A review of matrix SIR Arino epidemic models

TL;DR

This paper reviews matrix SIR epidemic models, emphasizing their fundamental formulas for the basic reproduction number and first integrals, and introduces a self-contained reference for these models, including extensions with multiple susceptible classes.

Contribution

It provides a comprehensive, self-contained overview of matrix SIR epidemic models, clarifies their fundamental properties, and introduces the SIR-PH variant with probabilistic interpretation.

Findings

Explicit formulas for R and first integrals in matrix SIR models

Introduction of the SIR-PH model with probabilistic interpretation

Potential for approximate control policies based on derived formulas

Abstract

Many of the models used nowadays in mathematical epidemiology, in particular in COVID-19 research, belong to a certain sub-class of compartmental models whose classes may be divided into three "(x, y, z)" groups, which we will call respectively "susceptible/entrance, diseased, and output" (in the classic SIR case, there is only one class of each type). Roughly, the ODE dynamics of these models contain only linear terms, with the exception of products between x and y terms. It has long been noticed that the basic reproduction number R has a very simple formula (3.3) in terms of the matrices which define the model, and an explicit first integral formula (3.8) is also available. These results can be traced back at least to [ABvdD+07] and [Fen07], respectively, and may be viewed as the "basic laws of SIR-type epidemics"; however many papers continue to reprove them in particular instances (by the next-generation matrix method or by direct computations, which are unnecessary). This motivated us to redraw the attention to these basic laws and provide a self-contained reference of related formulas for (x, y, z) models. We propose to rebaptize the class to which they apply as matrix SIR epidemic models, abbreviated as SYR, to emphasize the similarity to the classic SIR case. For the case of one susceptible class, we propose to use the name SIR-PH, due to a simple probabilistic interpretation as SIR models where the exponential infection time has been replaced by a PH-type distribution. We note that to each SIR-PH model, one may associate a scalar quantity Y(t) which satisfies "classic SIR relations", see (3.8). In the case of several susceptible classes, this generalizes to (5.10); in a future paper, we will show that (3.8), (5.10) may be used to obtain approximate control policies which compare well with the optimal control of the original model.