  During the COVID-19 pandemic, community containment measures have been
implemented in different parts of the world. However, despite government
recommendations and mandates, a progressive increase in mobility was observed
in several sites. This phenomenon is often referred to as "quarantine fatigue".
Mathematical models have been used for more than a century to study the
dynamics of diseases spread. Since the start of the COVID-19 pandemic, a large
number of models have been developed to investigate different aspects of the
pandemic. The aim of the present work has been to design and explore a
mathematical model of SARS-CoV-2 spread with quarantine fatigue. A
deterministic model represented by a system of differential equations, based on
Susceptible-Infected-Recovered (SIR) dynamics, was developed. The model was
explored by means of computational simulations. The results obtained show that,
in some scenarios, after a first prevalence peak, fatigue can cause a second
peak. Thus, the dynamic behavior of the model suggests that fatigue may have
contributed to the production of the second peak of infected people observed in
different parts of the world between 2020 and early 2021. The explorations
performed also showed that the model is sensitive to infection rate and other
parameters related to propagation dynamics. The developed model is relatively
simple and has important limitations for performing accurate predictions in the
real world. However, our study highlights the importance of considering
quarantine fatigue in the management of the current COVID-19 pandemic, as well
as of possible future pandemics caused by other pathogens.
