A recursive bifurcation model for early forecasting of COVID-19 | ResearchBunny

Index

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

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