Compartmental Epidemiological Models for Covid-19: Estimation, Goodness-of-Fit and Forecasting Epidemics
Keywords:Covid-19, Compartimental Epidemiological Models, Godness-of-fit, Mathematical Modelling
Compartmental Epidemiological Models have been widely used to predict epidemics in order to understand the mechanisms of transmission of infectious diseases worldwide. Such models are used when there is evidence of an initial exponential growth, which is usually convenient to be applied to assist in preventive measures and clinical decisions. However, the initial data may not reliably represent the transmission process due to several factors, including underreporting, asymptomatic cases or the inability of the health system to perform rapid tests. Thus, initial predictions may underestimate or overestimate the evolution of cases of infections, deaths and recoveries and, consequently, erroneously estimate the need for the health system. Therefore, this work carries out a study applying the main epidemiological compartmental models to illustrate the impact of these different models in characterizing the Covic-19 outbreak in the city of Parauapebas / PA - Brazil. Specifically, we present a criterion for selecting models based on the Mean Square Error (MSE) to assess the quality of fit and the impact on short and longterm epidemic predictions.