A Prediction System for the Distribution of Epidemic Patients and Asymptomatic Infected Persons Based on Big Data Technology

Guo, X.

In order to analyse and overcome the enormous impact of coronaviruses on people around the world, this paper presents a predictive model for epidemic and asymptomatic patients based on big data techniques. The prediction model chooses a sampling method to optimise the prediction of the main factor of the prevalent order of asymptomatic patients. Based on this, the prediction model is also able to summarise the current epidemiological problems facing the world's population and generate a prediction report and a recommendation report. The results of the study show that the prediction model can efficiently and scientifically address the quantitative conditions that define epidemics and pandemics and can accurately predict the distribution of asymptomatic patients, which can help medical professionals to better confront and address epidemic problems. © 2021 IEEE.