Predictive Theory of Covid-19 Infections at European Countries Through Bessel Functions: Past and Present

• Autor: Nieto-Chaupis, Huber
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad Autónoma del Perú
• Repositorio: AUTONOMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.autonoma.edu.pe:20.500.13067/1813
• Enlace del recurso: https://hdl.handle.net/20.500.13067/1813; https://doi.org/10.1109/TransAI51903.2021.00021
• Nivel de acceso: acceso restringido
• Materia: COVID-19; Pandemics; Morphology; Europe; Data models; Artificial intelligence; Strain; https://purl.org/pe-repo/ocde/ford#2.02.04

The data of infections by Covid-19 is modeled through the integer-order Bessel functions that have been parametrized in according to the morphology of data. In particular, the modeling is focused on official data belonging to UK, Germany, Italy and Netherlands. The free parameters of model have been coherently linked to data. Interestingly, it was seen that a "silent period" with the lowest cases of infections play a relevant role for new pandemics as well as the apparition of new strains, such as the most recent "delta-variant".