Department of Development and Sustainability, School of Environment, Resources and Development, Asian Institute of Technology (AIT), Pathumthani, Thailand.
Centre of International Politics, Organization, and Disarmament, School of International Studies, Jawaharlal Nehru University, New Delhi, India.
Int J Environ Health Res. 2022 Apr;32(4):723-737. doi: 10.1080/09603123.2020.1793921. Epub 2020 Jul 16.
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.
这项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。研究使用随机森林算法来理解潜在的关联和月度情景。结果表明,温度季节性(29.2±0.9%)对湿润大陆地区 COVID-19 传播的贡献最高。相比之下,昼夜温差(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 月分别有利于亚北极和湿润大陆地区 COVID-19 的传播。从 6 月到 8 月,疾病传播的高有利区将从湿润大陆地区向亚北极地区转移。该研究表明,政府应在这些月份实施严格措施,以防止俄罗斯 COVID-19 第二波爆发。