Analysis of stability and Hopf bifurcation for an eco-epidemiological model with distributed delay

In this paper, the dynamical behavior of an eco-epidemiological model with distributed delay is studied. Sufficient conditions for the asymptotical stability of all the equilibria are obtained. We prove that there exists a threshold value of the infection rate $b$ beyond which the positive equilibrium bifurcates towards a periodic solution. We further analyze the orbital stability of the periodic orbits arising from bifurcation by applying Poore's condition. Numerical simulation with some hypothetical sets of data has been done to support the analytical findings

Dynamic analysis of a fractional-order SIRS model with time delay

Mathematical modeling plays a vital role in the epidemiology of infectious diseases. Policy makers can provide the effective interventions by the relevant results of the epidemic models. In this paper, we build a fractional-order SIRS epidemic model with time delay and logistic growth, and we discuss the dynamical behavior of the model, such as the local stability of the equilibria and the existence of Hopf bifurcation around the endemic equilibrium. We present the numerical simulations to verify the theoretical analysis

Dynamics for a stochastic delayed SIRS epidemic model

In this paper, we consider a stochastic delayed SIRS epidemic model with seasonal variation. Firstly, we prove that the system is mathematically and biologically well-posed by showing the global existence, positivity and stochastically ultimate boundneness of the solution. Secondly, some sufficient conditions on the permanence and extinction of the positive solutions with probability one are presented. Thirdly, we show that the solution of the system is asymptotical around of the disease-free periodic solution and the intensity of the oscillation depends of the intensity of the noise. Lastly, the existence of stochastic nontrivial periodic solution for the system is obtained

Dynamical Properties of a Delay Prey-Predator Model with Disease in the Prey Species Only

A three-dimensional ecoepidemiological model with delay is considered. We first investigate the existence and stability of the equilibria. We then study the effect of the time delay on the stability of the positive equilibrium. The existence of a Hopf bifurcation at the positive equilibrium is obtained through the study of an exponential polynomial equation with delay-dependent coefficients. Numerical simulation with a hypothetical set of data has been carried out to support the analytical findings

Stability and Hopf bifurcation of a delay eco‐epidemiological model with nonlinear incidence rate

In this paper, a three‐dimensional eco‐epidemiological model with delay is considered. The stability of the two equilibria, the existence of Hopf bifurcation and the permanence are investigated. It is found that Hopf bifurcation occurs when the delay τ passes a sequence of critical values. Moreover, by applying Nyquist criterion, the length of delay is estimated for which the stability continues to hold. Numerical simulation with a hypothetical set of data has been done to support the analytical results. This work is supported by the National Natural Science Foundation of China (No. 10771104 and No.10471117), Program for Innovative Research Team (in Science and Technology) in University of Henan Province (No. 2010IRTSTHN006) and Program for Key Laboratory of Simulation and Control for Population Ecology in Xinyang Normal University (No. 201004) and Natural Science Foundation of the Education Department of Henan Province (No. 2009B1100200 and No. 2010A110017) First published online: 10 Feb 201

Modelling the Drugs Therapy for HIV Infection with Discrete-Time Delay

A discrete-time-delay differential mathematical model that described HIV infection of CD4+ T cells with drugs therapy is analyzed. The stability of the two equilibria and the existence of Hopf bifurcation at the positive equilibrium are investigated. Using the normal form theory and center manifold argument, the explicit formulas which determine the stability, the direction, and the period of bifurcating periodic solutions are derived. Numerical simulations are carried out to explain the mathematical conclusions

Predicting the trend of leptospirosis in China via a stochastic model with vector and environmental transmission

A stochastic model of leptospirosis with vector and environmental transmission is established in this paper. By mathematical analysis of the model, the threshold for eliminating the disease is obtained. The partial rank correlation coefficient was used to analyze the parameters that have a greater impact on disease elimination, and a sensitivity analysis was conducted on the parameters through numerical simulation. Further, combined with the data of leptospirosis case reports in China from 2003 to 2021, two parameter estimation methods, Least Squares method (LSM) and Markov Chain Monte Carlo-Metropolis Hastings method (MCMC-MH), are applied to estimate the important parameters of the model and the future trend of leptospirosis in China are predicted

Indoor Human Fall Detection Algorithm Based on Wireless Sensing

As the main health threat to the elderly living alone and performing indoor activities, falls have attracted great attention from institutions and society. Currently, fall detection systems are mainly based on wear sensors, environmental sensors, and computer vision, which need to be worn or require complex equipment construction. However, they have limitations and will interfere with the daily life of the elderly. On the basis of the indoor propagation theory of wireless signals, this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall behavior. The module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive, robustness, universality, and low price. The module combines digital signal processing technology and machine learning technology. This paper analyzes and processes the channel state information (CSI) data of wireless signals, and the local outlier factor algorithm is used to find the abnormal CSI sequence. The support vector machine and extreme gradient boosting algorithms are used for classification, recognition, and comparative research. Experimental results show that the average accuracy of fall detection based on wireless sensing is more than 90%. This work has important social significance in ensuring the safety of the elderly.Temple University. College of Science and TechnologyComputer and Information Science