Data-assimilation and state estimation for contact-based spreading processes using the ensemble kalman filter: Application to COVID-19

Schaum, Alexander; Bernal-Jáquez, R.; Ramos, L. Alarcon

doi:10.1016/j.chaos.2022.111887

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2024

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Cited by 3 publications

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References 28 publications

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“…Up to the best of our knowledge, very few works have investigated the COVID-19 outbreak with such models coupled with epidemiological data. As a rare example, let us mention [27] which uses an ensemble Kalman filter and a undirected graph of 200 nodes with a smallworld topology for estimating the evolution of the epidemic.…”

Section: Introductionmentioning

confidence: 99%

Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation

Sun

Richard

Miyoshi

et al. 2022

JCM

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In this paper, we introduce an agent-based model together with a particle filter approach to study the spread of COVID-19. Investigations are mainly performed on the metropolis of Tokyo, but other prefectures of Japan are also briefly surveyed. A novel method for evaluating the effective reproduction number is one of the main outcomes of our approach. Other unknown parameters are also evaluated. Uncertain quantities, such as, for example, the probability that an infected agent develops symptoms, are tested and discussed, and the stability of our computations is examined. Detailed explanations are provided for the model and for the assimilation process.

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Section: Introductionmentioning

confidence: 99%