Prediction model of global COVID-19 based on big data technology

ABSTRACT

In order to overcome the trend influence of novel Coronavirus epidemic in the future, this paper proposes the panel data modeling method based on big data crawler technology, which is based on Python crawler technology to obtain a more effective estimation model from the dynamic perspective of time and cross section. The results showed that the fixed effect error rate established by the development of COVID-19 in China, Japan, South Korea, Germany and Italy was about 3%, and there is a positive correlation between cured cases and confirmed cases of COVID-19. The predicted confirmed cases of COVID-19 in week 63 will be 69, 11,908, 3156, 112293 and 147,545, respectively. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.