Using logistic function to predict epidemic trend of COVID-19 in China
- 1 The Chinese University of Hong Kong
* Author to whom correspondence should be addressed.
Abstract
As the novel coronavirus continues to spread and mutate, there has been growing concern over public health. Multiple measures have been enacted to mitigate the transmission of the disease, resulting in varying infection scenarios across different countries. To achieve timely and effective control of the epidemic, we note that predicting the future course of an epidemic plays an important role. The logistic function, a continuous-time demographic model, may be a suitable mathematical tool for estimating the trend of the epidemic. This paper aims to evaluate the accuracy of the logistic map in estimating the future trend of the COVID-19. We collect the most recent COVID-19 epidemiological data prior to January 30, 2023, and subsequently integrate figures into the curve fitting tool in MATLAB to generate an epidemic curve. By comparing the actual numbers and the predicted figures, the accuracy of logistic map can be properly assessed.
Keywords
logistic function, infectious disease, COVID-19, modeling, prediction
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Cite this article
Xu,Y. (2023). Using logistic function to predict epidemic trend of COVID-19 in China. Theoretical and Natural Science,28,229-235.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2023 International Conference on Mathematical Physics and Computational Simulation
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