Natural Sciences Department, Kremenchuk Mykhailo Ostrohradskyi National University, Kremenchuk, Ukraine.
Department of Artificial Intelligence, University of Information Technology and Management in Rzeszow, Rzeszow, Poland.
Sci Rep. 2023 Aug 7;13(1):12752. doi: 10.1038/s41598-023-39705-2.
The statistics of COVID-19 accumulated in Ukraine show areas with a significantly lower incidence of diseases. The purpose of the study was to identify factors that could influence the pattern of the pandemic in a particular area. Within the study it was assumed that the level of health care is approximately the same throughout the country. Population density was considered the main factor influencing the dynamics of the spread of infection. To reduce the impact of changes in population density across regions, it was normalized by the average population density in the country. The normalization of statistics for the country resulted in a model in the form of a linear relationship between the normalized values of the number of COVID-19 cases in the region and the size of the region. Subsequent analysis of the graphical data made it possible to identify four regions with the lowest incidence of COVID-19. The geographical proximity of these regions Dnipro, Kherson, Vinnytsia and Kirovograd, indicates the presence of a common factor for them, not typical for the rest of Ukraine. Such a factor may be the location of 83% of Ukraine's uranium deposits in the territories around Kirovohrad. Radon is one of the decay products of uranium, so the population of these areas may experience increased exposure to radon. This noble gas has more than a century of medical use, in particular for pulmonary diseases, although there is still no consensus about its effectiveness and side effects. Considering that COVID-19 was often complicated by pulmonary diseases, it can be assumed that the geological specificity of these four regions of Ukraine had an impact on the course of the COVID-19 pandemic in their territories. The study findings are important in terms of further COVID-19 research and prevention strategies.
乌克兰 COVID-19 累计统计数据显示出疾病发病率较低的地区。本研究的目的是确定可能影响特定地区大流行模式的因素。研究中假设，全国的医疗保健水平大致相同。人口密度被认为是影响感染传播动态的主要因素。为了降低区域间人口密度变化的影响，通过该国的平均人口密度对其进行了标准化。对全国统计数据进行标准化后，得到了一种模型，该模型将区域内 COVID-19 病例的标准化值与区域大小之间呈线性关系。对图形数据的后续分析使我们能够确定 COVID-19 发病率最低的四个地区。这些地区第聂伯罗、赫尔松、文尼察和基洛夫格勒的地理位置接近，表明它们存在一个共同因素，而这个因素在乌克兰其他地区并不典型。这种因素可能是乌克兰 83%的铀矿床位于基洛夫格勒周边地区。氡是铀的衰变产物之一，因此这些地区的人口可能会接触到更多的氡。这种惰性气体已有一个多世纪的医疗用途，特别是在肺部疾病方面，尽管关于其有效性和副作用仍未达成共识。考虑到 COVID-19 经常伴有肺部疾病，因此可以假设乌克兰这四个地区的地质特殊性对其境内 COVID-19 大流行的进程产生了影响。这些研究结果对于进一步研究 COVID-19 和预防策略具有重要意义。
