UC Riverside

BACKGROUND:The recent outbreak of novel coronavirus (2019-nCoV) has infected tens of thousands of patients in China. Studies have forecasted future trends of the incidence of 2019-nCoV infection, but appeared unsuccessful. Farr's law is a classic epidemiology theory/practice for predicting epidemics. Therefore, we used and validated a model based on Farr's law to predict the daily-incidence of 2019-nCoV infection in China and 2 regions of high-incidence. METHODS:We extracted the 2019-nCoV incidence data of China, Hubei Province and Wuhan City from websites of the Chinese and Hubei health commissions. A model based on Farr's law was developed using the data available on Feb. 8, 2020, and used to predict daily-incidence of 2019-nCoV infection in China, Hubei Province and Wuhan City afterward. RESULTS:We observed 50,995 (37,001 on or before Feb. 8) incident cases in China from January 16 to February 15, 2020. The daily-incidence has peaked in China, Hubei Providence and Wuhan City, but with different downward slopes. If no major changes occur, our model shows that the daily-incidence of 2019-nCoV will drop to single-digit by February 25 for China and Hubei Province, but by March 8 for Wuhan city. However, predicted 75% confidence intervals of daily-incidence in all 3 regions of interest had an upward trend. The predicted trends overall match the prospectively-collected data, confirming usefulness of these models. CONCLUSIONS:This study shows the daily-incidence of 2019-nCoV in China, Hubei Province and Wuhan City has reached the peak and was decreasing. However, there is a possibility of upward trend.