Incorporating Immunity into Epidemiological Infectious Disease Models: Bridging Multiple Scales

新出现的和正在发生的传染病暴发严重影响人口的健康和经济稳定。由于个体的差异性，特别是在其对各种感染的保护水平方面，理解和预测此类疫情的过程具有挑战性。这项工作将涉及三种全球关注的传染病：登革热、疟疾和百日咳。简单的数学模型已经成功地描述了简单传染病的流行并提出了干预策略。然而，更复杂的疾病需要开发和分析更复杂的模型，特别是连接多个尺度-生物体，时间和空间。新的模型和定量工具将提供对观察到的暴发模式的原因的深入了解，并指导对抗这些复杂疾病的战略。这项工作将为本科生和研究生提供跨学科的培训，工作成果将通过开展传染病外联活动和同行评审的出版物和研讨会向广大受众传播。了解人群中可变免疫力的作用对于准确确定流行病的动态以及有效减缓和阻止其传播至关重要。这项工作包括开发、分析和模拟具有个体宿主免疫反应可变性的多尺度模型。详细的宿主内免疫动态将纳入登革热、疟疾和百日咳的人口流行病学模型，以评价人口一级的疾病动态。这项工作的目的有三个方面：确定宿主内病毒和免疫变异性对登革热流行病学动态的作用;确定适应性抗原特异性免疫对疟疾流行和传播潜力的作用;建立免疫力减弱和增强的模型，以确定百日咳的最佳初次接种和加强剂量时机。这项工作进一步的数学理论的多尺度系统的微分方程的动机，通过纳入宿主内异质性的人口模型。它将建立在微分方程和非线性动力系统的数学理论基础上。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Emerging and on-going infectious disease outbreaks significantly impact the health and economic stability of a population. Understanding and predicting the course of such outbreaks is challenging due to the variability of individuals, particularly with respect to their levels of protection against various infections. This work will address three infectious diseases of worldwide interest: dengue, malaria and whooping cough. Simple mathematical models have been successful at describing the epidemics of and suggesting intervention strategies for simple infectious disease. More complicated diseases, however, require the development and analysis of more complicated models, particularly linking multiple scales - organismal, temporal, and spatial. The novel models and quantitative tools will provide insight into the reason for observed patterns of outbreaks as well as guide strategies for combating these complicated diseases. This work will provide interdisciplinary training for undergraduate and graduate students, and the results of the work will be disseminated to a broad audience through the development of infectious disease based outreach activities and peer-reviewed publications and seminars.Understanding the role of variable immunity within populations is crucial to accurately determining the dynamics of epidemics and to effectively slowing and stopping their spread. This work includes the development, analysis, and simulation of multi-scale models with variability of the individual host immune response. Detailed within-host immune dynamics will be incorporated into population-level epidemiological models of dengue, malaria and pertussis (whooping cough) to evaluate population-level disease dynamics. The aims of this work are three fold: determine the role of within-host viral and immune variability on epidemiological dynamics of dengue; determine the role of adaptive antigen-specific immunity on malaria prevalence and transmission potential; and develop a model of waning and boosting of immunity to determine optimal primary vaccination and booster dose timing for pertussis. This work furthers the mathematical theory of multi-scale systems of differential equations motivated through the incorporation of within-host heterogeneity in population models. It will build upon mathematical theory from differential equations and non-linear dynamical systems. The main challenge will be analyses of non-linear systems with variable time scales and large dimensionality.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.