Mathematical modeling and simulation of the dynamics of the SARS-Cov-2 virus - Romero Romero, Ray Anthony (2021)
By the end of 2019 a novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appeared by the first time in Wuhan, China. Its fast spread around the world led in March 2020 to the World Health Organization (WHO) to declare the SARS-Cov-2 virus a pandemic. Epidemics and pandemics are not new phenomenons in human history, and mathematical models have been used to describe the dynamics of this infectious diseases. In this document we present a SEIR generalized model with no-demographic constraints. In this model we add asymptomatic, asymptomatic recovered, isolated and dead classes. We perform simulations in 4 data-driven contact networks: workplaces, households, general community and agglomeration places. The studies of Cuevas et al., Peng et al. and Quang et al. are relevant for this work. We decided to consider all parameters as constants with exception of the cure and mortality rate, nevertheless in future works these parameters will be modeled as functions of time for more accurate predictions. In particular, we focus in the behavior of asymptomatic, infected and dead classes in each one of the data-driven networks. We notice that the curves change in terms of which one of them reaches faster the peak of the curve. Finally, we compute the reproduction number, R0, using the next-generation approach for each one of the networks. Here, for every network we obtain R0 > 1 which agrees with the theory. It is important to mention that the lack of transparency in the data by govern makes hard to build this kind of models.