Forecasting the Endemic/Epidemic Transition in COVID-19 in Some Countries: Influence of the Vaccination

Author:

Waku Jules1,Oshinubi Kayode2ORCID,Adam Umar Muhammad3ORCID,Demongeot Jacques2ORCID

Affiliation:

1. IRD UMI 209 UMMISCO and LIRIMA, University of Yaounde I, Yaounde P.O. Box 337, Cameroon

2. AGEIS Laboratory, UGA, 38700 La Tronche, France

3. Department of Mathematics, Federal University, Dutse 720222, Nigeria

Abstract

Objective: The objective of this article is to develop a robust method for forecasting the transition from endemic to epidemic phases in contagious diseases using COVID-19 as a case study. Methods: Seven indicators are proposed for detecting the endemic/epidemic transition: variation coefficient, entropy, dominant/subdominant spectral ratio, skewness, kurtosis, dispersion index and normality index. Then, principal component analysis (PCA) offers a score built from the seven proposed indicators as the first PCA component, and its forecasting performance is estimated from its ability to predict the entrance in the epidemic exponential growth phase. Results: This score is applied to the retro-prediction of endemic/epidemic transitions of COVID-19 outbreak in seven various countries for which the first PCA component has a good predicting power. Conclusion: This research offers a valuable tool for early epidemic detection, aiding in effective public health responses.

Publisher

MDPI AG

Subject

General Medicine

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2. Xu, Z., Yang, D., Zhang, H., and Demongeot, J. (2023). A Novel Mathematical Model that Predicts the Protection Time of SARS-CoV-2 Antibodies. Viruses, 15.

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