Zhilan Feng
Purdue University
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Publication
Featured researches published by Zhilan Feng.
Bellman Prize in Mathematical Biosciences | 1998
Carlos Castillo-Chavez; Zhilan Feng
This article focuses on the study of an age-structure model for the disease transmission dynamics of tuberculosis in populations that are subjected to a vaccination program. We first show that the infection-free steady state is globally stable if the basic reproductive number R0 is below one, and that an endemic steady state exists when the reproductive number in the presence of vaccine is above one. We then apply the theoretical results to vaccination policies to determine the optimal age or ages at which an individual should be vaccinated. It is shown that the optimal strategies can be either one- or two-age strategies.
Siam Journal on Applied Mathematics | 2007
Libin Rong; Zhilan Feng; Alan S. Perelson
Various classes of antiretroviral drugs are used to treat HIV infection, and they target different stages of the viral life cycle. Age-structured models can be employed to study the impact of these drugs on viral dynamics. We consider two models with age-of-infection and combination therapies involving reverse transcriptase, protease, and entry/fusion inhibitors. The reproductive number R is obtained, and a detailed stability analysis is provided for each model. Interestingly, we find in the age-structured model a different functional dependence of R onRT , the efficacy of a reverse transcriptase inhibitor, than that found previously in nonage-structured models, which has significant implications in predicting the effects of drug therapy. The influence of drug therapy on the within-host viral fitness and the possible development of drug-resistant strains are also discussed. Numerical simulations are performed to study the dynamical behavior of solutions of the models, and the effects of different combinations of antiretroviral drugs on viral dynamics are compared.
Siam Journal on Applied Mathematics | 2005
M. Nuño; Zhilan Feng; Maia Martcheva; Carlos Castillo-Chavez
The time evolution of the influenza A virus is linked to a nonfixed landscape driven by interactions between hosts and competing influenza strains. Herd-immunity, cross-immunity, and age-structure are among the factors that have been shown to support strain coexistence and/or disease oscillations. In this study, we put two influenza strains under various levels of (interference) competition. We establish that cross-immunity and host isolation lead to periodic epidemic outbreaks (sustained oscillations) in this multistrain system. We compute the isolation reproductive number for each strain (
Journal of Dynamics and Differential Equations | 2001
Zhilan Feng; Wenzhang Huang; Carlos Castillo-Chavez
\Re_i
Siam Journal on Applied Mathematics | 2002
Zhilan Feng; M. Iannelli; Fabio A. Milner
) independently, as well as for the full system (
Bellman Prize in Mathematical Biosciences | 1995
Zhilan Feng; Horst R. Thieme
\Re_q
Proceedings of the Royal Society of London B: Biological Sciences | 2007
Murray E. Alexander; Christopher Bowman; Zhilan Feng; Michael Gardam; Seyed M. Moghadas; Gergely Röst; Jianhong Wu; Ping Yan
), and show that when
Siam Journal on Applied Mathematics | 2000
Zhilan Feng; Horst R. Thieme
\Re_q < 1
The American Naturalist | 2005
Yssa D. DeWoody; Zhilan Feng; Robert K. Swihart
, both strains die out. Subthreshold coexistence driven by cross-immunity is possible even when the isolation reproductive number of one strain is below 1. Conditions that guarantee a winning type or coexistence are established in general. Oscillatory coexistence is established via Hopf bifurcation theory and confirmed via n...
Bulletin of Mathematical Biology | 2010
Zhipeng Qiu; Zhilan Feng
The qualitative behaviors of a system of ordinary differential equations and a system of differential-integral equations, which model the dynamics of disease transmission for tuberculosis (TB), have been studied. It has been shown that the dynamics of both models are governed by a reproductive number. All solutions converge to the origin (the disease-free equilibrium) when this reproductive number is less than or equal to the critical value one. The disease-free equilibrium is unstable and there exists a unique positive (endemic) equilibrium if the reproductive number exceeds one. Moreover, the positive equilibrium is stable. Our results show that the qualitative behaviors predicted by the model with arbitrarily distributed latent stage are similar to those given by the TB model with an exponentially distributed period of latency.
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National Center for Immunization and Respiratory Diseases
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