Biomedical subjects

Yunxin Huang

Publications and source records attributed to Yunxin Huang.

4 recordsLinked to original sources

PubMed2005

The dynamical implications of disease interference: correlations and coexistence.

Ecological interference between unrelated diseases, caused by the temporary or permanent removal of individuals susceptible to one disease following infection with another, might be an important mechanism underlying epidemics. In this paper, we explore the potential dynamic consequences of interference by analyzing a two-disease model. By studying the stability domain of the model's equilibria, we find that the stable region of the two-disease endemic state becomes increasingly smaller as the strength of interference (largely determined by the disease-induced mortality) increases. When seasonal changes are included in the transmission rates, the bifurcation structure of the model's periodic cycles reveals that when the two diseases have similar mean transmission rates, multiple attractors in which the two diseases are strongly correlated can coexist, and that when the two diseases have very different mean transmission rates, the one with higher mean transmission rate may determine the dynamics of the system, with the other infection mimicking the behavior. We conclude that ecological interference can have important effects on the dynamical pattern of interacting diseases, the extent of which is determined by the epidemiological features of the diseases, their mean transmission rates in particular.

Disease Transmission, Infectious↗

PubMed2005

How do cross-migration models arise?

In this paper we present a general method to derive spatio-temporal population models mechanistically. We consider a system of multiple species living in a patchy habitat in which the local population of each species consists of some behavioural groups. We then formulate a continuous-time model where a small positive parameter is present, measuring the time scale of behavioural transitions relative to that of giving birth, death and migration among patches. By the singular perturbation method the model is reduced to a lower dimensional one in which the migration terms are, in general, nonlinear and related to the reaction terms describing the local dynamics. Two examples demonstrating the emergence of cross-migration models, i.e., the models in which the per-capita migration rate of one species depends on the density of some other species, are given.

Animal Migration↗

PubMed2004

Double-Jump migration and diffusive instability.

In order to look into the stability consequences of a particular migration process in which individuals choose to settle, we formulated a continuous-time multi-species multi-patch model in which individuals migrate by one or two instantaneous jumps while making the second jump with a certain probability that possibly depends on the conditions at the end point of the first jump. It turned out that a second jump has some quantitative effects on diffusive instability even when it occurs in the absence of density-dependent mechanisms. When a second jump happens as a natural interspecific response of individuals, and such a response is sufficiently strong, it has crucial effects on diffusive instability: it leads to diffusive instability in the case of competitive interactions, whereas it annihilates diffusive instability in the case of prey-predator interactions. We demonstrated these results in the context of two specific examples.

Animals↗

PubMed2003

Interspecific influence on mobility and Turing instability.

In this paper we formulate a multi-patch multi-species model in which the per-capita emigration rate of one species depends on the density of some other species. We then focus on Turing instability to examine if and when this cross-emigration response has crucial effects. We find that the type of interaction matters greatly. In the case of competition a cross-emigration response promotes pattern formation by exercising a destabilizing influence; in particular, it may lead to diffusive instability provided that the response is sufficiently strong, which contrasts sharply with the well-known fact that the standard competition system does not exhibit Turing instability. In the case of prey-predator or activator-inhibitor interaction it acts against pattern formation by exerting a stabilizing effect; in particular, the diffusive instability, even though it may happen in a standard system, never occurs when the response is sufficiently strong. We conclude that the cross-emigration response is an important factor that should not be ignored when pattern formation is the issue.

Animals↗