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Loglet-analysis (Decomposition of growth into S-shaped logistic components) is a better predictor for the covid-19 spread, as it takes into account the evolution of multiple waves.

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deganza/Loglet-analysis-revisiting-covid19-projections

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Loglet-analysis-Revisiting covid19-projections

In the last analysis we showed how to make a forecast for the next 30 days using covid data from the Johns Hopkins Institute. The projections were optimized for a logistic growth model. We will show that the decomposition of growth into S-shaped logistic components also known as Loglet analysis, is more accurate as it takes into account the evolution of multiple covid waves.

The article to this project is published on Medium: https://deganza11.medium.com/loglet-analysis-revisiting-covid19-projections-5e9d14a46f2

knime-workflow on Knime-Hub: https://hub.knime.com/deganza/spaces/Public/latest/covid19_Loglet_knime_jupyter_tableau/

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Loglet-analysis (Decomposition of growth into S-shaped logistic components) is a better predictor for the covid-19 spread, as it takes into account the evolution of multiple waves.

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