AI Article Synopsis

  • This study explores the Hybrid NAR-RBFs Networks model to understand the spread of a modified COVID-19 virus, focusing on different age groups and the effectiveness of various strategies to curb transmission.
  • The research verifies the existence and stability of unique solutions for the COVID-19 model using fixed point theory, indicating a comprehensive approach to analyzing the disease dynamics.
  • Additionally, advanced techniques, such as the Atanga Toufik method and fractal fractional analysis, are employed to monitor the infection spread effectively, with MATLAB simulations validating the model's outcomes.

Article Abstract

The Hybrid NAR-RBFs Networks for COVID-19 fractional order model is examined in this scientific study. Hybrid NAR-RBFs Networks for COVID-19, that is more infectious which is appearing in numerous areas as people strive to stop the COVID-19 pandemic. It is crucial to figure out how to create strategies that would stop the spread of COVID-19 with a different age groups. We used the epidemic scenario in the Hybrid NAR-RBFs Networks as a case study in order to replicate the propagation of the modified COVID-19. In this research work, existence and stability are verified for COVID-19 as well as proved unique solutions by applying some results of fixed point theory. The developed approach to investigate the impact of Hybrid NAR-RBFs Networks due to COVID-19 at different age groups is relatively advanced. Also obtain solutions for a proposed model by utilizing Atanga Toufik technique and fractal fractional which are the advanced techniques for such type of infectious problems for continuous monitoring of spread of COVID-19 in different age groups. Comparisons has been made to check the efficiency of techniques as well as for finding the reliable solutions to understand the dynamical behavior of Hybrid NAR-RBFs Networks for non-linear COVID-19. Finally, the parameters are evaluated to see the impact of illness and present numerical simulations using Matlab to see actual behavior of this infectious disease for Hybrid NAR-RBFs Networks of COVID-19 for different age groups.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11430756PMC
http://dx.doi.org/10.1186/s12879-024-09329-6DOI Listing

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Article Synopsis
  • This study explores the Hybrid NAR-RBFs Networks model to understand the spread of a modified COVID-19 virus, focusing on different age groups and the effectiveness of various strategies to curb transmission.
  • The research verifies the existence and stability of unique solutions for the COVID-19 model using fixed point theory, indicating a comprehensive approach to analyzing the disease dynamics.
  • Additionally, advanced techniques, such as the Atanga Toufik method and fractal fractional analysis, are employed to monitor the infection spread effectively, with MATLAB simulations validating the model's outcomes.
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Background: Mathematical modeling of vector-borne diseases and forecasting of epidemics outbreak are global challenges and big point of concern worldwide. The outbreaks depend on different social and demographic factors based on human mobility structured with the help of mathematical models for vector-borne disease transmission. In Dec 2019, an infectious disease is known as "coronavirus" (officially declared as COVID-19 by WHO) emerged in Wuhan (Capital city of Hubei, China) and spread quickly to all over the china with over 50,000 cases including more than 1000 death within a short period of one month.

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