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The logistic equation is ubiquitous in applied mathematics as a minimal model of saturating growth. Here, we examine a broad generalisation of the logistic growth model to discretely structured populations, motivated by examples that range from the ageing of individuals in a species to immune cell exhaustion by cancerous tissue. Through exploration of a range of concrete examples and a general analysis of polynomial kinetics, we derive necessary and sufficient conditions for the dependence of the kinetics on structure to result in closed, low-dimensional moment equations that are exact. Further, we showcase how coarse-grained moment information can be used to elucidate the details of structured dynamics, with immediate potential for model selection and hypothesis testing. This paper belongs to the special collection: Problems, Progress and Perspectives in Mathematical and Computational Biology.

Original publication

DOI

10.1007/s11538-025-01446-w

Type

Journal article

Journal

Bulletin of mathematical biology

Publication Date

05/2025

Volume

87

Addresses

Department of Mathematics, University College London, Gordon Street, London, WC1H 0AY, UK. benjamin.walker@ucl.ac.uk.

Keywords

Animals, Humans, Neoplasms, Logistic Models, Computational Biology, Aging, Kinetics, Models, Biological, Computer Simulation, Mathematical Concepts