School of Informatics, Aristotle University of Thessaloniki, GR-54124 Thessalonica, Greece.
Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas (CERTH), Thermi, GR-57001 Thessalonica, Greece.
Viruses. 2021 Mar 29;13(4):574. doi: 10.3390/v13040574.
The Covid-19 pandemic has required nonpharmaceutical interventions, primarily physical distancing, personal hygiene and face mask use, to limit community transmission, irrespective of seasons. In fact, the seasonality attributes of this pandemic remain one of its biggest unknowns. Early studies based on past experience from respiratory diseases focused on temperature or humidity, with disappointing results. Our hypothesis that ultraviolet (UV) radiation levels might be a factor and a more appropriate parameter has emerged as an alternative to assess seasonality and exploit it for public health policies. Using geographical, socioeconomic and epidemiological criteria, we selected twelve North-equatorial-South countries with similar characteristics. We then obtained UV levels, mobility and Covid-19 daily incidence rates for nearly the entire 2020. Using machine learning, we demonstrated that UV radiation strongly associated with incidence rates, more so than mobility did, indicating that UV is a key seasonality indicator for Covid-19, irrespective of the initial conditions of the epidemic. Our findings can inform the implementation of public health emergency measures, partly based on seasons in the Northern and Southern Hemispheres, as the pandemic unfolds into 2021.
Covid-19 大流行需要采取非药物干预措施，主要是保持身体距离、个人卫生和戴口罩，以限制社区传播，无论季节如何。事实上，这种大流行的季节性特征仍然是其最大的未知数之一。早期基于过去呼吸道疾病经验的研究主要集中在温度或湿度上，但结果令人失望。我们假设紫外线 (UV) 辐射水平可能是一个因素，并且作为评估季节性和利用其制定公共卫生政策的替代方法，一个更合适的参数已经出现。使用地理、社会经济和流行病学标准，我们选择了十二个具有相似特征的北赤道-南赤道国家。然后，我们获得了近 2020 年的 UV 水平、流动性和 Covid-19 每日发病率。使用机器学习，我们证明了 UV 辐射与发病率密切相关，比流动性更相关，这表明 UV 是 Covid-19 的一个关键季节性指标，无论疫情的初始条件如何。我们的发现可以为公共卫生应急措施的实施提供信息，部分依据北半球和南半球的季节，因为大流行在 2021 年继续发展。
