21 results match your criteria Applied Mathematical Modelling[Journal]

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Review of fractional epidemic models.

Appl Math Model 2021 Sep 20;97:281-307. Epub 2021 Apr 20.

School of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong 643000, China.

The global impact of corona virus (COVID-19) has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 influenza A(H1N1) pandemic. In this paper, we have focused on reviewing the results of epidemiological modelling especially the fractional epidemic model and summarized different types of fractional epidemic models including fractional Susceptible-Infective-Recovered (SIR), Susceptible-Exposed-Infective-Recovered (SEIR), Susceptible-Exposed-Infective-Asymptomatic-Recovered (SEIAR) models and so on. Furthermore, we propose a general fractional SEIAR model in the case of single-term and multi-term fractional differential equations. Read More

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September 2021

Modeling airborne pathogen transport and transmission risks of SARS-CoV-2.

Authors:
Clifford K Ho

Appl Math Model 2021 Jul 24;95:297-319. Epub 2021 Feb 24.

Sandia National Laboratories, P.O. Box 5800, MS-1127, Albuquerque, NM 87185, USA.

An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g. Read More

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Fractional model for the spread of COVID-19 subject to government intervention and public perception.

Appl Math Model 2021 Jul 17;95:89-105. Epub 2021 Feb 17.

Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN 37132-0001, USA.

COVID-19 pandemic has impacted people all across the world. As a result, there has been a collective effort to monitor, predict, and control the spread of this disease. Among this effort is the development of mathematical models that could capture accurately the available data and simulate closely the futuristic scenarios. Read More

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Global analysis of the COVID-19 pandemic using simple epidemiological models.

Appl Math Model 2021 Feb 22;90:995-1008. Epub 2020 Oct 22.

Department of Physics & Astronomy, University of the Western Cape, P/B X17 Bellville ZA-7535, South Africa.

Several analytical models have been developed in this work to describe the evolution of fatalities arising from coronavirus COVID-19 worldwide. The Death or 'D' model is a simplified version of the well-known SIR (susceptible-infected-recovered) compartment model, which allows for the transmission-dynamics equations to be solved analytically by assuming no recovery during the pandemic. By fitting to available data, the D-model provides a precise way to characterize the exponential and normal phases of the pandemic evolution, and it can be extended to describe additional spatial-time effects such as the release of lockdown measures. Read More

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February 2021

The threshold of a deterministic and a stochastic SIQS epidemic model with varying total population size.

Appl Math Model 2021 Mar 8;91:749-767. Epub 2020 Oct 8.

Department of Applied Mathematics, Lanzhou University of Technology, Lanzhou 730050, People's Republic of China.

In this paper, a stochastic and a deterministic SIS epidemic model with isolation and varying total population size are proposed. For the deterministic model, we establish the threshold . When is less than 1, the disease-free equilibrium is globally stable, which means the disease will die out. Read More

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A time-delayed SVEIR model for imperfect vaccine with a generalized nonmonotone incidence and application to measles.

Authors:
Isam Al-Darabsah

Appl Math Model 2021 Mar 1;91:74-92. Epub 2020 Oct 1.

Department of Applied Mathematics, University of Waterloo, Waterloo, ON N2L 3G1, Canada.

In this paper, we investigate the effects of the latent period on the dynamics of infectious disease with an imperfect vaccine. We assume a general incidence rate function with a non-monotonicity property to interpret the psychological effect in the susceptible population when the number of infectious individuals increases. After we propose the model, we provide the well-posedness property by verifying the non-negativity and boundedness of the models solutions. Read More

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Analytical features of the SIR model and their applications to COVID-19.

Appl Math Model 2021 Feb 28;90:466-473. Epub 2020 Sep 28.

Angara GmbH, In der Steele 2, Düsseldorf 40599, Germany.

A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painlevé test shows that the system of equations is not integrable in the general case. Read More

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February 2021

Design of a nonlinear model for the propagation of COVID-19 and its efficient nonstandard computational implementation.

Appl Math Model 2021 Jan 22;89:1835-1846. Epub 2020 Sep 22.

Department of Mathematics and Statistics, The University of Lahore, Lahore, Pakistan.

In this manuscript, we develop a mathematical model to describe the spreading of an epidemic disease in a human population. The emphasis in this work will be on the study of the propagation of the coronavirus disease (COVID-19). Various epidemiologically relevant assumptions will be imposed upon the problem, and a coupled system of first-order ordinary differential equations will be obtained. Read More

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January 2021

Transmission dynamics and control methodology of COVID-19: A modeling study.

Appl Math Model 2021 Jan 21;89:1983-1998. Epub 2020 Sep 21.

Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville 37919, USA.

The coronavirus disease 2019 (COVID-19) has grown up to be a pandemic within a short span of time. To investigate transmission dynamics and then determine control methodology, we took epidemic in Wuhan as a study case. Unfortunately, to our best knowledge, the existing models are based on the common assumption that the total population follows a homogeneous spatial distribution, which is not the case for the prevalence occurred both in the community and in hospital due to the difference in the contact rate. Read More

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January 2021

Migration rate estimation in an epidemic network.

Appl Math Model 2021 Jan 12;89:1949-1964. Epub 2020 Sep 12.

Instituto de Matemáticas, Universidad Nacional Autónoma de México, Boulevard Juriquilla No. 3001, Juriquilla, 76230, México.

Most of the recent epidemic outbreaks in the world have as a trigger, a strong migratory component as has been evident in the recent Covid-19 pandemic. In this work we address the problem of migration of human populations and its effect on pathogen reinfections in the case of Dengue, using a Markov-chain susceptible-infected-susceptible (SIS) metapopulation model over a network. Our model postulates a general contact rate that represents a local measure of several factors: the population size of infected hosts that arrive at a given location as a function of total population size, the current incidence at neighboring locations, and the connectivity of the network where the disease spreads. Read More

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January 2021

Dynamics of an SIS network model with a periodic infection rate.

Appl Math Model 2021 Jan 6;89:907-918. Epub 2020 Aug 6.

Sciences and Mathematics Faculty, College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA.

Seasonal forcing and contact patterns are two key features of many disease dynamics that generate periodic patterns. Both features have not been ascertained deeply in the previous works. In this work, we develop and analyze a non-autonomous degree-based mean field network model within a Susceptible-Infected-Susceptible (SIS) framework. Read More

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January 2021

The dynamical model for COVID-19 with asymptotic analysis and numerical implementations.

Appl Math Model 2021 Jan 8;89:1965-1982. Epub 2020 Aug 8.

Department of Mathematics, Harvard University Boston 02138, USA.

The 2019 novel coronavirus (COVID-19) emerged at the end of 2019 has a great impact on China and all over the world. The transmission mechanism of COVID-19 is still unclear. Except for the initial status and the imported cases, the isolation measures and the medical treatments of the infected patients have essential influences on the spread of COVID-19. Read More

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January 2021

Effect of pollutant source location on air pollutant dispersion around a high-rise building.

Appl Math Model 2020 May 15;81:582-602. Epub 2020 Jan 15.

Centre for Infrastructure Engineering, School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW 2751, Australia.

This article investigates the dispersion of airborne pollutants emitted from different locations near a high-rise building. A Computational Fluid Dynamics (CFD) model for simulating the wind flow field and the pollutant dispersion was developed and validated by wind tunnel data. Then the spreading of the pollutant emitted from different locations to a rectangular-shaped high-rise residential (HRR) building was numerically studied. Read More

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Chaos in a nonautonomous eco-epidemiological model with delay.

Appl Math Model 2020 Mar 8;79:865-880. Epub 2019 Nov 8.

Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.

In this paper, we propose and analyze a nonautonomous predator-prey model with disease in prey, and a discrete time delay for the incubation period in disease transmission. Employing the theory of differential inequalities, we find sufficient conditions for the permanence of the system. Further, we use Lyapunov's functional method to obtain sufficient conditions for global asymptotic stability of the system. Read More

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Accounting for data sparsity when forming spatially coherent zones.

Appl Math Model 2019 Aug;72:537-552

Sustainable Agricultural Systems, Rothamsted Research, Harpenden, AL5 2JQ, UK.

Efficient farm management can be aided by the identification of zones in the landscape. These zones can be informed from different measured variables by ensuring a sense of spatial coherence. Forming spatially coherent zones is an established method in the literature, but has been found to perform poorly when data are sparse. Read More

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Low-dose spectral CT reconstruction using image gradient -norm and tensor dictionary.

Appl Math Model 2018 Nov 21;63:538-557. Epub 2018 Jul 21.

Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA.

Spectral computed tomography (CT) has a great superiority in lesion detection, tissue characterization and material decomposition. To further extend its potential clinical applications, in this work, we propose an improved tensor dictionary learning method for low-dose spectral CT reconstruction with a constraint of image gradient -norm, which is named as TDL. The TDL method inherits the advantages of tensor dictionary learning (TDL) by employing the similarity of spectral CT images. Read More

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November 2018

Random variables with moment-matching staircase density functions.

Appl Math Model 2018 Jul;64:196-213

Aeroelasticity Branch, NASA Langley Research Center, Hampton, VA 23681, USA.

This paper proposes a family of random variables for uncertainty modeling. The variables of interest have a bounded support set, and prescribed values for the first four moments. We present the feasibility conditions for the existence of any of such variables, and propose a class of variables that conforms to such constraints. Read More

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Optimal control analysis of a tuberculosis model.

Appl Math Model 2018 Jun 29;58:47-64. Epub 2017 Dec 29.

Department of Mathematics, Sichuan University, Chengdu, Sichuan 610064, PR China.

In this paper, we extend the model of Liu and Zhang (Math Comput Model 54:836-845, 2011) by incorporating three control terms and apply optimal control theory to the resulting model. Optimal control strategies are proposed to minimize both the disease burden and the intervention cost. We prove the existence and uniqueness of optimal control paths and obtain these optimal paths analytically using Pontryagin's Maximum Principle. Read More

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Adaptive dispersal effect on the spread of a disease in a patchy environment.

Authors:
Chang-Yuan Cheng

Appl Math Model 2017 Jul 14;47:17-30. Epub 2017 Mar 14.

Department of Applied Mathematics, National Pingtung University, Pingtung 900, Taiwan, ROC.

During outbreaks of a communicable disease, people intensely follow the media coverage of the epidemic. Most people attempt to minimize contact with others, and move themselves to avoid crowds. This dispersal may be adaptive regarding the intensity of media coverage and the population numbers in different patches. Read More

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Disease control in a food chain model supplying alternative food.

Appl Math Model 2013 Apr 13;37(8):5653-5663. Epub 2012 Dec 13.

Department of Applied Mathematics, University of Calcutta, Kolkata, West Bengal, India.

Necessity to find a non-chemical method of disease control is being increasingly felt due to its eco-friendly nature. In this paper the role of alternative food as a disease controller in a disease induced predator-prey system is studied. Stability criteria and the persistence conditions for the system are derived. Read More

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A Monte Carlo/response surface strategy for sensitivity analysis: application to a dynamic model of vegetative plant growth.

Appl Math Model 1989 Aug;13:479-84

Department of Resource Crop, Soon Chun National University, Junnam, Republic of Korea.

We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. Read More

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