Accurate Estimation of COVID-19 Active Cases Using Bézier Curve-Based Mathematical Modeling
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Keywords

COVID-19
Bézier curve
Pandemic forecasting
Active case estimation
Data-driven prediction
Mathematical modeling
Epidemiological modeling

How to Cite

Eroglu, E. (2025). Accurate Estimation of COVID-19 Active Cases Using Bézier Curve-Based Mathematical Modeling. Journal of Advances in Applied & Computational Mathematics, 12, 217–230. https://doi.org/10.15377/2409-5761.2025.12.13

Abstract

COVID-19 has reminded humanity of the devastating reality of a pandemic after many years. This global crisis fundamentally altered daily life and exposed significant vulnerabilities in public health systems worldwide. This work proposes a geometric curve-based prototype to support the fight against current and future pandemics. The study models a near-perfect estimation of the active case number with the help of the Bézier curve. The Bézier prototype consists of a C0 class, piecewise continuous, and segmented structure. The noiseless and cost-free model estimates the number of active cases in Germany, Canada, and Israel with minimum error. It compares the results obtained with those of cases in China. The absolute average error of the model is reduced to 0.087%. As a result, the consistent and cost-effective model can increase the likelihood of making rapid and accurate decisions against epidemics, produce well-organized projections for the future, and improve the effectiveness of measures to be taken.

https://doi.org/10.15377/2409-5761.2025.12.13
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Copyright (c) 2025 Emre Eroglu

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