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Diseño de un método analítico para predicción de la cuarta ola de la pandemia de Covid-19 en el Atlántico

Authors: Castellanos, Miguel Ángel; Caro, Angie Paulet; Restrepo, Valeria Carolina;

Diseño de un método analítico para predicción de la cuarta ola de la pandemia de Covid-19 en el Atlántico

Abstract

El proyecto pretende desarrollar un algoritmo que sea capaz de pronosticar la cuarta ola de la pandemia covid-19 en el atlántico , dar apoyo a los conocimientos algorítmicos de alto rendimiento y a un conjunto de modelos matemáticos que permitan evaluar por medio de variables especificas junto con datos actuales de contagios el comportamiento de lo que se conoce como el cuarto pico de la pandemia, el cual es denominado como un momento de curva ascendente donde va aumentando la cantidad de contagios. Y En un momento dado, esa curva tiene que aplanarse y empezar a disminuir; cuando llega ese tope, ese es el pico de la curva y es cuando se supone que ya empieza a bajar la cantidad de contagios que van habiendo día a día, este proyecto es de gran utilidad ya que gracias al pronóstico donde se intenta predecir a futuro el comportamiento del virus , se puede igual evaluar las medidas tomadas en el departamento del atlántico para un mejor desarrollo de la situación donde no tengan que haber un alto número de víctimas, Siendo el modelo matemático desarrollado también aplicable a usos futuros en diversas regiones del país. Donde se podría evaluar las variables usadas en los modelos, pero enfocadas a cada región para dar una vista clara de lo que podría suceder a futuro, este proyecto evalúa todas las situaciones posibles que logren alterar el comportamiento del virus, ya sea por la llegada de variantes como la delta, británica y andina, por la disminución de restricciones, reactivación del comercio, vida laboral etc. La pandemia de COVID-19 ha perturbado todos los aspectos de la cotidianidad. donde las personas han tenido que enfrentarse a diversos desafíos para poder salir adelante, estudios revelan que el impacto de la pandemia en las personas es sistemático, profundo y desproporcionado.

The project aims to develop an algorithm that is capable of forecasting the fourth wave of the covid-19 pandemic in the Atlantic, supporting high-performance algorithmic knowledge and a set of mathematical models that allow evaluating through specific variables together with data current infections the behavior of what is known as the fourth peak of the pandemic, which is called a moment of ascending curve where the number of infections increases. And At some point, that curve has to flatten out and start to decline; When that limit arrives, that is the peak of the curve and that is when it is assumed that the amount of infections that occur day by day begins to decrease, this project is very useful since thanks to the forecast where you try to predict the future the behavior of the virus, it is also possible to evaluate the measures taken in the department of the atlantic for a better development of the situation where there should not be a high number of victims, being the mathematical model developed also applicable to future uses in various regions of the country . Where the variables used in the models could be evaluated, but focused on each region to give a clear view of what could happen in the future, this project evaluates all possible situations that manage to alter the behavior of the virus, either by the arrival of variants such as the delta, British and Andean, due to the reduction of restrictions, reactivation of trade, working life, etc. The COVID-19 pandemic has disrupted all aspects of everyday life. where people have had to face various challenges to get ahead, studies reveal that the impact of the pandemic on people is systematic, profound and disproportionate.

Country
Colombia
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Keywords

Machine Learning, Cuarta ola, Algoritmo, COVID-19, Atlantico, Modelo analitico

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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