Kang Yun, Castillo-Chavez Carlos
Applied Sciences and Mathematics, Arizona State University, Mesa, AZ 85212, USA.
Mathematical, Computational and Modeling Sciences Center Arizona State University, Tempe, 85287-1904 School of Human Evolution and Social Changes and School of Sustainability Santa Fe Institute, Santa Fe, NM, 87501 Cornell University, Biological Statistics and Computational Biology, Ithaca, NY 14853 - 2601
Discrete Continuous Dyn Syst Ser B. 2014 Jan;19(1):89-130. doi: 10.3934/dcdsb.2014.19.89.
The study of the dynamics of human infectious disease using deterministic models is typically carried out under the assumption that a critical mass of individuals is available and involved in the transmission process. However, in the study of animal disease dynamics where demographic considerations often play a significant role, this assumption must be weakened. Models of the dynamics of animal populations often naturally assume that the presence of a minimal number of individuals is essential to avoid extinction. In the ecological literature, this a priori requirement is commonly incorporated as an . The focus here is on the study disease dynamics under the assumption that a critical mass of susceptible individuals is required to guarantee the population's survival. Specifically, the emphasis is on the study of the role of an Allee effect on a Susceptible-Infectious (SI) model where the possibility that susceptible and infected individuals reproduce, with the S-class the best fit. It is further assumed that infected individuals loose some of their ability to compete for resources, the cost imposed by the disease. These features are set in motion in as model as possible. They turn out to lead to a rich set of dynamical outcomes. This model supports the possibility of multi-stability (hysteresis), saddle node and Hopf bifurcations, and catastrophic events (disease-induced extinction). The analyses provide a full picture of the system under disease-free dynamics including disease-induced extinction and proceed to identify required conditions for disease persistence. We conclude that increases in (i) the maximum birth rate of a species, or (ii) in the relative reproductive ability of infected individuals, or (iii) in the competitive ability of a infected individuals at low density levels, or in (iv) the per-capita death rate (including disease-induced) of infected individuals, can stabilize the system (resulting in disease persistence). We further conclude that increases in (a) the Allee effect threshold, or (b) in disease transmission rates, or in (c) the competitive ability of infected individuals at high density levels, can destabilize the system, possibly leading to the eventual collapse of the population. The results obtained from the analyses of this model highlight the significant role that factors like an Allee effect may play on the survival and persistence of animal populations. Scientists involved in biological conservation and pest management or interested in finding sustainability solutions, may find these results of this study compelling enough to suggest additional focused research on the role of disease in the regulation and persistence of animal populations. The risk faced by endangered species may turn out to be a lot higher than initially thought.
使用确定性模型对人类传染病动态进行的研究通常是在这样的假设下进行的,即有足够数量的个体参与传播过程。然而,在动物疾病动态研究中,人口统计学因素往往起着重要作用,这一假设必须弱化。动物种群动态模型通常自然地假设,存在最少数量的个体对于避免灭绝至关重要。在生态学文献中,这一先验要求通常作为一个……被纳入。这里的重点是在需要有临界数量的易感个体以保证种群生存的假设下研究疾病动态。具体而言,重点是研究阿利效应在易感 - 感染(SI)模型中的作用,其中易感个体和感染个体都有可能繁殖,且S类最符合情况。进一步假设感染个体失去了一些竞争资源的能力,这是疾病造成的代价。这些特征在尽可能简单的模型中展现出来。结果发现它们会导致一系列丰富的动态结果。这个模型支持多稳定性(滞后现象)、鞍结分岔和霍普夫分岔以及灾难性事件(疾病导致的灭绝)的可能性。分析提供了包括疾病导致灭绝在内的无病动态下系统的全貌,并进而确定疾病持续存在所需的条件。我们得出结论,(i)物种最大出生率的增加,或(ii)感染个体相对繁殖能力的增加,或(iii)低密度水平下感染个体竞争能力的增加,或(iv)感染个体的人均死亡率(包括疾病导致的)的增加,都可以使系统稳定(导致疾病持续存在)。我们还得出结论,(a)阿利效应阈值的增加,或(b)疾病传播率的增加,或(c)高密度水平下感染个体竞争能力的增加,可以使系统不稳定,可能导致种群最终崩溃。从这个模型分析中获得的结果突出了诸如阿利效应等因素可能对动物种群生存和持续存在所起的重要作用。参与生物保护和害虫管理的科学家或对寻找可持续性解决方案感兴趣的人,可能会发现这项研究的这些结果极具说服力,足以建议对疾病在动物种群调节和持续存在中的作用进行更多有针对性的研究。濒危物种面临的风险可能比最初想象的要高得多。