Planella-Morató Jesús, Pelegrí Josep L, Martín-Rey Marta, Olivé Abelló Anna, Vallès Xavier, Roca Josep, Rodrigo Carlos, Estrada Oriol, Vallès-Casanova Ignasi
Departament d'Oceanografia Física i Tecnològica, Institut de Ciències del Mar, CSIC, Barcelona, Spain.
Departament de Física, Universitat de Girona, Girona, Spain.
Front Public Health. 2024 Dec 5;12:1430902. doi: 10.3389/fpubh.2024.1430902. eCollection 2024.
Numerous studies have explored whether and how the spread of the SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19), responds to environmental conditions without reaching consistent answers. Sociodemographic factors, such as variable population density and mobility, as well as the lack of effective epidemiological monitoring, make it difficult to establish robust correlations. Here we carry out a regional cross-correlation study between nine atmospheric variables and an infection index ( ) estimated from standardized positive polymerase chain reaction (PCR) test cases. The correlations and associated time-lags are used to build a linear multiple-regression model between weather conditions and the index. Our results show that surface pressure and relative humidity can largely predict COVID-19 outbreaks during periods of relatively minor mobility and meeting restrictions. The occurrence of low-pressure systems, associated with the autumn onset, leads to weather and behavioral changes that intensify the virus transmission. These findings suggest that surface pressure and relative humidity are key environmental factors that may be used to forecast the spread of SARS-CoV-2.
众多研究探讨了2019冠状病毒病(COVID-19)的病原体严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的传播是否以及如何对环境条件做出反应,但尚未得出一致的答案。社会人口统计学因素,如人口密度和流动性的变化,以及缺乏有效的流行病学监测,使得难以建立强有力的相关性。在此,我们对九个大气变量与根据标准化聚合酶链反应(PCR)检测呈阳性病例估算的感染指数()进行了区域交叉相关性研究。利用这些相关性和相关的时间滞后,建立了天气条件与该指数之间的线性多元回归模型。我们的结果表明,在流动性相对较小且实施集会限制的时期,地面气压和相对湿度能够在很大程度上预测COVID-19疫情的爆发。与秋季开始相关的低压系统的出现,会导致天气和行为变化,从而加剧病毒传播。这些发现表明,地面气压和相对湿度是可用于预测SARS-CoV-2传播的关键环境因素。