Multiscale systems immunology: mathematical and data-driven models of pathological immune dynamics

Immune processes during pathological conditions such as inflammation, acute and chronic infection, autoimmune disease, and cancer exhibit complex dynamics across interconnected biological scales. At the cellular level, intracellular signaling networks and interferon-stimulated gene (ISG) responses regulate virus replication, immune activation, and tumor cell survival. At the tissue scale, interactions among infected cells, cytotoxic T lymphocytes (CTLs), free virus, antibodies, and inflammatory mediators generate nonlinear feedback mechanisms that shape disease progression or resolution. At the population level, heterogeneity in immunity, vaccination coverage, and transmission dynamics determines epidemic spread and long-term immune landscapes. Mathematical modeling provides a rigorous framework to dissect these processes, by enabling mechanistic insight, quantitative analysis, and predictive understanding of immune-driven disease.The goal of this Research Topic is to advance theoretical and quantitative modeling of immune processes and systems across biological scales in pathological conditions, including inflammation, infection, and cancer. We aim to collect studies that develop, analyze, or apply mathematical frameworks at single or multiple scales to elucidate key mechanisms, regulatory factors, and feedback structures governing immune dynamics. Contributions may focus on intracellular signaling, tissue-level interactions, or population-level immunity-driven transmission, as well as integrative multiscale approaches. We particularly welcome work that combines mechanistic modeling with emerging data-driven strategies, including inference and machine learning, to enhance linkage to clinical and experimental results, as well as increase predictive capability, parameter identification, and quantitative understanding of immune-mediated disease.This Research Topic invites high-impact theoretical and quantitative studies that advance the systemic understanding of immune processes in pathological conditions across biological scales. Contributions may address single-scale systems or develop multiscale frameworks that couple intracellular, tissue, and population dynamics. Emerging computational approaches, including machine learning integrated with mechanistic modeling, are particularly encouraged.Topics of interest include:• Modeling intracellular virus replication and interactions with interferon-stimulated genes (ISGs).• Mechanistic models of acute and chronic infections elucidating mechanisms of immune activation, regulation, and persistence.• Disease-specific models of immune dysregulation in autoimmune diseases and cancer.• Population-level transmission models that explicitly incorporate immunological dynamics such as immunity, vaccination, and heterogeneity.• Modeling methods that advance integration of clinical and experimental data with mechanistic models. Topic editors: Anass Bouchnita, Vitaly Volpert Source: https://www.frontiersin.org/research-topics/78883/multiscale-systems-immunology-mathematical-and-data-driven-models-of-pathological-immune-dynamics