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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.
Chen, Jia; Lin, Ping; Tang, Ping; Zhu, Dajian; Ma, Rong; Meng, Juan.
Afiliação
  • Chen J; Department of Otolaryngology - Head and Neck Surgery, The Second People's Hospital of Chengdu, Chengdu, 610000, China.
  • Lin P; Department of Otorhinolaryngology - Head and Neck Surgery, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, 610041, China.
  • Tang P; Department of Otolaryngology - Head and Neck Surgery, The Second People's Hospital of Chengdu, Chengdu, 610000, China.
  • Zhu D; Department of Otolaryngology - Head and Neck Surgery, The Second People's Hospital of Chengdu, Chengdu, 610000, China.
  • Ma R; Department of Otorhinolaryngology, The First People's Hospital of Shuangliu District / West China (Airport) Hospital Sichuan University, Chengdu, 610000, China.
  • Meng J; People's Hospital of Xindu District, Chengdu, 610500, China.
Heliyon ; 10(13): e33487, 2024 Jul 15.
Article em En | MEDLINE | ID: mdl-39040246
ABSTRACT

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 Leroux-prior-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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article