Modeling complex systems: A case study of compartmental models in epidemiology

TL;DR

This paper critically examines compartmental epidemic models, highlighting how their assumptions can limit the range of possible epidemic behaviors and emphasizing the importance of validating these assumptions in specific contexts.

Contribution

It provides a detailed analysis of the assumptions behind compartmental models and illustrates general modeling principles applicable beyond epidemiology.

Findings

Assumptions can constrain epidemic model outcomes.

Model validity depends on context-specific justification.

General principles of modeling are illustrated through case study.

Abstract

Compartmental epidemic models have been widely used for predicting the course of epidemics, from estimating the basic reproduction number to guiding intervention policies. Studies commonly acknowledge these models' assumptions but less often justify their validity in the specific context in which they are being used. Our purpose is not to argue for specific alternatives or modifications to compartmental models, but rather to show how assumptions can constrain model outcomes to a narrow portion of the wide landscape of potential epidemic behaviors. This concrete examination of well-known models also serves to illustrate general principles of modeling that can be applied in other contexts.