Use of Getis-Ord's statistic to detect hotspots and coldspots of COVID-19 in Hanoi City, Vietnam

Background: The emergence and rapid spread of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a potentially fatal disease, is swiftly leading to public health crises worldwide. This study aimed to detect hotspots and coldspots of COVID-19 in Hanoi city, Vietnam.
Methods: the Getis-Ord’s G*i statistic-based hotspot analysis was employed to detect hotspots and coldspots of COVID-19 pandemic in Hanoi city. Two methods for constructing spatial weight matrix have been used, namely the first and second order of contiguity.
Results: it was found from a case study of COVID-19 cases reported on 31 January 2022 in Hanoi city, a total of six hotspots and six coldspots of COVID-19 were detected using the first order contiguity (statistically significance at the 0.05 level). For the case of using the second order of contiguity, six hotspots and three coldspots were successfully identified. Hotspots were mainly concentrated in urbarn districts in the east of Hanoi. Coldspots were detected in the western suburban districts.
Conclusions: the study results has proven the effective use of Getis-Ord's statistics to detect hotspots and coldspots of COVID-19 pandemic. Findings in this study make great contributions to our understanding of the spatial clustering of the COVID-19 pandemic.