University of Bucharest, Street Schitu Maguranu, no. 9, Sector 1, 010181, Bucharest, Romania.
J Prev (2022). 2022 Oct;43(5):673-695. doi: 10.1007/s10935-022-00688-x. Epub 2022 Jun 29.
This is an analysis of conditions favouring the cumulative COVID-19 infection rates between February 2020 and April 2021 in Romania, as an Eastern European society, at the local community level. What are the socio-demographic and location profiles of the local communities by considering their infection rates with SARS-COV-2 at the beginning of the pandemia as a dependent variable? This is the research question that structured the approach. The general hypothesis that is tested is that reported infections with the new coronavirus are higher in communities of higher social interactions. The theoretical model is tested by multiple regression analysis working on more than 2500 local communities, out of the 3200 local administrative units of the country. Data basis for testing the model are coming from the National Institute of Public Health and the National Institute of Statistics. Higher COVID infection rates are favoured by socio-human capital, the regional capital, migration abroad experience, and modernity at a local level. Other factors are captured by the cultural areas as subregions of historical regions of the country, formed by neighboured similar counties. Nuclei of higher infections with COVID-19 are located in developed communities around large cities, high modernity areas, and communities of high emigration abroad. Principles for health public policies are formulated at the end by considering the role of decentralisation, and better ways to do a rapid and good diagnosis at local levels. To our knowledge, this is one of the very few studies that address determinants of COVID-19 infections at the local community level for a whole country in Europe. New research questions are formulated as an outcome of conclusions. They could be answered only by supplementary multilevel research. Limitations of analysis are derived from the fact that we are using only ecological, spatially aggregated data, and not multilevel ones. Relations that were recorded to the community could not be transferred to the individual level.
这是对罗马尼亚作为东欧社会在地方社区层面上 2020 年 2 月至 2021 年 4 月期间累积 COVID-19 感染率的条件进行的分析。考虑到 SARS-COV-2 在大流行初期的感染率作为因变量，哪些是地方社区的社会人口统计学和地理位置特征？这是构成研究方法的研究问题。测试的一般假设是，报告的新冠状病毒感染在社会互动较高的社区中更高。理论模型通过对全国 3200 个地方行政单位中的 2500 多个地方社区进行多元回归分析进行测试。测试模型的数据基础来自国家公共卫生研究所和国家统计局。较高的 COVID 感染率受到社会人力资本、区域资本、国外移民经验和地方层面现代化的推动。其他因素由作为该国历史地区子区域的文化区捕获，这些文化区由相邻的类似县组成。COVID-19 高感染率的核心位于大城市周边发达社区、高度现代化地区和国外移民率高的社区。在考虑权力下放作用和在地方层面进行快速和良好诊断的更好方法后，最终制定了卫生公共政策原则。据我们所知，这是为数不多的针对整个欧洲国家地方社区层面 COVID-19 感染决定因素的研究之一。新的研究问题是作为结论的结果提出的。只有通过补充多层次研究才能回答这些问题。分析的局限性源于我们只使用生态、空间聚合数据而不是多层次数据的事实。记录到社区的关系不能转移到个人层面。
