ArticleComputers in biology and medicine2021
Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling.
Article in Computers in biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 55 citations in OpenAlex.
- A data-driven analysis and forecasting of Leishmaniasis-COVID-19 co-infection model using ensemble Kalman filter.Scientific reports · 2026Article
- A semi-mechanistic modeling strategy for infectious diseases forecasting: Error correction and probabilistic prediction.Biosafety and health · 2026Article
- Article
- Kalman Filter-Based Epidemiological Model for Post-COVID-19 Era Surveillance and Prediction.Sensors (Basel, Switzerland) · 2025Article
- Joint estimation of hand-foot-mouth disease model and prediction in korea using the ensemble kalman filter.PLoS computational biology · 2025Article
- Bayesian model selection for COVID-19 pandemic state estimation using extended Kalman filters: Case study for Saudi Arabia.PLOS global public health · 2024Article
- Research on the Cooperative Target State Estimation and Tracking Optimization Method of Multi-UUV.Sensors (Basel, Switzerland) · 2023Article
- Kalman-based compartmental estimation for covid-19 pandemic using advanced epidemic model.Biomedical signal processing and control · 2023Article
- A new hybrid prediction model of COVID-19 daily new case data.Engineering applications of artificial intelligence · 2023Article
- Early estimation of the number of hidden HIV infected subjects: An extended Kalman filter approach.Infectious Disease Modelling · 2023Article
- Analysis and simulation of a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures: A case study of the outbreak in Urumqi, China in August 2022.Infectious Disease Modelling · 2023Article
- Bayesian Noise Modelling for State Estimation of the Spread of COVID-19 in Saudi Arabia with Extended Kalman Filters.Sensors (Basel, Switzerland) · 2023Article
- Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates.Computer methods and programs in biomedicine · 2023Article
- Article
- Recursive state and parameter estimation of COVID-19 circulating variants dynamics.Scientific reports · 2022Article
- An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic.Health and technology · 2022Article
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Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a new stochastic-based method for modelling and analysis of COVID-19 spread. A new deterministic Susceptible, Exposed, Infectious, Recovered (Re-infected) and Deceased-based Social Distancing model, named SEIR(R)D-SD, is proposed by introducing the re-infection rate and social distancing factor into the traditional SEIRD (Susceptible, Exposed, Infectious, Recovered and Deceased) model to account for the effects of re-infection and social distancing on COVID-19 spread. The deterministic SEIRD(R)D-SD model is further converted into the stochastic form to account for uncertainties involved in COVID-19 spread. Based on this, an extended Kalman filter (EKF) is developed based on the stochastic SEIR(R)D-SD model to simultaneously estimate both model parameters and transmission state of COVID-19 spread. Simulation results and comparison analyses demonstrate that the proposed method can effectively account for the re-infection and social distancing as well as uncertain effects on COVID-19 spread, leading to improved accuracy for prediction of COVID-19 spread.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.