ArticleJournal of computational and applied mathematics2023
Analysis of COVID-19 in Japan with extended SEIR model and ensemble Kalman filter.
Article in Journal of computational and applied mathematics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Efficient sequential Bayesian inference for state-space epidemic models using ensemble data assimilation.PLoS computational biology · 2026Article
- A Bayesian model calibration framework for stochastic compartmental models with both time-varying and time-invariant parameters.Infectious Disease Modelling · 2024Article
- Bayesian model selection for COVID-19 pandemic state estimation using extended Kalman filters: Case study for Saudi Arabia.PLOS global public health · 2024Article
- Modeling Consequences of COVID-19 and Assessing Its Epidemiological Parameters: A System Dynamics Approach.Healthcare (Basel, Switzerland) · 2023Article
- Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation.Journal of clinical medicine · 2022Article
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3 authors.
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Abstract
We introduce an extended SEIR infectious disease model with data assimilation for the study of the spread of COVID-19. In this framework, undetected asymptomatic and pre-symptomatic cases are taken into account, and the impact of their uncertain proportion is fully investigated. The standard SEIR model does not consider these populations, while their role in the propagation of the disease is acknowledged. An ensemble Kalman filter is implemented to assimilate reliable observations of three compartments in the model. The system tracks the evolution of the effective reproduction number and estimates the unobservable subpopulations. The analysis is carried out for three main prefectures of Japan and for the entire country of Japan. For these four communities, our estimated effective reproduction numbers are more stable than the corresponding ones estimated by a different method (Toyokeizai). We also perform sensitivity tests for different values of some uncertain medical parameters, like the relative infectivity of symptomatic/asymptomatic cases. The regional analysis results suggest the decreasing efficiency of the states of emergency.
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