Institute of Geography and Environmental Sciences, Jan Kochanowski University in Kielce, Poland.
Environ Res. 2023 Jan 1;216(Pt 3):114662. doi: 10.1016/j.envres.2022.114662. Epub 2022 Oct 30.
Several waves of COVID-19 caused by different SARS-CoV-2 variants have been recorded worldwide. During this period, many publications were released describing the influence of various factors, such as environmental, social and economic factors, on the spread of COVID-19. This paper presents the results of a detailed spatiotemporal analysis of the course of COVID-19 cases and deaths in five waves in Poland in relation to green‒blue spaces. The results, based on 380 counties, reveal that the negative correlation between the indicator of green‒blue space per inhabitant and the average daily number of COVID-19 cases and deaths was clearly visible during all waves. These relationships were described by a power equation (coefficient of determination ranging from 0.83 to 0.88) with a high level of significance. The second important discovery was the fact that the rates of COVID-19 cases and deaths were significantly higher in urban counties (low values of the green-blue space indicator in m/people) than in rural areas. The developed models can be used in decision-making by local government authorities to organize anti-COVID-19 prevention measures, including local lockdowns, especially in urban areas.
由不同 SARS-CoV-2 变体引起的几波 COVID-19 已在全球范围内记录。在此期间,发布了许多出版物,描述了环境、社会和经济等各种因素对 COVID-19 传播的影响。本文介绍了 COVID-19 在波兰五次浪潮中与绿色-蓝色空间相关的病例和死亡的详细时空分析结果。基于 380 个县的结果表明,在所有波次中,绿色-蓝色空间人均指标与 COVID-19 病例和死亡的平均日数量之间的负相关关系非常明显。这些关系由幂方程(决定系数范围从 0.83 到 0.88)描述,具有很高的显著性。第二个重要发现是,城市县的 COVID-19 病例和死亡率明显高于农村地区(人均绿色-蓝色空间指标值较低)。开发的模型可用于地方政府当局做出决策,以组织包括局部封锁在内的抗 COVID-19 预防措施,尤其是在城市地区。