{"title":"COVID-19 病例数量的地区趋势","authors":"Keisuke Chujo, Tatsunori Seki, Toshiki Murata, Yu Kimura, Tomoaki Sakurai, Satoshi Miyata, Hiroyasu Inoue, Nobuyasu Ito","doi":"10.1007/s10015-024-00938-7","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, we analysed the novel coronavirus disease (COVID-19) cases data to investigate the regional infection trends in Japan. There had been seven outbreaks by October 2022 in Japan. In each outbreak, the number of COVID-19 cases has increased at different rates in different regions. The prefectural infection ratio is defined using COVID-19 cases data. We calculate the prefectural infection ratio and study the characteristic of each pandemic wave. The prefectural order of infection progression is estimated in each past wave of the COVID-19 pandemic. This study shows that the infection spread from the Kanto region in the fourth pandemic wave and the infection spread simultaneously from four regions in the sixth wave. It is also found that the infection situation trend in Okinawa differs from that in the other regions.</p></div>","PeriodicalId":46050,"journal":{"name":"Artificial Life and Robotics","volume":"29 2","pages":"205 - 210"},"PeriodicalIF":0.8000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10015-024-00938-7.pdf","citationCount":"0","resultStr":"{\"title\":\"Regional trends in the number of COVID-19 cases\",\"authors\":\"Keisuke Chujo, Tatsunori Seki, Toshiki Murata, Yu Kimura, Tomoaki Sakurai, Satoshi Miyata, Hiroyasu Inoue, Nobuyasu Ito\",\"doi\":\"10.1007/s10015-024-00938-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this study, we analysed the novel coronavirus disease (COVID-19) cases data to investigate the regional infection trends in Japan. There had been seven outbreaks by October 2022 in Japan. In each outbreak, the number of COVID-19 cases has increased at different rates in different regions. The prefectural infection ratio is defined using COVID-19 cases data. We calculate the prefectural infection ratio and study the characteristic of each pandemic wave. The prefectural order of infection progression is estimated in each past wave of the COVID-19 pandemic. This study shows that the infection spread from the Kanto region in the fourth pandemic wave and the infection spread simultaneously from four regions in the sixth wave. It is also found that the infection situation trend in Okinawa differs from that in the other regions.</p></div>\",\"PeriodicalId\":46050,\"journal\":{\"name\":\"Artificial Life and Robotics\",\"volume\":\"29 2\",\"pages\":\"205 - 210\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10015-024-00938-7.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Life and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10015-024-00938-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Life and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s10015-024-00938-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ROBOTICS","Score":null,"Total":0}
In this study, we analysed the novel coronavirus disease (COVID-19) cases data to investigate the regional infection trends in Japan. There had been seven outbreaks by October 2022 in Japan. In each outbreak, the number of COVID-19 cases has increased at different rates in different regions. The prefectural infection ratio is defined using COVID-19 cases data. We calculate the prefectural infection ratio and study the characteristic of each pandemic wave. The prefectural order of infection progression is estimated in each past wave of the COVID-19 pandemic. This study shows that the infection spread from the Kanto region in the fourth pandemic wave and the infection spread simultaneously from four regions in the sixth wave. It is also found that the infection situation trend in Okinawa differs from that in the other regions.
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