Heterogeneously Structured Compartmental Models of Epidemiological Systems: From Individual‐Level Processes to Population‐Scale Dynamics

ABSTRACT We develop a general modeling framework for compartmental epidemiological systems structured by continuous variables which are linked to the levels of expression of compartment‐specific traits. We start by formulating an individual‐based model that describes the dynamics of single individuals in terms of stochastic processes. Then, we formally derive: (i) the mesoscopic counterpart of this model, which is formulated as a system of integrodifferential equations for the distributions of individuals over the structuring‐variable domains of the different compartments; (ii) the corresponding macroscopic model, which takes the form of a system of ordinary differential equations for the fractions of individuals in the different compartments and the mean levels of expression of the traits represented by the structuring variables. We employ a reduced version of the macroscopic model to obtain a general formula for the basic reproduction number, , in terms of key parameters and functions of the underlying microscopic model, so as to illustrate how such a modeling framework makes it possible to draw connections between fundamental individual‐level processes and population‐scale dynamics. Finally, we apply the modeling framework to case studies based on classical compartmental epidemiological systems, for each of which we report on Monte Carlo simulations of the individual‐based model as well as on analytical results and numerical solutions of the macroscopic model.

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Publication Details

Journal
Studies in Applied Mathematics
Published
2025-08-01
DOI
https://doi.org/10.1111/sapm.70091
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.37
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article

Heterogeneously Structured Compartmental Models of Epidemiological Systems: From Individual‐Level Processes to Population‐Scale Dynamics

Tommaso Lorenzi, Emanuele Bernardi, Andrea Tosin, Mattia Sensi
1 citations
Studies in Applied Mathematics
COVID-19 epidemiological studies
1.37
article

Heterogeneously Structured Compartmental Models of Epidemiological Systems: From Individual‐Level Processes to Population‐Scale Dynamics

Tommaso Lorenzi, Emanuele Bernardi, Andrea Tosin, Mattia Sensi
article en
1 citations

Abstract

ABSTRACT We develop a general modeling framework for compartmental epidemiological systems structured by continuous variables which are linked to the levels of expression of compartment‐specific traits. We start by formulating an individual‐based model that describes the dynamics of single individuals in terms of stochastic processes. Then, we formally derive: (i) the mesoscopic counterpart of this model, which is formulated as a system of integrodifferential equations for the distributions of individuals over the structuring‐variable domains of the different compartments; (ii) the corresponding macroscopic model, which takes the form of a system of ordinary differential equations for the fractions of individuals in the different compartments and the mean levels of expression of the traits represented by the structuring variables. We employ a reduced version of the macroscopic model to obtain a general formula for the basic reproduction number, , in terms of key parameters and functions of the underlying microscopic model, so as to illustrate how such a modeling framework makes it possible to draw connections between fundamental individual‐level processes and population‐scale dynamics. Finally, we apply the modeling framework to case studies based on classical compartmental epidemiological systems, for each of which we report on Monte Carlo simulations of the individual‐based model as well as on analytical results and numerical solutions of the macroscopic model.

Studies in Applied MathematicsVol. 155(2)
Politecnico di Torino (IT)
Openalex Percentile: Top 18%
COVID-19 epidemiological studies
1.37
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