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Sci Rep
. 2025 Jan 7;15(1):1081.
doi: 10.1038/s41598-024-82962-y. Hotspot analysis of COVID-19 infection in Tokyo based on influx patterns
Yu Kimura 1 , Tatsunori Seki 2 , Keisuke Chujo 2 , Toshiki Murata 3 , Tomoaki Sakurai 2 , Satoshi Miyata 2 , Hiroyasu Inoue 4 5 , Nobuyasu Ito 5
Affiliations
We analyse the relationship between population influx and the effective reproduction number in the 23 wards of Tokyo during the COVID-19 pandemic to estimate hotspots of infection. We identify some patterns of population influx via factor analysis and estimate specific areas as infection-related hotspots by focusing on influx patterns that are highly correlated with the effective reproduction number. As a result, several influx patterns are assumed to be directly related to the subsequent spread of the infection. This analytical method has the potential to detect unknown hotspots related to pandemics in the future.
. 2025 Jan 7;15(1):1081.
doi: 10.1038/s41598-024-82962-y. Hotspot analysis of COVID-19 infection in Tokyo based on influx patterns
Yu Kimura 1 , Tatsunori Seki 2 , Keisuke Chujo 2 , Toshiki Murata 3 , Tomoaki Sakurai 2 , Satoshi Miyata 2 , Hiroyasu Inoue 4 5 , Nobuyasu Ito 5
Affiliations
- PMID: 39774000
- PMCID: PMC11707207
- DOI: 10.1038/s41598-024-82962-y
We analyse the relationship between population influx and the effective reproduction number in the 23 wards of Tokyo during the COVID-19 pandemic to estimate hotspots of infection. We identify some patterns of population influx via factor analysis and estimate specific areas as infection-related hotspots by focusing on influx patterns that are highly correlated with the effective reproduction number. As a result, several influx patterns are assumed to be directly related to the subsequent spread of the infection. This analytical method has the potential to detect unknown hotspots related to pandemics in the future.