Analysis of an epidemic model considering the effects of negative feedback

Este trabajo tiene como objetivo estudiar el comportamiento dinámico de un modelo SIR epidemiológico (Susceptible-Infectado-Removido) modificado mediante la introducción de la retroalimentación negativa y una intervención no farmacéutico.

Epidemics, due to their dynamic nature, have a basic mathematical modeling that becomes more complex as more characteristic factors of each disease are added. There are also factors external to the disease that influence its incidence; for example, prejudices about vaccination campaigns (negative feedback) ¿such as mistrust of the human papillomavirus (HPV) vaccine ¿ often caused by misinformation. In this work, we propose and analyze an epidemic model in delayed differential equations that defines the information index function and the effect of negative feedback on the infestation parameter (incidence). The mathematical and simulation results will provide us with the various scenarios of the dynamics of a disease and will help us to show the importance, for example, of vaccination against myths or misinformation about it, in order to promote a healthy country conscious public. This work will take into account an application of the model under study for the COVID-19 pandemic, given that the model is basic and serves to answer some questions about the spread of SARS-CoV-2.

La reaccion del público ante las intervenciones de los sistemas de Salud, cuando se presentan pandemias, influye en la propagación de las mismas. La matemática puede mostrarnos los diferentes escenarios de ocurrencia de este fenómeno.

Se logra establecer las condiciones sobre los parametros, que intervienen en la dinámica de las epidemias,