Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions

Jonathan M Read; Jessica RE Bridgen; Derek AT Cummings; Antonia Ho; Chris P Jewell

Our model necessarily makes a number of assumptions. Our estimates of the basic reproductive number of this novel coronavirus are tied to the specific time period and data analysed here, and this measure may change substantially over the course of this outbreak and as additional data arrives. Additionally, the spatial component of our model is dependent upon only airline travel; the model does not include rail and road transportation, so we may underestimate local connectivity and the connectivity of Wuhan to other locations. We also do not attempt to account for any implementation of control, nor and dynamic changes of factors than may influence transmission (such as spontaneous social distancing), nor changes in surveillance and reporting effort. Our choice of modelling approach may also lead to unreliability in the precision of our estimated model parameters (King et al. 2015) , However, our approach used 'raw' counts of cases to fit the model, not cumulative case information, and the point estimates would not be biased (King et al. 2015) .