%0 Journal Article %1 thi_quynh_nguyen_2024_10685793 %A Nguyen, Thi-Quynh %A Ngo, Thi-Thuy %A Than, Thi-Binh %D 2024 %J World Journal of Biology Pharmacy and Health Sciences %K Clustering Spatial %N 2 %P 187–194 %R 10.30574/wjbphs.2023.15.2.0361 %T Spatial clustering analysis of COVID-19 using LISA: A case study of the 2022 winter Day in Hanoi, Vietnam %U https://wjbphs.com/content/spatial-clustering-analysis-covid-19-using-lisa-case-study-2022-winter-day-hanoi-vietnam %V 15 %X 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.

@article{thi_quynh_nguyen_2024_10685793, 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.}, added-at = {2024-03-17T09:09:12.000+0100}, author = {Nguyen, Thi-Quynh and Ngo, Thi-Thuy and Than, Thi-Binh}, biburl = {https://www.bibsonomy.org/bibtex/277d2639db2f7d7c0927e18302a0bb166/wjbphsjournal}, doi = {10.30574/wjbphs.2023.15.2.0361}, interhash = {8b216ab46cbe80d18bd290b726563479}, intrahash = {77d2639db2f7d7c0927e18302a0bb166}, issn = {2582-5542}, journal = {{World Journal of Biology Pharmacy and Health Sciences}}, keywords = {Clustering Spatial}, month = feb, number = 2, pages = {187–194}, timestamp = {2024-03-17T09:09:12.000+0100}, title = {Spatial clustering analysis of COVID-19 using LISA: A case study of the 2022 winter Day in Hanoi, Vietnam}, url = {https://wjbphs.com/content/spatial-clustering-analysis-covid-19-using-lisa-case-study-2022-winter-day-hanoi-vietnam}, volume = 15, year = 2024 }