Modelling epidemics: a perspective on mathematical models and their use in the present SARS-CoV-2 epidemic

TL;DR

This paper reviews various mathematical models used during the SARS-CoV-2 pandemic, emphasizing the importance of biological plausibility for effective epidemic management and policy-making.

Contribution

It provides a comprehensive overview of classic and generalized epidemic models, highlighting the need for biologically feasible models in public health decision-making.

Findings

Classic Kermack-McKendrick models form the basis for many epidemic models.

Generalizations include contact structures and co-circulation of viruses.

Biologically sound models are crucial for effective epidemic control.

Abstract

In this work we look at several mathematical models that have been constructed during the present pandemic to address dfferent issues of importance to public health policies about epidemic scenarios and thier causes. We start by briefly reviewing the most basic properties of the classic Kermack-McKendrick models and then proceed to look at some generalizations and their applications to contact structures, cocirculation of viral infections, growth patterns of epidemic curves, characterization of probability distributions and passage times necessary to parametrize the compartments that are added to the basic Kermack-McKendrick model. All of these examples revolve around the idea that a system of differential equations constructed for an specifc epidemiological problem, has as central and main theoretical and conceptual support the epidemiological, medical and biological context that motivates its construction and analysis. Fitting differential models to data without a sound perspective on the biological feasibility of the mathematical model will provide an statistical significant fit but will also fall short of providing useful information for the management, mitigation and eventual control of the epidemic of SARS-CoV-2.