Growth forecast of the covid-19 with the gompertz function, Case study: Italy, spain, Hubei (China) and South Korea

Abstract

In this article,carry out an analysis on the growth and expansion models of the new virus outbreak belonging to the Coronavirus family called SARS-CoV-2 and associated with the clinical picture COVID-19. This outbreak of the disease was declared a pandemic by the World Health Organization (WHO) in March 2020, it is now affecting most countries in the world and its accelerated progress is a global concern. A non-linear growth model based on the Gompertz function was designed to characterize the serious pandemic impact in Asian and European countries: Spain, Italy, South Korea, and Hubei (China). The compilation of official data from each area on infected and deceased people until May 11, 2020, to verify the validity of the growth model in the calculated terms. With the obtained values, made a comparison by measuring the forecast errors, using the root indicators of the root mean square error (RMSE), the mean absolute percentage error (MAPE) and the regression coefficient index R2, which yielded highly accurate values of the predicted correlation for infected and dead of 0.99 on the dates considered. Verified the validation of the viral growth model of COVID-19 for these four countries and verified how the different measures taken to alleviate the pandemic have affected the final results of infected and dead countries, obtaining different growth coefficients that could be due to some exogenous factors (such as social, political and health factors, among others) that are difficult to measure and require qualitative methods and resources. The simple and well-structured model can be adapted to different propagation dynamics. Due to its direct and rapid implementation, the model could be useful for health managers and politicians for better decision-making in the control and prevention of this pandemic.