A population-based spatio-temporal analysis of the early COVID-19 dynamic in Serbia

Q3 Social Sciences
Stanovnistvo Pub Date : 2022-01-01 DOI:10.2298/stnv2201001l
Suzana Lovic-Obradovic, H. Rabiei-Dastjerdi, S. Matović
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引用次数: 1

Abstract

The COVID-19 pandemic escalated in almost all parts of the world over a very short period of time. The speed of the spread was determined by the degree of mobility of the population, while the risk of severe illness or death depended on the population?s demographic characteristics, population health status, and the capacity of the health system to treat patients. This paper aims to assess spatio-temporal patterns of patients with COVID-19 in Serbia at the early stage and whether these patterns are linked to valid public health measures that were enforced during this period. The study adopted the local Moran?s index to identify the spatial grouping of the number of infected at a municipality level and joinpoint regression analysis to identify whether and when statistically significant changes occurred to the number of infected by gender and age groups, and to the number of deaths in the entire population. The results show the polarisation of the spatial grouping of the number of infected. Considering the change in the trend in the number of infected between genders, no significant difference was noticeable. When the age-gender categories of infected were examined, the differences became more significant. In addition, changes in the trend were associated with the tightening or loosening of public health measures.
基于人群的塞尔维亚COVID-19早期动态时空分析
COVID-19大流行在很短的时间内几乎在世界所有地区升级。传播的速度取决于人口的流动程度,而严重疾病或死亡的风险取决于人口。人口特征、人口健康状况和卫生系统治疗病人的能力。本文旨在评估塞尔维亚早期COVID-19患者的时空模式,以及这些模式是否与此期间实施的有效公共卫生措施有关。该研究采用了当地的Moran?S指数用于确定城市一级感染人数的空间分组,并进行联结点回归分析,以确定按性别和年龄组划分的感染人数以及整个人口中死亡人数是否以及何时发生了统计上显著的变化。结果表明,感染人数的空间分组呈两极分化。考虑到感染人数在性别之间的变化趋势,没有明显差异。当检查感染者的年龄-性别类别时,差异变得更加显著。此外,这一趋势的变化与公共卫生措施的收紧或放松有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Stanovnistvo
Stanovnistvo Social Sciences-Social Sciences (all)
CiteScore
0.60
自引率
0.00%
发文量
7
审稿时长
15 weeks
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