Relationships between socio-demographic structure and spatio-temporal distribution patterns of COVID-19 cases in Istanbul, Turkey

IF 2.9 3区 工程技术 Q2 ENVIRONMENTAL STUDIES
M. Yılmaz, Aslı Ulubaş Hamurcu
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引用次数: 4

Abstract

ABSTRACT This study aims to find out specific relationships between socio-demographic and spatio-temporal distribution patterns of COVID-19 cases. Istanbul being one of the most dynamic and overpopulated cities in Turkey is chosen as the case area. The study explores the spatio-temporal spread pattern of COVID-19 between 24 September and 12 December 2020 in 960 neighbourhoods of Istanbul using spatial statistical analysis. Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) methods are used to explain how socio-demographic structure and intensity of COVID-19 cases are related. The results of the study show that gender, household size, and population density are important drivers of exposure to COVID-19. Education level is also found statistically significant though having a weaker effect on spatio-temporal distribution pattern of COVID-19. It is anticipated that the findings of this study will be used by the decision-makers to take action to control the spread of the COVID-19 pandemic – and any other upcoming and unexpected diseases – and to improve the existing conditions to overcome such vulnerabilities to possible risk factors.
土耳其伊斯坦布尔社会人口结构与COVID-19病例时空分布格局的关系
摘要本研究旨在探讨新型冠状病毒肺炎病例的社会人口学特征与时空分布格局之间的具体关系。伊斯坦布尔是土耳其最具活力和人口过剩的城市之一,被选为案例区域。该研究利用空间统计分析探讨了2020年9月24日至12月12日期间2019冠状病毒病在伊斯坦布尔960个街区的时空传播模式。使用普通最小二乘(OLS)和地理加权回归(GWR)方法解释了社会人口结构与COVID-19病例强度之间的关系。研究结果表明,性别、家庭规模和人口密度是COVID-19暴露的重要驱动因素。受教育程度对新冠肺炎时空分布格局的影响较弱,但也具有统计学意义。预计这项研究的结果将被决策者用来采取行动,控制COVID-19大流行以及任何其他即将到来和意想不到的疾病的传播,并改善现有条件,以克服对可能的风险因素的脆弱性。
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
CiteScore
5.90
自引率
6.90%
发文量
36
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