ABSTRACT

The study is the first attempt to assess the role of climatic predictors in the rise of COVID-19 intensity in the Russian climatic region. The study used the Random Forest algorithm to understand the underlying associations and monthly scenarios. The results show that temperature seasonality (29.2 ± 0.9%) has the highest contribution for COVID-19 transmission in the humid continental region. In comparison, the diurnal temperature range (26.8 ± 0.4%) and temperature seasonality (14.6 ± 0.8%) had the highest impacts in the sub-arctic region. Our results also show that September and October have favorable climatic conditions for the COVID-19 spread in the sub-arctic and humid continental regions, respectively. From June to August, the high favorable zone for the spread of the disease will shift towards the sub-arctic region from the humid continental region. The study suggests that the government should implement strict measures for these months to prevent the second wave of COVID-19 outbreak in Russia.

摘要

该研究首次尝试评估气候预测因子在俄罗斯气候区 COVID-19 强度上升中的作用。该研究使用随机森林算法来了解潜在的关联和每月情景。结果表明，温度季节性（29.2 ± 0.9%）对潮湿大陆地区的 COVID-19 传播贡献最大。相比之下，昼夜温度范围（26.8±0.4%）和温度季节性（14.6±0.8%）对亚北极地区的影响最大。我们的研究结果还表明，9 月和 10 月分别有利于 COVID-19 在亚北极和潮湿大陆地区传播的气候条件。从六月到八月，疾病传播的高度有利区将从潮湿的大陆地区向亚北极地区转移。该研究表明，政府应在这几个月内实施严格的措施，以防止俄罗斯爆发第二波 COVID-19。