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Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling.

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TLDR
Wang et al. as mentioned in this paper proposed a new deterministic SEIR(R)D-SD model by introducing the re-infection rate and social distancing factor into the traditional SEIRD (Susceptible, Exposed, Infectious, Recovered (Re-infected) and Deceased-based Social Distancing model).
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This article is published in Computers in Biology and Medicine.The article was published on 2021-08-28 and is currently open access. It has received 16 citations till now. The article focuses on the topics: Extended Kalman filter.

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Journal ArticleDOI

An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic

TL;DR: In this article , the authors proposed an approach based on incremental learning to build predictive models of the SEIRD variables for the COVID-19 pandemic, which is a dynamic ensemble method that allows the addition of new models or the updating of incremental models.
Proceedings ArticleDOI

State Estimation of the Spread of COVID-19 in Saudi Arabia using Extended Kalman Filter

TL;DR: In this paper , the authors considered the nonlinear compartmental epidemiological dynamical system model in the Susceptible-Exposed-Infected-Quarantined-Recovered-Deceased (SEIQRD) form based on the recursive estimator known as the extended Kalman filter (EKF) to predict the evolution of the COVID-19 pandemic in Saudi Arabia.
Journal ArticleDOI

Recursive state and parameter estimation of COVID-19 circulating variants dynamics

TL;DR: In this article , a SEIR-based model is proposed considering dynamic feedback estimation, which is suitable for dynamic feedback as simulation results presented an efficient detection and dynamic characterization of circulating variants.
Journal ArticleDOI

An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data

TL;DR: In this article , an extension/improvement of the classic SIR compartmental model is proposed, which also takes into consideration the populations of exposed, hospitalized, admitted in intensive care units (ICU), deceased and vaccinated cases, in combination with an unscented Kalman filter (UKF), providing a dynamic estimation of the time dependent system's parameters.
Journal ArticleDOI

Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates

TL;DR: In this article , an interval type-2 fuzzy stochastic modeling and control strategy was proposed to deal with the realistic uncertainties of pandemics and manage the size of the infected population.
References
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Book

Bayesian Data Analysis

TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Journal ArticleDOI

An interactive web-based dashboard to track COVID-19 in real time.

TL;DR: The outbreak of the 2019 novel coronavirus disease (COVID-19) has induced a considerable degree of fear, emotional stress and anxiety among individuals around the world.
Journal ArticleDOI

COVID-19 infection: the perspectives on immune responses.

TL;DR: The role of asymptomatic SARS-CoV-2 infected individuals in disseminating the infection remains to be defined and the conventional wisdom based on overall immunity of the infected patients cannot explain this broad spectrum in disease presentation.
Journal ArticleDOI

Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China.

TL;DR: Overall, the asymptomatic carriers identified from close contacts were prone to be mildly ill during hospitalization and highlighted the importance of close contact tracing and longitudinally surveillance via virus nucleic acid tests.
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