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Novel indicator for the spread of new coronavirus disease 2019 and its association with human mobility in Japan.
Kawakami, Yuta; Nojiri, Shuko; Nakamoto, Daisuke; Irie, Yoshiki; Miyazawa, Satoshi; Kuroki, Manabu; Nishizaki, Yuji.
  • Kawakami Y; Clinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
  • Nojiri S; Department of Mathematics, Physics, Electrical Engineering and Computer Science, Graduate School of Engineering Science, Yokohama National University, 79-5 Tokiwadai, Hodogaya-Ku, Yokohama, Kanagawa, 240-8501, Japan.
  • Nakamoto D; Clinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. s-nojiri@juntendo.ac.jp.
  • Irie Y; Medical Technology Innovation Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. s-nojiri@juntendo.ac.jp.
  • Miyazawa S; Clinical Translational Science, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. s-nojiri@juntendo.ac.jp.
  • Kuroki M; Clinical Translational Science, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
  • Nishizaki Y; Clinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Sci Rep ; 13(1): 115, 2023 01 03.
Article in English | MEDLINE | ID: covidwho-2186071
ABSTRACT
The Japanese government adopted policies to control human mobility in 2020 to prevent the spread of severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). The present study examined the impact of human mobility on COVID-19 cases at the prefectural level in Japan by devising an indicator to have a relationship between the number of infected people and on human mobility. We calculated origin-destination travel mobility within prefectures in Japan from March 1st to December 31st, 2020, using mobile phone data. A cross-correlation function (CCF) was used to examine the relationship between human mobility and a COVID-19 infection acceleration indicator (IAI), which represents the rate of change in the speed of COVID-19 infection. The CCF of intraprefectural human mobility and the IAI in Tokyo showed a maximum value of 0.440 at lag day 12, and the IAI could be used as an indicator to predict COVID-19 cases. Therefore, the IAI and human mobility during the COVID-19 pandemic were useful for predicting infection status. The number of COVID-19 cases was associated with human mobility at the prefectural level in Japan in 2020. Controlling human mobility could help control infectious diseases in a pandemic, especially prior to starting vaccination.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2023 Document Type: Article Affiliation country: S41598-022-27322-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2023 Document Type: Article Affiliation country: S41598-022-27322-4