Predicting the epidemic trend of COVID-19 in China and across the world using the machine learning approach

Background: Although the COVID-19 has been well controlled in China, it is rapidly spreading outside China that may lead to catastrophic results globally without implementation of necessary mitigation measures. Because the COVID-19 outbreak has made comprehensive and profound impacts on the world, an accurate prediction of its epidemic trend is significant. Although many studies have predicted the COVID-19 epidemic trend, most of these studies have used the early stage data and focused on the China cases. Methods: We predicted the COVID-19 epidemic trend in China and across the world using the machine learning approach. We first built the models for predicting the daily numbers of cumulative confirmed cases (CCCs), new cases (NCs), and death cases (DCs) of COVID-19 in China based on the data from Jan 20, 2020, to Mar 1, 2020. Furthermore, we built the models, derived from the models for the China cases, for predicting the epidemic trend across the world (outside China). Findings: The COVID-19 outbreak will peak on Feb 22, 2020 in China and April 10, 2020 across the world. It will be basically under control early April, 2020 in China and mid-June, 2020 across the world. The total number of COVID-19 cases will reach around 89, 000 in China and 403,000 across the world during the epidemic. Around 4,000 and 18,300 people will died of COVID-19 in China and across the world, respectively. The COVID-19 mortality rate is estimated to be around 4% all over the world. Interpretation: The COVID-19 outbreak is controllable in the foreseeable future if comprehensive and stringent control measures are taken.