Ponente
Descripción
Tuberculosis remains one of the leading infectious diseases worldwide, yet the biological events occurring during the first days following infection are still incompletely represented in most mathematical models. Classical tuberculosis models have primarily focused on granuloma formation and adaptive immunity, whereas the early innate immune response has received comparatively less attention (Ibarguen-Mondragón, E. & Cuesta, L. preprint, ,2025). Since the outcome of infection is largely determined during these initial stages, developing mathematical models that explicitly represent the underlying innate immune mechanisms is essential for understanding disease progression within the host, Ibarguen-Mondragón & Cuesta (2025).
In this work, we propose a biologically grounded mathematical model describing the cellular dynamics of the innate immune response during the early stage of Mycobacterium tuberculosis infection. The model explicitly represents the interactions among resident alveolar macrophages (infected and non-infected), monocyte-derived macrophages (infected and non-infected), immature, infected and antigen-bearing dendritic cells, neutrophils (infected and non-infected), circulating monocytes, and intracellular and extracellular bacterial populations. Unlike classical tuberculosis models, cytokines and chemokines are not introduced as independent dynamical variables. Instead, their regulatory effects on recruitment, differentiation, activation, migration and antimicrobial activity are incorporated through biologically interpretable effective parameters, reducing model complexity while preserving the principal immunological mechanisms (Marino, S. & Kirschner, D.E., J. Theor. Biol. 227, 463–486, 2004).
The mathematical formulation follows a multiscale biological methodology in which each differential equation is derived directly from experimentally supported cellular processes, allowing nonlinear functional responses to be associated with identifiable biological interactions. This strategy provides a transparent connection between immunological knowledge and mathematical structure, facilitating future parameter estimation, sensitivity analysis and model extensión.
The proposed model constitutes a general framework for studying the early establishment of tuberculosis infection and provides a foundation for future mathematical analyses, numerical simulations and multiscale extensions incorporating bacterial virulence and adaptive immunity.