Effectiveness analysis of multiple epidemic prevention measures in the context of COVID-19 using the SVIRD model and ensemble Kalman filter
Tài liệu tham khảo
Abdy, 2021, An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia, Adv. Differ. Equ., 1, 1
Giordano, 2020, Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy, Nat. Med., 26, 855, 10.1038/s41591-020-0883-7
Faruk, 2021, A data driven analysis and forecast of COVID-19 dynamics during the third wave using SIRD model in Bangladesh, COVID, 1, 503, 10.3390/covid1020043
Yang, 2020, Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions, J. Thorac. Dis., 12, 165, 10.21037/jtd.2020.02.64
Amaral, 2021, Simulating immunization campaigns and vaccine protection against COVID-19 pandemic in Brazil, IEEE Access, 9, 126011, 10.1109/ACCESS.2021.3112036
Rise, 2022, Socioeconomic analysis of infectious diseases based on different scenarios using uncertain SEIAR system dynamics with effective subsystems and ANFIS, J. Econ. Admin. Sci.
Liu, 2022, Return to normal pre-COVID-19 life is delayed by inequitable vaccine allocation and SARS-CoV-2 variants, Epidemiol. Infect., 150, E46, 10.1017/S0950268822000139
Liu, 2020, Using the contact network model and Metropolis-Hastings sampling to reconstruct the COVID-19 spread on the “Diamond Princess”, Sci. Bull., 65, 1297, 10.1016/j.scib.2020.04.043
Zhao, 2021, Stringent nonpharmaceutical interventions are crucial for curbing COVID-19 transmission in the course of vaccination: a case study of South and Southeast asian countries, Healthcare, 9, 10.3390/healthcare9101292
He, 2020, SEIR modeling of the COVID-19 and its dynamics, Nonlinear Dynam., 101, 1667, 10.1007/s11071-020-05743-y
Fox, 2020, The impact of asymptomatic COVID-19 infections on future pandemic waves, MedRxiv
Li, 2020, Harmonizing models and observations: data assimilation in Earth system science, Sci. China Earth Sci., 63, 1059, 10.1007/s11430-019-9620-x
Rhodes, 2009, Variational data assimilation with epidemic models, J. Theor. Biol., 258, 591, 10.1016/j.jtbi.2009.02.017
Shaman, 2012, Forecasting seasonal outbreaks of influenza, Proc. Natl. Acad. Sci. USA, 109, 20425, 10.1073/pnas.1208772109
Pasetto, 2016, Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting, Adv. Water Resour., 108
Evensen, 2020, An international assessment of the COVID-19 pandemic using ensemble data assimilation, medRxiv
Ghostine, 2021, An extended SEIR model with vaccination for forecasting the COVID-19 pandemic in Saudi Arabia using an ensemble Kalman filter, Mathematics, 9.6, 636, 10.3390/math9060636
Engbert, 2021, Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics, Bull. Math. Biol., 83, 1, 10.1007/s11538-020-00834-8
Kermack, 1927, A contribution to the mathematical theory of epidemics, Proc. R. Soc. Lond. Ser. A Containing Papers of a Mathematical and Physical Character, 115, 700
Hieu, 2015, Dynamical behavior of a stochastic SIRS epidemic model, Math. Model. Nat. Phenom., 56, 10.1051/mmnp/201510205
Kuznetsov, 1994, Bifurcation analysis of periodic SEIR and SIR epidemic models, J. Math. Biol., 32, 109, 10.1007/BF00163027
van den Driessche, 2000, A simple SIS epidemic model with a backward bifurcation, J. Math. Biol., 40, 525, 10.1007/s002850000032
Sahu, 2015, Dynamics of an SEQIHRS epidemic model with media coverage, quarantine and isolation in a community with pre-existing immunity, J. Math. Anal. Appl., 421, 1651, 10.1016/j.jmaa.2014.08.019
Nadler, 2020, An epidemiological modelling approach for COVID-19 via data assimilation, Eur. J. Epidemiol., 35, 749, 10.1007/s10654-020-00676-7
Zhao, 2020, Prediction of the COVID-19 spread in African countries and implications for prevention and control: a case study in South Africa, Egypt, Algeria, Nigeria, Senegal and Kenya, Sci. Total Environ., 729, 138959, 10.1016/j.scitotenv.2020.138959
Masuhara, 2022, Convergent movement of COVID-19 outbreak in Japan based on SIR model, Econ. Anal. Policy, 73, 29, 10.1016/j.eap.2021.10.016
Zhu, 2021, Extended Kalman filter based on stochastic epidemiological model for COVID-19 modelling, Comput. Biol. Med., 137, 104810, 10.1016/j.compbiomed.2021.104810
Ma, 2022, Understanding the dynamics of pandemic models to support predictions of COVID-19 transmission: parameter sensitivity analysis of the SIR-type model, IEEE J. Biomed. Health Inform., 10.1109/JBHI.2022.3168825
Shaman, 2013, Real-time influenza forecasts during the 2012–2013 season, Nat. Commun., 4.1, 1
Orenstein, 1988, Assessing vaccine efficacy in the field: further observations, Epidemiol. Rev., 10.1, 212, 10.1093/oxfordjournals.epirev.a036023
Li, 2010, A bayesian filter framework for sequential data assimilation, Adv. Earth Sci., 25, 515
Zhu, 2014, Simultaneously assimilating multivariate data sets into the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwestern China, Geosci. Model Dev., 7, 1467, 10.5194/gmd-7-1467-2014
Fan, 2021, Coupling the K-nearest neighbors and locally weighted linear regression with ensemble Kalman filter for data-driven data assimilation, Open Geosci., 13, 1395, 10.1515/geo-2020-0312
Fan, 2021, Combining a fully connected neural network With an ensemble Kalman filter to emulate a dynamic model in data assimilation, IEEE Access., 9, 10.1109/ACCESS.2021.3120482
Liu, 2022, Quantifying the representativeness errors caused by scale transformation of remote sensing data in stochastic ensemble data assimilation, IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens., 15, 1968, 10.1109/JSTARS.2022.3149957
Hu, 2022, A novel strategy to assimilate category variables in land-use models based on Dirichlet distribution, Environ. Model. Software, 149, 10.1016/j.envsoft.2022.105324
Liu, 2020, ComDA: a common software for nonlinear and non-Gaussian land data assimilation, Environ. Model. Softw., 127, 104638, 10.1016/j.envsoft.2020.104638
Andrews, 2022, Covid-19 vaccine effectiveness against the Omicron (B. 1.1. 529) variant, New England J. Med., 386, 1532, 10.1056/NEJMoa2119451
Xia, 2004, Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics, Am. Nat., 164, 267, 10.1086/422341
Bertuzzo, 2016, On the probability of extinction of the Haiti cholera epidemic, Stoch. Environ. Res. Risk Assess., 30, 2043, 10.1007/s00477-014-0906-3
Hladish, 2012, EpiFire: an open source C++ library and application for contact network epidemiology, BMC Bioinform., 13, 1, 10.1186/1471-2105-13-76
El Kryech, 2023, Simulating and modeling the vaccination of Covid-19 pandemic using SIR Model-SVIRD
Li, 2020, Big data assimilation to improve the predictability of COVID-19, Geogr. Sustain., 1, 317