Loading...
3 results
Search Results
Now showing 1 - 3 of 3
- Homotopy analysis of explicit solutions in a chronic hepatitis C virus modelPublication . Duarte, Jorge; Januário, Cristina; Martins, NunoMathematical analysis of nonlinear models in epidemiology has generated a deep interest in gaining insights into the mechanisms that underlie hepatitis C virus (HCV) infections. In this article, we provide a study of a chronic HCV infection model with immune response, incorporating the effect of dendritic cells (DC) and cytotoxic T lymphocytes (CTL). Considering very recent developments in the literature related to the Homotopy Analysis Method (HAM), we calculate the explicit series solutions of the HCV model, focusing our analysis on a particular set of dynamical variables. An optimal homotopy analysis approach is used to improve the computational efficiency of HAM by means of appropriate values for a convergence control parameter, which greatly accelerates the convergence of the series solutions. The approximated analytical solutions, with the variation of a parameter representing the expansion rate of CTL, are used to compute density plots, which allow us to discuss additional dynamical features of the model.
- The role of noise in the tumor dynamics under chemotherapy treatmentPublication . Bashkirtseva, Irina; Ryashko, Lev; Duarte, Jorge; Seoane, Jesús M.; SANJUAN, MIGUEL A. F.Dynamical systems modeling tumor growth have been investigated to analyze the dynamics between tumor and healthy cells. Recent theoretical studies indicate that these interactions may lead to different dynamical outcomes under the effect of particular cancer therapies. In the present paper, we derive a system of nonlinear differential equations, in order to investigate solid tumors in vivo, taking into account the impact of chemotherapy on both tumor and healthy cells. We start by studying our model only in terms of deterministic dynamics under the variation of a drug concentration parameter. Later, with the introduction of noise, a stochastic model is used to analyze the impact of the unavoidable random fluctuations. As a result, new insights into noise-induced transitions are provided and illustrated in detail using techniques from dynamical systems and from the theory of stochastic processes.
- Controlling infectious diseases: the decisive phase effect on a seasonal vaccination strategyPublication . Duarte, Jorge; Januário, Cristina; Martins, Nuno; Seoane, Jesús M.; SANJUAN, MIGUEL A. F.The study of epidemiological systems has generated deep interest in exploring the dynamical complexity of common infectious diseases driven by seasonally varying contact rates. Mathematical modeling and field observations have shown that, under seasonal variation, the incidence rates of some endemic infectious diseases fluctuate dramatically and the dynamics is often characterized by chaotic oscillations in the absence of specific vaccination programs. In fact, the existence of chaotic behavior has been precisely stated in the literature as a noticeable feature in the dynamics of the classical Susceptible-Infected-Recovered (SIR) seasonally forced epidemic model. However, in the context of epidemiology, chaos is often regarded as an undesirable phenomenon associated with the unpredictability of infectious diseases. As a consequence, the problem of converting chaotic motions into regular motions becomes particularly relevant. In this article, we consider the so-called phase control method applied to the seasonally forced SIR epidemic model to suppress chaos. Interestingly, this method of controlling chaos has a clear meaning as a weak perturbation on a seasonal vaccination strategy. Numerical simulations show that the phase difference between the two periodic forces - contact rate and vaccination - plays a very important role in controlling chaos.