Simulaciones de modelos estacionales de propagación del covid: estudio de caso en México

In this work we propose some mathematical models to simulate seasonality behaviorof Covid-19 spread; a periodic transmission rate is added to SEIR, SEIRS, SEIRS withvaccination (SEIRSV) ode systems and the models are fitted to reported Covid infectedhistorical data 2021 in Mexico. Numerical simulations reproduce the qualitative seasonalitybehavior of covid spread and provide an insight to develop strategies to prevent the diseasesspread. Nearly all discussed approaches show the possible appearance of a fourth covidwave in Mexico at the end of 2021. Our results suggest that it is mandatory to considerseasonal factors when planing intervention strategies.Key words: seir, reinfection, vaccination, periodic transmission rate, machinelearning, Pearson correlation, seasonality.Codes: 68U20, 92D30, 65D10,00A71.