Cargando…
Detection of space–time clusters using a topological hierarchy for geospatial data on COVID-19 in Japan
In this paper, we detected space–time clusters using data on coronavirus disease 2019 (COVID-19) collected daily by each prefecture in Japan. COVID-19 has spread globally since the first confirmed case in China, in December 2019. Several people have to date been infected in Japan since the first con...
Autores principales: | Takemura, Yusuke, Ishioka, Fumio, Kurihara, Koji |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9097570/ https://www.ncbi.nlm.nih.gov/pubmed/35578605 http://dx.doi.org/10.1007/s42081-022-00159-x |
Ejemplares similares
-
Enhanced cluster detection and noise reduction for geospatial time series data of COVID-19
por: Gaire, Sabitri, et al.
Publicado: (2023) -
Topological Strings and Integrable Hierarchies
por: Aganagic, M, et al.
Publicado: (2003) -
SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering
por: Cresswell, Kellen G., et al.
Publicado: (2020) -
Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy
por: Liao, Xinmeng, et al.
Publicado: (2023) -
A geospatial platform to support visualization, analysis, and prediction of tuberculosis notification in space and time
por: Dao, Thang Phuoc, et al.
Publicado: (2022)