Modeling Across-Scale Feedback of Pathogen Virulence, Host Immunity, and Disease Control

疾病建模和公共卫生目前面临的挑战是了解从宿主内到宿主间的感染尺度上的病原体动态。感染时的病毒和免疫反应动力学影响传播到其他宿主并反馈到人群免疫，所有这些都影响总体疾病负担和爆发轨迹。例如，登革热病毒（DENV）负担与宿主免疫有着错综复杂的联系；宿主体内预先存在的某些水平的抗体实际上可能会增加具有不同血清型的继发感染的严重程度。更好地了解免疫和流行病学的耦合动态对DENV的控制策略至关重要，最近关于疫苗接种是否会增加严重登革热感染的辩论突出了这一点。该项目开发了新的多尺度建模框架，包括动态分析、计算方法和数据拟合，以破译跨尺度的疾病结果。考虑了三个案例研究：(i)预先存在的抗体对DENV严重程度和疫苗接种的作用；（ii）口蹄疫病毒（FMDV）病原体持久性和宿主免疫的反馈；（三）载体内病毒动力学和接种量（感染剂量）对媒介传播疾病流行和控制的影响。通过结合这些研究，将评估跨尺度反馈对疾病负担和宿主免疫的影响，并为疾病控制和动力学提供见解。这项工作将为本科生和研究生在这一新兴的跨学科科学领域提供先进的训练。感染尺度的相互联系对描述复杂病毒至关重要，这在数学/计算方面提出了重要的挑战。虽然多尺度模型已被应用于传染病，但一个主要的限制是缺乏流行病学和免疫学尺度的双向依赖。在本研究中，将人群范围内的流行病模型与个体感染动力学相结合，以检查多种菌株的感染，免疫的减弱/增强，媒介能力以及疾病控制。将制定一类新的抗体结构免疫流行病学微分方程模型，以描述可变宿主免疫和感染轨迹之间的联系。正在开发的方法包括创新的平衡、稳定性和持久性分析，以及多尺度模拟方法。此外，将利用多尺度设置，拟合宿主/媒介和流行病学数据，为模型提供信息和验证。对于DENV，将与生物学家合作，将从感染期间的病毒免疫动力学到流行病发生率等几个数据集结合起来，以提高模型的能力和预测能力。该项目由数学科学部（DMS）的数学生物学计划和刺激竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，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。

A current challenge for disease modeling and public health is to understand pathogen dynamics across infection scales from within-host to between-host. Viral and immune response kinetics upon infection impact transmission to other hosts and feedback into population-wide immunity, all of which influence the overall disease burden and trajectory of an outbreak. For example, dengue virus (DENV) burden and host immunity are intricately linked; certain levels of pre-existent antibodies in a host may actually enhance severity of secondary infection with a distinct serotype. A better understanding of the coupled immunological and epidemiological dynamics is critical for control strategies against DENV, highlighted by recent debate over whether vaccination may increase severe dengue infection. This project develops novel multi-scale modeling frameworks with dynamical analysis, computational methods, and data fitting for deciphering disease outcomes across scales. Three case studies are considered: (i) the role of pre-existent antibodies on DENV severity and vaccination; (ii) feedbacks in pathogen persistence and host immunity in Foot and Mouth Disease Virus (FMDV); and (iii) effect of in-vector viral kinetics and inoculum (infection dose) on vector-borne disease epidemics and control. By combining these studies, across-scale feedbacks will be assessed for their influence on disease burden and host immunity, and to provide insights on disease control and dynamics. This work will provide undergraduate and graduate students with advanced training in this emerging interdisciplinary scientific field.The interconnection of infection scales, vital for describing complex viruses, poses important mathematical/computational challenges. While multi-scale models have been applied to infectious diseases, a major limitation has been lack of bidirectional dependence of epidemiological and immunological scales. In this research, population-wide epidemic models are unified with individual infection dynamics to examine infection by multiple strains, waning/boosting of immunity, and vector competence, along with disease control. A new class of antibody-structured immuno-epidemiological differential equation models will be formulated to depict connections between variable host immunity and infection trajectories. Methods under development include innovative equilibrium, stability, and persistence analysis, along with multi-scale simulation approaches. Moreover, the multi-scale setting will be utilized by fitting within-host/vector and epidemiological data to inform and validate the models. For DENV, several datasets, ranging from virus-immune dynamics during infection to epidemic incidence, will be combined to improve power and prediction of the models, in collaboration with biologists. This project is jointly funded by the Mathematical Biology Program of the Division of Mathematical Sciences (DMS) and the Established Program to Stimulate Competitive Research (EPSCoR).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.