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COVID-19/*mortality
Aged ; COVID-19/ethnology ; COVID-19/virology ; Cluster Analysis ; Female ; Humans ; Male ; Mortality ; Pandemics ; Prevalence ; Public Health ; Race Factors ; Risk Factors ; SARS-CoV-2/isolation & purification ; Sex Factors ; Socioeconomic Factors ; Statistics, Nonparametric ; United States/epidemiology
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References:
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Grant Information:
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UL1 TR001863 United States TR NCATS NIH HHS
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Contributed Indexing:
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Keywords: Adverse health factors; County-level confirmed and deaths; Physical environment; Race/ethnicity; Segregation index
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Entry Date(s):
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Date Created: 20210105 Date Completed: 20210113 Latest Revision: 20230919
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Update Code:
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20240105
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PubMed Central ID:
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PMC7780082
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DOI:
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10.1186/s40249-020-00786-0
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PMID:
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33397470
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Background: The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood.
Methods: Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal-Wallis tests were used in our statistical analysis.
Results: A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties.
Conclusions: The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19.
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