Prediction of an epidemic with Machine Learning and Covid-19 Data

¹ University of California, Santa Barbara, California, United States, 93117.
² University of California, Santa Barbara, California, United States, 93117.
³ Sichuan University, Chengdu, Sichuan.

^a Email: wfang@ucsb.edu
^b Email:yihuiwang@ucsb.edu
^c Email: 2017141491001@stu.scu.edu.cn

Abstract

The human race has already overcome many epidemics such as smallpox, SARS, and Black Death with vaccines or cures. As the number of infected people climes up to 10 million due to the new coronavirus in 2020, the human race faced another public health challenge. Because of the strong infectivity of the new coronavirus, humans have not won this fight after half a year. During the times of defeating these viruses, humans sacrificed not only wealth but also lives. Apart from many tribulations, human race also has great development in on technology. Machine learning method was invented and applied in many fields such as robotics, healthcare, and medicine. Since the transmission of a virus is related to social factors such as the percentage of college degree, and population density, there is a model built in this article that only related to outside factors such as health insurance coverage to predict that when the climax of an epidemic will arrive by using machine learning techniques and data related to Covid-19. Since the model does not take transmissibility of one specific virus, this model can apply to any epidemics to forecast the peak with enough data.