AAEDM: Theoretical Dynamic Epidemic Diffusion Model and Covid-19 Korea Pandemic Cases

Song-Kyoo Kim

In the other hand, a virus epidemic is atypical textbook example of an exponential growth [9] . An exponential growth model insanely fits well in diffusion (or growth) problems including virus generating systems if the proper parameters are pre-defined at the beginning. But the main problem is that these parameters keeps changing in real-world problems like Covid-19 epidemic cases. The AAEDM (Advanced Analytical Epidemic Diffusion Model) is a dynamic diffusion prediction model which is still a theoretical model but the periods of prediction are segmented for adapting the values from the dataset when the data is available. Additionally, two critical parameters are suggested to build this new prediction model. These two parameters have been opted by most of data scientists and epidemiologists. These factors become vital parameters which could impact on the future prediction of a epidemic and give the clear cut to understand the current pandemic situation well.