Parameter Estimation on a Stochastic SIR Model with Media Coverage

Li, Changguo; Pei, Yongzhen; Zhu, Ming; Deng, Yue

doi:10.1155/2018/3187807

Cited by 6 publications

(16 citation statements)

References 12 publications

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“…However, we were encouraged by the consistent clustering between mice and the ability of LHS to distinguish naïve and APA+ mice by their non-overlapping ranges for liver and spleen permeation and retention properties, while also revealing greater variability in APA+ mice. Other approaches to parameter estimation, such as Markov Chain Monte Carlo, have been demonstrated for other dynamical systems (Li et al 2018 ; Talawar and Aundhakar 2016 ). Bayesian methods combined with MCMC have been demonstrated for parameter identification in PBPK systems (Krauss et al 2013 ), and LHS has been previously employed for quantifying uncertainty in PBPK (Fàbrega et al 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Experimental Data and PBPK Modeling Quantify Antibody Interference in PEGylated Drug Carrier Delivery

et al. 2021

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Section: Discussionmentioning

confidence: 99%

Experimental Data and PBPK Modeling Quantify Antibody Interference in PEGylated Drug Carrier Delivery

et al. 2021

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“…Using the Routh-Hurwitz criteria, the asymptotic stability of the equilibrium for equations (4) and 5is calculated. We can also use the Jacobian matrix of equations (4) and (5) to illustrate this as follows:…”

Section: Theoretical Analysis Of Equilibrium Stabilitymentioning

confidence: 99%

“…In serious cases, traffic accidents occur in chaos, which will further aggravate the impact of the whole event. In such an emergency, if evacuees can calm the panic as soon as possible, casualties can be avoided or significantly reduced [4]. erefore, proper official guidance can save many lives in an emergency.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Spreading Model of Passenger Group Panic considering Official Guidance Information in Subway Emergencies

Tang

Wang

2019

Mathematical Problems in Engineering

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Safety concerns are increasing as rail transportation develops at a fast pace. When emergencies erupt in the course of transportation, panic will spread among passengers. Subway operators should understand how the emotions of passengers spread and how the guidance instructions work, in order to effectively deter the transmission of panic. Based on the models of system dynamics, transmission dynamics, and contagious disease, the essay constructs a dynamic transmission model for passenger panic inside the carriage, incorporating the official guidance instructions. Then, the essay utilizes Routh–Hurwitz criteria and analyzes the stability equilibrium of the dynamic differential equation. Mathematical analysis and simulation tests have verified the validity of the model and stability conditions. Finally, it is proved in the essay by mathematical analysis and simulation tests that official guidance instructions can effectively control the spread of panic and quickly stabilize the system. Thus, the essay helps subway operators to come up with clear official guidance, so as to find quick solutions and prevent escalation of panic due to lack of trust.

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“…Althaus [ 21 ] estimated the basic reproductive number of the Ebola virus in West Africa. Li et al [ 22 ] estimated the parameters of the stochastic SIR model using the maximum likelihood and Bayesian approaches with reference to media coverage of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Pandemic Data Modeling in Pakistan Using Time-Series SIR

Taimoor

Ali

Shah

et al. 2022

Computational and Mathematical Methods in Medicine

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Pakistan is currently facing the fourth wave of the deadly coronavirus, which was first reported in Wuhan, China, in December 2019. This work utilizes the epidemiological models to analyze Pakistan’s COVID-19 data. The basic susceptible, infected, and recovered (SIR) model is studied assuming Bayesian and time-series SIR (tSIR) approaches. Many studies have been conducted from different perspectives, but to the best of our knowledge, no study is available using the SIR models for Pakistan. The coronavirus incubation period has been set to 14 days across the globe; however, this study noticed that the assumption of 14 days is not suitable for Pakistan’s data. Furthermore, on the basis of R 0 , we infer that COVID-19 is not a pandemic in Pakistan, as it was in other nations, such as the United States, India, Brazil, and Italy, among others. We attribute this to the best strategy adopted by the Government of Pakistan to minimize the burden of COVID-19 cases in Pakistani hospitals. It is also noticed that the posterior-based SIR (pSIR) model with uniform prior to R 0 and Poisson distribution (of log-likelihood) provides better results as compared to other distributions. From time-series SIR (tSIR), we observed that the value of the reporting rate ρ is less than 1 which means that cases are underreported.

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Parameter Estimation on a Stochastic SIR Model with Media Coverage

Cited by 6 publications

References 12 publications

Experimental Data and PBPK Modeling Quantify Antibody Interference in PEGylated Drug Carrier Delivery

Experimental Data and PBPK Modeling Quantify Antibody Interference in PEGylated Drug Carrier Delivery

Dynamic Spreading Model of Passenger Group Panic considering Official Guidance Information in Subway Emergencies

COVID-19 Pandemic Data Modeling in Pakistan Using Time-Series SIR

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