Spatial clustering analysis of COVID-19 using LISA: A case study of the 2022 winter Day in Hanoi, Vietnam

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.