A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation...

Full description

Bibliographic Details
Main Authors: Yukun Tan, Durward Cator III, Martial Ndeffo-Mbah, Ulisses Braga-Neto
Format: Article
Language:English
Published: AIMS Press 2021-09-01
Series:Mathematical Biosciences and Engineering
Subjects:
epidemic model
seird model
nonlinear stochastic model
unscented kalman filter
maximum likelihood
adaptive filtering
parameter estimation
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2021381?viewType=HTML

Internet

https://www.aimspress.com/article/doi/10.3934/mbe.2021381?viewType=HTML

Similar Items