The application of chaos theory in COVID-19 data analysis

This research presents a study on the existence of chaotic behaviour in COVID-19 time series data using the Largest Lyapunov Exponent (LLE) and forecasts the outcome of the new daily cases of infected people until 2023 by chaos indicators tools, Logistic Map. The study also chooses another mathematical model, Linear Regression, to verify the accuracy of the Logistic Map by comparing both methods. The comparison between these methods is analyzed by using Mean Square Error (MSE). The data was collected from the end of January until early December 2020 involving Malaysia, China, Singapore, the USA and Italy. The result shows the countries tested have the existence of chaotic behaviour. Meanwhile, forecasting depicts some countries whose cases are declining and some are increasing.