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A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany

Medicine and Health

A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany

J. Shen

This paper by Julia Shen introduces a groundbreaking recursive bifurcation model for early forecasting of COVID-19 spread, demonstrating remarkable effectiveness in comparison to traditional models in South Korea and Germany.

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Playback language: English
Abstract
This paper introduces a recursive bifurcation model for early forecasting of COVID-19 spread. The model uses linear and nonlinear least-squares fitting to analyze infected populations, recursively processing data through bifurcations. Applying the model to South Korea and Germany data shows its effectiveness compared to logistic and Richards models in early forecasting, though limitations and future research directions are noted.
Publisher
Scientific Reports
Published On
Nov 27, 2020
Authors
Julia Shen
Tags
COVID-19
forecasting
recursive bifurcation model
infected populations
South Korea
Germany
data analysis

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