COVID-19 in Italy: Is the Mortality Analysis a Way to Estimate How the Epidemic Lasts?

Abstract

When an epidemic breaks out, many health, economic, social, and political problems arise that require a prompt and effective solution. It would be useful to obtain all information about the virus, including epidemiological ones, as soon as possible. In a previous study of our group, the analysis of the positive-alive was proposed to estimate the epidemic duration. It was stated that every epidemic ends when the number of positive-alive (=infected-healed-dead) glides toward zero. In fact, if with the contagion everyone can enter the epidemic phenomenon, only by healing or dying can they get out of it. In this work, a different biomathematical model is proposed. A necessary condition for the epidemic to be resolved is that the mortality reaches the asymptotic value, from there, remains stable. At that time, the number of positive-alive must also be close to zero. This model seems to allow us to interpret the entire development of the epidemic and highlight its phases. It is also more appropriate than the previous one, especially when the spread of the infection is so rapid that the increase in live positives is staggering.

An Epidemiological Analysis for Assessing and Evaluating COVID-19 Based on Data Analytics in Latin American Countries

“…Studies into different aspects of epidemics is being conducted by numerous scientists, each striving to provide helpful insights that may benefit mankind. These studies employ a variety of methodologies, with some relying on epidemic models [11,12], while others predominantly use statistical and mathematical methods, as in [13], where the authors applied mathematical models to analyze and predict the timeline and phases of an epidemic, specifically focusing on COVID-19 in Italy. In addition, control theory [14] has been applied to epidemic models to derive optimal strategies for easing restrictive measures, as showcased in [15].…”

Inference Based on the Stochastic Expectation Maximization Algorithm in a Kumaraswamy Model with an Application to COVID-19 Cases in Chile

“…The impact of the pandemic extended beyond public health, affecting aspects such as the economy and gross domestic product, especially in Latin America [41]. Different models have proven to be relevant in forecasting epidemic diseases, and various methodologies have been employed to gain insights into diverse aspects of epidemics around the world [42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60].…”