Your browser doesn't support javascript.
loading
Direct modelling from GPS data reveals daily-activity-dependency of effective reproduction number in COVID-19 pandemic.
Ozaki, Jun'ichi; Shida, Yohei; Takayasu, Hideki; Takayasu, Misako.
Afiliación
  • Ozaki J; Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503, Japan.
  • Shida Y; Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503, Japan.
  • Takayasu H; Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503, Japan.
  • Takayasu M; Sony Computer Science Laboratories, Inc., 3-14-13, Higashigotanda, Shinagawa-ku, Tokyo, 141-0022, Japan.
Sci Rep ; 12(1): 17888, 2022 10 25.
Article en En | MEDLINE | ID: mdl-36284166
During the COVID-19 pandemic, governments faced difficulties in implementing mobility restriction measures, as no clear quantitative relationship between human mobility and infection spread in large cities is known. We developed a model that enables quantitative estimations of the infection risk for individual places and activities by using smartphone GPS data for the Tokyo metropolitan area. The effective reproduction number is directly calculated from the number of infectious social contacts defined by the square of the population density at each location. The difference in the infection rate of daily activities is considered, where the 'stay-out' activity, staying at someplace neither home nor workplace, is more than 28 times larger than other activities. Also, the contribution to the infection strongly depends on location. We imply that the effective reproduction number is sufficiently suppressed if the highest-risk locations or activities are restricted. We also discuss the effects of the Delta variant and vaccination.
Asunto(s)
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido