Grillenzoni Carlo
IUAV: Institute of Architecture, University of Venice, Italy.
Hyg Environ Health Adv. 2022 Dec;4:100026. doi: 10.1016/j.heha.2022.100026. Epub 2022 Sep 9.
The effects of environmental factors on the spread of the CoViD-19 pandemic have been widely debated in the scientific literature. The results are important for understanding the outbreak dynamics and for defining health measures of prevention and containment. Using multivariate autoregressive (AR) models and robust statistics of causality, this paper analyzes the effect of 19 time series (10 physical and 9 social) on 3 daily CoViD-19 series (infected, hospitalized, deaths) in the Milan area for about 16 months. Robust M-estimation shows the weak effect of climatic and pollution factors, while authority restrictions, people mobility, smart working and vaccination rate have a significant impact. In particular, the vaccination campaign is important for reducing hospitalizations and deaths.
环境因素对新冠疫情传播的影响在科学文献中一直存在广泛争论。这些结果对于理解疫情动态以及确定预防和控制的卫生措施至关重要。本文使用多元自回归（AR）模型和稳健的因果关系统计方法，分析了19个时间序列（10个物理因素和9个社会因素）对米兰地区约16个月内3个每日新冠疫情序列（感染、住院、死亡）的影响。稳健的M估计表明气候和污染因素的影响较弱，而政府限制、人员流动、远程办公和疫苗接种率则有显著影响。特别是，疫苗接种运动对于减少住院和死亡至关重要。
