Journal of Biological Dynamics最新文献

Measles is a highly contagious and potentially fatal disease, despite the availability of effective immunizations. This study formulates a deterministic mathematical model to investigate the transmission dynamics of measles, with eight compartments representing different epidemiological states such as susceptible, vaccinated, exposed, infected, early-treated, delayed-treated, hospitalized, and recovered individuals. We use the Next Generation Matrix (NGN) approach to obtain the basic reproduction number ($R_0$) and examine local stability at the disease-free equilibrium (DFE). Sensitivity analysis with Partial Rank Correlation Coefficients (PRCC) identifies significant parameters influencing disease dynamics, such as vaccination rates, transmission rate, treatment timings, and disease-induced mortality rates. Simulation results show that delayed therapy has a limited effect on lowering the infected population, emphasizing the importance of immediate intervention. Early treatment considerably reduces the number of infected individuals, whereas improved recovery rates in hospitalized cases result in fewer hospitalizations. Vaccination is extremely successful, with increased rates significantly lowering the susceptible population while boosting the vaccinated population. Higher disease-related mortality rates reduce the afflicted population, stressing the importance of strong control methods. The transmission rate has a substantial impact on infection rates and hospitalizations, emphasizing the need for effective public health policies and healthcare capacity. The combined effect of immunization and early treatment provides useful information for optimizing control measures. This study emphasizes the need of quick and effective measures in managing measles outbreaks and serves as a platform for future research into improved public health methods.

This article proposes a dispersal strategy for infected individuals in a spatial susceptible-infected-susceptible (SIS) epidemic model. The presence of spatial heterogeneity and the movement of individuals play crucial roles in determining the persistence and eradication of infectious diseases. To capture these dynamics, we introduce a moving strategy called risk-induced dispersal (RID) for infected individuals in a continuous-time patch model of the SIS epidemic. First, we establish a continuous-time n-patch model and verify that the RID strategy is an effective approach for attaining a disease-free state. This is substantiated through simulations conducted on 7-patch models and analytical results derived from 2-patch models. Second, we extend our analysis by adapting the patch model into a diffusive epidemic model. This extension allows us to explore further the impact of the RID movement strategy on disease transmission and control. We validate our results through simulations, which provide the effects of the RID dispersal strategy.

In this paper, we consider a stochastic two-species predator-prey system with modified Leslie-Gower. Meanwhile, we assume that hunting cooperation occurs in the predators. By using Itô formula and constructing a proper Lyapunov function, we first show that there is a unique global positive solution for any given positive initial value. Furthermore, based on Chebyshev inequality, the stochastic ultimate boundedness and stochastic permanence are discussed. Then, under some conditions, we prove the persistence in mean and extinction of system. Finally, we verify our results by numerical simulations.

In this paper, a compartmental model on the co-infection of pneumonia and HIV/AIDS with optimal control strategies was formulated using the system of ordinary differential equations. Using qualitative methods, we have analysed the mono-infection and HIV/AIDS and pneumonia co-infection models. We have computed effective reproduction numbers by applying the next-generation matrix method, applying Castillo Chavez criteria the models disease-free equilibrium points global stabilities were shown, while we have used the Centre manifold criteria to determine that the pneumonia infection and pneumonia and HIV/AIDS co-infection exhibit the phenomenon of backward bifurcation whenever the corresponding effective reproduction number is less than unity. We carried out the numerical simulations to investigate the behaviour of the co-infection model solutions. Furthermore, we have investigated various optimal control strategies to predict the best control strategy to minimize and possibly to eradicate the HIV/AIDS and pneumonia co-infection from the community.

The basic reproduction number $R_0$ is one of the main parameters determining the spreading of an epidemic in a population of susceptible individuals. Wallinga and Lipsitch proposed a method for estimating $R_0$ using the Euler-Lotka equation, which requires the Laplace transform of the generation interval distribution. The determination of the generation time distribution is challenging, as the generation time is not directly observable. We prove upper and lower bounds on $R_0$ using only the first few moments of the generation interval distributions and study the sensitivity of the bounds to these parameters. The bounds do not require the exact shape of the generation interval distribution and give robust estimates of the $r-R_0$ relationship.

We study an avascular spherical solid tumour model with cell physiological age and resource constraints in vivo. We divide the tumour cells into three components: proliferating cells, quiescent cells and dead cells in necrotic core. We assume that the division rate of proliferating cells is nonlinear due to the nutritional and spatial constraints. The proportion of newborn tumour cells entering directly into quiescent state is considered, since this proportion can respond to the therapeutic effect of drug. We establish a nonlinear age-structured tumour cell population model. We investigate the existence and uniqueness of the model solution and explore the local and global stabilities of the tumour-free steady state. The existence and local stability of the tumour steady state are studied. Finally, some numerical simulations are performed to verify the theoretical results and to investigate the effects of different parameters on the model.

The adaptive immune system has two types of plasma cells (PC), long-lived plasma cells (LLPC) and short-lived plasma cells (SLPC), that differ in their lifespan. In this paper, we propose that LLPC is crucial to the clearance of viral particles in addition to reducing the viral basic reproduction number in secondary infections. We use a sequence of within-host mathematical models to show that, CD8 T cells, SLPC and memory B cells cannot achieve full viral clearance, and the viral load will reach a low positive equilibrium level because of a continuous replenishment of target cells. However, the presence of LLPC is crucial for viral clearance.

This paper concerns the invasion dynamics of the lattice pioneer-climax competition model with parameter regions in which the system is non-monotone. We estimate the spreading speeds and establish appropriate conditions under which the spreading speeds are linearly selected. Moreover, the existence of travelling waves is determined by constructing suitable upper and lower solutions. It shows that the spreading speed coincides with the minimum wave speed of travelling waves if the diffusion rate of the invasive species is larger or equal to that of the native species. Our results are new to estimate the spreading speed of non-monotone lattice pioneer-climax systems, and the techniques developed in this work can be used to study the invasion dynamics of the pioneer-climax system with interaction delays, which could extend the results in the literature. The analysis replies on the construction of auxiliary systems, upper and lower solutions, and the monotone dynamical system approach.

A population model of HIV that includes susceptible individuals not taking the pre-exposure prophylaxis (PrEP), susceptible individuals taking daily PrEP, and infected individuals is developed for casual partnerships, as well as monogamous and non-monogamous long-term partnerships. Reflecting the reality of prescription availability and usage in the U.S., the PrEP taking susceptible population is a mix of individuals designated by the CDC as high and low risk for acquiring HIV. The rate of infection for non-monogamous long-term partnerships with differential susceptibility is challenging to calculate and requires Markov chain theory to represent the movement between susceptible populations before infection. The parameters associated with PrEP initiation, suspension and adherence impact both the reproduction number of the model and the elasticity indices of the reproduction model. A multi-parameter analysis reveals that increasing adherence has the largest effect on decreasing the number of new infections.