ABSTRACT
The COVID-19 Pandemic has been one of the most significant health problems in the world. Several academic studies focus on health consequences. However, only a few studies have paid attention to analyzing government strategies as general public guidelines. In this work, we use a Susceptible-Infected-Recovered-Deceased (SIRD) model to assess infection rate, mortality rate, and the effects of the Mexican government intervention during the three waves of the COVID-19 pandemic. We carry out Bayesian inferences on the proposed model using a Robust Adaptive Metropolis (RAM) algorithm. Essentially, the proposed methodology allows appreciating the effects of quarantine on the three pandemic wave's mortality rate. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.