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巴西城市气象参数与 COVID-19 病例:一项观察性研究。

Meteorological parameters and cases of COVID-19 in Brazilian cities: an observational study.

机构信息

Department of Architecture and Urbanism; State University of Londrina (Uel), Londrina, PR, Brazil.

Department of Statistics, State University of Londrina (Uel), Londrina, Pr, Brazil.

出版信息

J Toxicol Environ Health A. 2022 Jan 2;85(1):14-28. doi: 10.1080/15287394.2021.1969304. Epub 2021 Sep 2.

DOI:10.1080/15287394.2021.1969304
PMID:34474657
Abstract

Meteorological parameters modulate transmission of the SARS-Cov-2 virus, the causative agent related to coronavirus disease-2019 (COVID-19) development. However, findings across the globe have been inconsistent attributed to several confounding factors. The aim of the present study was to investigate the relationship between reported meteorological parameters from July 1 to October 31, 2020, and the number of confirmed COVID-19 cases in 4 Brazilian cities: São Paulo, the largest city with the highest number of cases in Brazil, and the cities with greater number of cases in the state of Parana during the study period (Curitiba, Londrina and Maringa). The assessment of meteorological factors with confirmed COVID-19 cases included atmospheric pressure, temperature, relative humidity, wind speed, solar irradiation, sunlight, dew point temperature, and total precipitation. The 7- and 15-day moving averages of confirmed COVID-19 cases were obtained for each city. Pearson's correlation coefficients showed significant correlations between COVID-19 cases and all meteorological parameters, except for total precipitation, with the strongest correlation with maximum wind speed (0.717, <0.001) in São Paulo. Regression tree analysis demonstrated that the largest number of confirmed COVID-19 cases was associated with wind speed (between ≥0.3381 and <1.173 m/s), atmospheric pressure (<930.5mb), and solar radiation (<17.98e). Lower number of cases was observed for wind speed <0.3381 m/s and temperature <23.86°C. Our results encourage the use of meteorological information as a critical component in future risk assessment models.

摘要

气象参数调节 SARS-CoV-2 病毒的传播,该病毒是导致 2019 年冠状病毒病(COVID-19)发展的病原体。然而,由于存在多种混杂因素,全球各地的研究结果并不一致。本研究旨在调查 2020 年 7 月 1 日至 10 月 31 日期间报告的气象参数与巴西 4 个城市(圣保罗,巴西病例最多的最大城市,以及该研究期间巴拉那州病例较多的城市(库里蒂巴,隆德里纳和马雷格罗)的确诊 COVID-19 病例数之间的关系。评估与确诊 COVID-19 病例相关的气象因素包括大气压、温度、相对湿度、风速、太阳辐射、日照、露点温度和总降水量。每个城市都获得了 7 天和 15 天的确诊 COVID-19 病例移动平均值。Pearson 相关系数显示,COVID-19 病例与所有气象参数均呈显著相关,除总降水量外,与最大风速(0.717,<0.001)相关性最强。回归树分析表明,与确诊 COVID-19 病例相关的病例数最多的是风速(介于≥0.3381 和 <1.173 m/s)、大气压(<930.5mb)和太阳辐射(<17.98e)。风速<0.3381 m/s 和温度<23.86°C 时病例数较低。我们的研究结果鼓励将气象信息作为未来风险评估模型的关键组成部分加以利用。

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