☆ 4.7 Article

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

JOURNAL OF CLINICAL MEDICINE (2022)

Related references

Note: Only part of the references are listed.

Article Automation & Control Systems

Data-driven modeling and forecasting of COVID-19 outbreak for public policy making

A. Hasan et al.

Summary: This paper presents a data-driven approach for COVID-19 modeling and forecasting, which can be used by policymakers to control the outbreak through non-pharmaceutical interventions. The paper applies an extended Kalman filter to estimate the time-varying effective reproduction number and forecasts the effect of relaxing and tightening public measures. Case studies are provided to demonstrate the practicality of the approach.

ISA TRANSACTIONS (2022)

Add to Collection

Article Biology

A behavioural modelling approach to assess the impact of COVID-19 vaccine hesitancy

Bruno Buonomo et al.

Summary: This study introduces a new epidemic model to describe the spread of COVID-19 within a population. The findings show that voluntary vaccination can reduce the impact of the disease but cannot eliminate it completely. Widespread information coverage and short-term memory are effective in mitigating vaccine hesitancy and refusal. Additionally, the possible impact of seasonality on disease spread is investigated.

JOURNAL OF THEORETICAL BIOLOGY (2022)

Add to Collection

Article Mathematics, Interdisciplinary Applications

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

A. Schaum et al.

Summary: The present paper aims to present an extended contact-based model for analyzing the spread of contagious diseases in complex networks, with consideration of asymptomatic evolutions. The paper also introduces a parametrization method for the model and validates it using actual data from the spread of COVID-19 in Germany, Mexico, and the United States of America. Furthermore, the paper showcases the combination of contact-based network spreading models with modern state estimation and filtering techniques for real-time monitoring and efficient dealing with uncertainties.

CHAOS SOLITONS & FRACTALS (2022)

Add to Collection

Article Infectious Diseases

Bayesian sequential data assimilation for COVID-19 forecasting

Maria L. Daza-Torres et al.

Summary: This article introduces a Bayesian sequential data assimilation and forecasting method for non-autonomous dynamical systems, with application to the current COVID-19 pandemic. The method sequentially updates forecasts over a sliding window of epidemic records and assembles prior distributions for state variables to achieve a balance between data fitting and dynamical system prediction.

EPIDEMICS (2022)

Add to Collection

Article Biology

Sequential Data Assimilation of the Stochastic SEIR Epidemic Model for Regional COVID-19 Dynamics

Ralf Engbert et al.

Summary: The study suggests that applying sequential data assimilation to the stochastic SEIR epidemic model can capture the dynamic behavior of outbreaks and achieve short-term predictions on a regional level. Regional modeling, considering spatial heterogeneity and stochasticity, offers a more realistic approach for epidemic prediction and control.

BULLETIN OF MATHEMATICAL BIOLOGY (2021)

Add to Collection

Article Multidisciplinary Sciences

Tracking R of COVID-19: A new real-time estimation using the Kalman filter

Francisco Arroyo-Marioli et al.

Summary: This study introduces a new method for estimating the effective reproduction number of infectious diseases, applied to tracking the dynamics of COVID-19. The method utilizes Kalman filter to estimate the time-varying growth rate of infected individuals from new case data, and performs well even in imperfectly measured situations or when the infection does not follow the SIR model. The estimated R values for COVID-19 in 124 countries are provided for assessing the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.

PLOS ONE (2021)

Add to Collection

Article Biology

A non-parametric method for determining epidemiological reproduction numbers

Frank P. Pijpers

Summary: This paper presents a non-parametric inverse method for determining the average transmission rate of infected cases, demonstrated using the timeline of hospitalisation admissions for COVID-19 in the Netherlands.

JOURNAL OF MATHEMATICAL BIOLOGY (2021)

Add to Collection

Article Medicine, General & Internal

Seroprevalence and humoral immune durability of anti-SARS-CoV-2 antibodies in Wuhan, China: a longitudinal, population-level, cross-sectional study

Zhenyu He et al.

LANCET (2021)

Add to Collection

Article Mathematics

An Extended SEIR Model with Vaccination for Forecasting the COVID-19 Pandemic in Saudi Arabia Using an Ensemble Kalman Filter

Rabih Ghostine et al.

Summary: This paper introduces an extended SEIR model with a vaccination compartment to simulate COVID-19 spread in Saudi Arabia. Mathematical analysis and data assimilation experiments are used to enhance the model's predictive skills.

MATHEMATICS (2021)

Add to Collection

Article Biology

Alternative Strategies for the Estimation of a Disease's Basic Reproduction Number: A Model-Agnostic Study

Gustavo Nicolas Paez et al.

Summary: This work evaluates four different models for estimating the basic reproduction number of a disease in a model-agnostic manner. The models are compared based on their theoretical foundations and tested through eight impartial simulations. The advantages and flaws of each model are discussed from both theoretical and practical perspectives.

BULLETIN OF MATHEMATICAL BIOLOGY (2021)

Add to Collection

Article Biology

Analyzing the effects of observation function selection in ensemble Kalman filtering for epidemic models

Leah Mitchell et al.

Summary: The Ensemble Kalman Filter (EnKF) is a widely used method in epidemiological studies for parameter estimation and forecast prediction. The choice of observation function is crucial in connecting unknown system variables with observed data, and different functions can impact the accuracy of filtering estimates and predictions. This study demonstrates the importance of selecting an appropriate observation function based on available data for EnKF estimates in various filtering scenarios.

MATHEMATICAL BIOSCIENCES (2021)

Add to Collection

Article Mathematics, Applied

AN INTERNATIONAL INITIATIVE OF PREDICTING THE SARS-COV-2 PANDEMIC USING ENSEMBLE DATA ASSIMILATION

Geir Evensen et al.

Summary: This study demonstrates the efficiency of utilizing iterative ensemble smoothers to estimate the parameters of an SEIR model. By extending the standard SEIR model with age-classes and compartments, and conditioning on data of accumulated deaths and hospitalized cases, the model can accurately predict epidemic development and assess the impact of intervention measures. The approach used in this study can potentially be applicable to more complex models with regional compartments for accurate long-term epidemic scenarios.

FOUNDATIONS OF DATA SCIENCE (2021)

Add to Collection

Article Mathematical & Computational Biology

Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation

Eve Armstrong et al.

Summary: The study demonstrates the capabilities of statistical data assimilation in accurately estimating the state and parameters in an epidemiological model for COVID-19. Results show that excellent estimates of all quantities can be obtained using noiseless measurement data, with the exception of the time-varying transmission rate prior to the implementation of social distancing.

INFECTIOUS DISEASE MODELLING (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Kalman filter based short term prediction model for COVID-19 spread

Koushlendra Kumar Singh et al.

Summary: This article conducts studies and analysis on the latest data of COVID19 spread using machine learning models and techniques, identifies important contributing factors, and estimates future virus spread using Kalman Filter for short term estimation.

APPLIED INTELLIGENCE (2021)

Add to Collection

Article Multidisciplinary Sciences

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

Marino Gatto et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Add to Collection

Article Multidisciplinary Sciences

Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)

Ruiyun Li et al.

SCIENCE (2020)

Add to Collection

Article Immunology

Reconstruction of Transmission Pairs for Novel Coronavirus Disease 2019 (COVID-19) in Mainland China: Estimation of Superspreading Events, Serial Interval, and Hazard of Infection

Xiao-Ke Xu et al.

CLINICAL INFECTIOUS DISEASES (2020)

Add to Collection

Article Mathematics, Interdisciplinary Applications

Dynamics identification and forecasting of COVID-19 by switching Kalman filters

Xiaoshu Zeng et al.

COMPUTATIONAL MECHANICS (2020)

Add to Collection

Article Public, Environmental & Occupational Health

An epidemiological modelling approach for COVID-19 via data assimilation

Philip Nadler et al.

EUROPEAN JOURNAL OF EPIDEMIOLOGY (2020)

Add to Collection

Article Medicine, General & Internal

Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis

Diana Buitrago-Garcia et al.

PLOS MEDICINE (2020)

Add to Collection

Editorial Material Medicine, General & Internal

Asymptomatic transmission of covid-19

Allyson M. Pollock et al.

BMJ-BRITISH MEDICAL JOURNAL (2020)

Add to Collection

Article Biochemical Research Methods

Practical considerations for measuring the effective reproductive number, Rt

Katelyn M. Gostic et al.

PLOS COMPUTATIONAL BIOLOGY (2020)

Add to Collection

Article Green & Sustainable Science & Technology

Big data assimilation to improve the predictability of COVID-19

Xin Li et al.

GEOGRAPHY AND SUSTAINABILITY (2020)

Add to Collection

Article Multidisciplinary Sciences

Using the kalman filter with Arima for the COVID-19 pandemic dataset of Pakistan

Muhammad Aslam

DATA IN BRIEF (2020)

Add to Collection

Article Physics, Fluids & Plasmas

Epidemic spreading on modular networks: The fear to declare a pandemic

Lucas D. Valdez et al.

PHYSICAL REVIEW E (2020)

Add to Collection

Article Infectious Diseases

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

R. N. Thompson et al.

EPIDEMICS (2019)

Add to Collection

Article Public, Environmental & Occupational Health

A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics

Anne Cori et al.

AMERICAN JOURNAL OF EPIDEMIOLOGY (2013)

Add to Collection

Article Physics, Multidisciplinary

Discrete-time Markov chain approach to contact-based disease spreading in complex networks

S. Gomez et al.

EPL (2010)

Add to Collection

Article Biology

Variational data assimilation with epidemic models

C. J. Rhodes et al.

JOURNAL OF THEORETICAL BIOLOGY (2009)

Add to Collection

Article Biology

Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission

P van den Driessche et al.

MATHEMATICAL BIOSCIENCES (2002)

Add to Collection

Review Mathematics, Applied

The mathematics of infectious diseases

HW Hethcote

SIAM REVIEW (2000)

Add to Collection

© Peeref 2019-2024. All rights reserved.