Spatial clustering analysis of COVID-19 using LISA: A case study of the 2022 winter Day in Hanoi, Vietnam
1 Faculty of Nursing, East Asia University of Technology, Hanoi, Vietnam.
2 Faculty of Nursing, Phenikaa University, Hanoi, Vietnam.
3 Department of Training, Lang Son Medical College, Lang Son, Vietnam.
Research Article
World Journal of Biology Pharmacy and Health Sciences, 2023, 15(02), 187–194.
Article DOI: 10.30574/wjbphs.2023.15.2.0361
Publication history:
Received on 11 July 2023; revised on 18 August 2023; accepted on 21 August 2023
Abstract:
Background:A novel coronavirus disease outbreak in 2019 (COVID-19) caused by he emergence of severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) in China quickly spreads throughout the world. This study aimed to analyze the spatial clustering of COVID-19.
Methods:The global and local Moran's I statistic (LISA) was used to investigate the spatial clusters of COVID-19 including spatial clusters (high-high and low-low) and spatial outliers (low-high and high-low).
Results: A case study of COVID-19 locally transmitted cases reported in a 2022 winter day in Hanoi city has indicated that high-high spatial clusters were totally concentrated in 6 urban districts in the Hanoi metropolitan including such as districts of Dong Da, Gia Lam, Thanh Tri, Hai Ba Trung, Cau Giay, and Long Bien. Whereas, low-low spatial clusters were mainly in sub-urban districts such as Ba Vi, Thach That, Phuc Tho, and Son Tay town (0 cases) in the northwest and Ung Hoa district in the south of Hanoi.
Conclusions:The study results indicated the effectiveness of LISA in analysis of spatial clustering of COVID-19. Findings in this study make great contributions to the fight of the COVID-19 pandemic.
Keywords:
Spatial Clustering; Moran’s I statistic; LISA; COVID-19; Hanoi; Vietnam
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