Dynamics of epidemics: Impact of easing restrictions and control of infection spread

During an infectious disease outbreak, mathematical models and computational simulations are essential tools to characterize the epidemic dynamics and aid in design public health policies. Using these tools, we provide an overview of the possible scenarios for the COVID-19 pandemic in the phase of easing restrictions used to reopen the economy and society. To investigate the dynamics of this outbreak, we consider a deterministic compartmental model (SEIR model) with an additional parameter to simulate the restrictions. In general, as a consequence of easing restrictions, we obtain scenarios characterized by high spikes of infections indicating significant acceleration of the spreading disease. Finally, we show how such undesirable scenarios could be avoided by a control strategy of successive partial easing restrictions, namely, we tailor a successive sequence of the additional parameter to prevent spikes in phases of low rate of transmissibility. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

Mathematical models and computational simulations are essential tools during infectious disease outbreaks to characterize epidemic dynamics and design public health policies. The COVID-19 pandemic may face scenarios characterized by high spikes of infections due to easing restrictions, but these undesirable scenarios could be avoided by a control strategy of successive partial easing restrictions.