Cargando…
System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19
We extend the classical SIR model of infectious disease spread to account for time dependence in the parameters, which also include diffusivities. The temporal dependence accounts for the changing characteristics of testing, quarantine and treatment protocols, while diffusivity incorporates a mobile...
Autores principales: | Wang, Z., Zhang, X., Teichert, G. H., Carrasco-Teja, M., Garikipati, K. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824376/ https://www.ncbi.nlm.nih.gov/pubmed/35194281 http://dx.doi.org/10.1007/s00466-020-01894-2 |
Ejemplares similares
-
Correction to: System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19
por: Wang, Z., et al.
Publicado: (2020) -
System Inference Via Field Inversion for the Spatio-Temporal Progression of Infectious Diseases: Studies of COVID-19 in Michigan and Mexico
por: Wang, Zhenlin, et al.
Publicado: (2021) -
Trajectory Modeling of Spatio-Temporal Trends in COVID-19 Incidence in Flint and Genesee County, Michigan
por: Wojciechowski, Thomas Walter, et al.
Publicado: (2022) -
Spatio-Temporal Analysis of Infectious Diseases
por: López-Quílez, Antonio
Publicado: (2019) -
Spatio-temporal evolution of Beijing 2003 SARS epidemic
por: Cao, ZhiDong, et al.
Publicado: (2010)