Spatiotemporal heterogeneity of the association between short-term exposure to carbon monoxide and COVID-19 incidence: A multistage time-series study in the continental United States

被引:0
作者
Chen, Jia [1 ,2 ]
Lin, Ping [1 ]
Tang, Ping [1 ]
Zhu, Dajian [3 ]
Ma, Rong [4 ]
Meng, Juan [2 ]
机构
[1] Second Peoples Hosp Chengdu, Dept Otolaryngol Head & Neck Surg, Chengdu 610000, Peoples R China
[2] Sichuan Univ, West China Hosp, West China Sch Med, Dept Otorhinolaryngol Head & Neck Surg, Chengdu 610041, Peoples R China
[3] Sichuan Univ, Peoples Hosp Shuangliu Dist 1, West China Airport Hosp, Dept Otorhinolaryngol, Chengdu 610000, Peoples R China
[4] Peoples Hosp Xindu Dist, Chengdu 610500, Peoples R China
关键词
COVID-19; incidence; Carbon monoxide; Post -pandemic era; Spatiotemporal pattern; Vaccination; AIR-POLLUTION; DAILY MORTALITY; INFLAMMATION; MARKERS;
D O I
10.1016/j.heliyon.2024.e33487
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Previous research has established carbon monoxide (CO) as a significant air pollutant contributing to coronavirus disease 2019 (COVID-19) transmission. The spatiotemporal heterogeneity in the relationship between short-duration CO exposure and COVID-19 incidence remain underexplored. Investigating such heterogeneity plays a crucial role in designing region-specific cost-effective public health policies, exploring the reasons for heterogeneity, and understanding the temporal trends in the association between CO and an emerging infectious disease such as COVID-19. Methods: The 49 states of the continental United States (U.S.) were examined in this study. Initially, we developed time-series generalized additive models (GAMs) for each state to assess the preliminary correlation between daily COVID-19 cases and short-term CO exposure from April 1, 2020, to December 31, 2021. Subsequently, the correlations were compiled utilizing Lerouxprior-based conditional autoregression (LCAR) to achieve a smoothed spatial distribution. Finally, we integrated a time-varying component into the GAM and LCAR to analyze temporal correlations and illuminate the factors contributing to spatiotemporal heterogeneity. Results: Our analysis revealed that, across the 49 states, a 10-ppb increase in CO concentration was associated with a 1.33 % (95%CI: 0.86%-1.81 %) increase in COVID-19 cases on average. Furthermore, spatial variability was noted, with weaker correlations observed in the central and southeastern regions, stronger associations in the northeastern regions, and negligible associations in the western regions. Temporally, the correlation was not significant from April 2020 to June 2021, but began to increase steadily thereafter until the end of 2021. Additionally, vaccination and temperature were determined to be potential causes contributing to the heterogeneity, indicating stronger positive associations in areas with higher vaccination rates and temperatures. Conclusion: The findings of this study underscore the importance of monitoring CO pollution in the central and northeastern US, especially in the aftermath of the pandemic.
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