Propagation analysis and prediction of the COVID-19

LiXiang Li; ZiHang Yang; ZhongKai Dang; Cui Meng; JingZe Huang; HaoTian Meng; DeYu Wang; GuanHua Chen; JiaXuan Zhang; HaiPeng Peng

We also studied the curve of the daily increase in the number of people( Figure 6 ). Because the official did not include the imaging features of pneumonia in the clinical diagnosis into the diagnosis conditions for statistics before February 12, 2020, the omission and inaccuracy of the previous data caused the official data to jump on the February 12 (the number of newly diagnosed patients in Hubei was 14840 people).As shown in Figure 6 , our simulation data meet the normal distribution, at this time, the daily new infection data peaked on February 8, with the number of 4500. However, the published data, due to not timely included in the clinical diagnosis image test (red line), many patients were not diagnosed, but the curve has become a downward trend, data deviation. For this reason, we smoothed the clinical diagnosis data on February 12, 13 and 14, and used the Gauss function of latent period. These three days were chosen because of the sudden increase of the number of clinical diagnosis in these three days. It can be seen from the figure that the smooth number of official daily infected persons (black line) and the simulation curve (blue line) fit very well.