Dynamical crises, multistability and the influence of the duration of immunity in a seasonally-forced model of disease transmission.
Dynamical crises, multistability and the influence of the duration of immunity in a seasonally-forced model of disease transmission.
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DOI：
10.1186/1742-4682-11-43
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发表时间：
2014-10-04
影响因子：
--
通讯作者：
McCaw JM
中科院分区：
文献类型：
--
作者：
Dafilis MP;Frascoli F;McVernon J;Heffernan JM;McCaw JM
然而，由于传播的季节性变化和人口免疫状况之间的相互作用，使人口对传染病更具弹性的非常成功的战略，如儿童疫苗接种计划，可能会导致不可预测的结果。受百日咳等疾病研究的启发，我们引入了一个季节性强制的免疫力减弱和增强的疾病传播的易感染-感染-恢复模型。我们研究了系统的动力学性质，使用数值模拟和分岔技术相结合，特别注意的初始条件空间的属性。我们发现，高度不可预测的行为可以触发生物相关的模型参数，如免疫力的持续时间的变化。在特定的系统中，我们分析-以前在文献中使用的研究百日咳动力学-我们确定存在一个初始条件景观包含三个共存的吸引子。因此，很难预测该系统对干扰人口免疫力的干预措施（例如疫苗接种“追赶”运动）的反应。鉴于越来越多地使用模型来为疫苗引进和调度以及传染病干预政策提供信息，我们的研究结果强调了彻底调查这些模型的动态特性以确定关键不确定性领域的重要性。我们的研究结果表明，捕获生物复杂性和利用数学简单模型之间的经常陈述的紧张关系可能比一般建议的更微妙。简单的动力学模型，特别是那些包含强迫项的模型，可以产生令人难以置信的复杂行为。
Highly successful strategies to make populations more resilient to infectious diseases, such as childhood vaccinations programs, may nonetheless lead to unpredictable outcomes due to the interplay between seasonal variations in transmission and a population’s immune status. Motivated by the study of diseases such as pertussis we introduce a seasonally-forced susceptible-infectious-recovered model of disease transmission with waning and boosting of immunity. We study the system’s dynamical properties using a combination of numerical simulations and bifurcation techniques, paying particular attention to the properties of the initial condition space. We find that highly unpredictable behaviour can be triggered by changes in biologically relevant model parameters such as the duration of immunity. In the particular system we analyse — previously used in the literature to study pertussis dynamics — we identify the presence of an initial-condition landscape containing three coexisting attractors. The system’s response to interventions which perturb population immunity (e.g. vaccination "catch-up" campaigns) is therefore difficult to predict. Given the increasing use of models to inform policy decisions regarding vaccine introduction and scheduling and infectious diseases intervention policy more generally, our findings highlight the importance of thoroughly investigating the dynamical properties of those models to identify key areas of uncertainty. Our findings suggest that the often stated tension between capturing biological complexity and utilising mathematically simple models is perhaps more nuanced than generally suggested. Simple dynamical models, particularly those which include forcing terms, can give rise to incredibly complex behaviour.
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影响因子：
4
作者：
Kamo, M;Sasaki, A
通讯作者：
Sasaki, A
影响因子：
--
作者：
Campbell, Helen;Andrews, Nick;Miller, Elizabeth
通讯作者：
Miller, Elizabeth
DOI：
10.1098/rspa.2003.1183
发表时间：
2004-02-08
影响因子：
3.5
作者：
Gottwald, GA;Melbourne, I
通讯作者：
Melbourne, I
影响因子：
2.9
作者：
ARECCHI, FT;BADII, R;POLITI, A
通讯作者：
POLITI, A
影响因子：
1.4
作者：
ARON, JL
通讯作者：
ARON, JL