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

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.