Simulating and Forecasting the Cumulative Confirmed Cases of SARS-CoV-2 in China by Boltzmann Function-based Regression Analyses

Xinmiao Fu; Qi Ying; Tieyong Zeng; Tao Long; Yan Wang

The above analyses were performed assuming that the released data on the confirmed cases are 144 precise. However, there is a tendency to miss-report some positive cases such that the reported 145 numbers represent a lower limit. One typical example indicating this uncertainty is the sudden 146 increase of more than 13 000 new confirmed cases in Hubei province on Feb 12 after clinical 147 features were officially accepted as a standard for infection confirmation. Another uncertainty 148 might result from insufficient kits for viral nucleic acid detection at the early stage of the outbreak. 149 We thus examined the effects of the uncertainty of the released data on the estimation of the 150 potential total number of confirmed cases using a Monte Carlo method (for detail, refer to the 151 Methods section). For simplicity, we assumed that the relative uncertainty of the reported data 152 follows a single-sided normal distribution with a mean of 1.0 and a standard deviation of 10%.