Model simulation
We show our simulations in Figure 4 . Under the naive scenario, we assume governmental action strength α  = 0 and intensity of individual reaction κ  = 0, which is unlikely. The second scenario is when we only consider “individual reaction”, both the peak value and the number of cumulative cases are substantially reduced. The third scenario is considering both “individual reaction” and “governmental action”, and the reduction becomes even further. We highlight the third scenario, as we know the individual reaction and governmental action existed and played important role in previous epidemic and pandemic (He et al., 2013). Our third scenario implies that• The total number of zoonotic infections was 145 which corresponds to the reported 41 zoonotic cases with a reporting rate of ≈28%. This level is largely in line with estimates of Riou and Althaus (2020), Nishiura et al. (2020), and Q. Li et al. (2020).
• The cumulative number of cases in Wuhan was 4648 by January 18, 2020, which is in line with estimates of other teams (Bogoch et al., 2020, J.T. Wu et al., 2020, NCPERET, 2020).
• The cumulative number of cases in Wuhan was 16,589 by 27 January, 2020. Compared with estimates 25,630 (95%CI: 12,260–44,440), announced by University of Hong Kong team on 27 January, 2020, our estimate is low but in their the 95% CI.
• The cumulative infections could be 84,116 in Wuhan by the end of April 2020.
• We compare simulated and reported numbers, and reconstruct the daily reporting ratio, which shows an improvement from a level of below 10% to around 50% from January 2020 to February 2020 and reflects the reality.
• Due to adjustment of the reporting policy, i.e., an effort to report all clinical cases accumulated in the past few days/weeks, there are a few days where the number of reported cases are artificially high than simulated cases. The reason is that the reported cases in these few days included clinical cases but not laboratory confirmed that are accumulated in the past few days, also weeks.
Figure 4 (a) Daily new cases with a reporting delay of 14 days under three scenarios: naive (i.e., no action taken) as grey dotted curve, individual reaction regarding to the outbreak as red dashed curve, and individual reaction plus governmental action as green solid curve and reported cases (from official release and (Li et al., 2020) as grey curve with dotes. (b) The reporting ratio between reported cases and estimates when individual reaction and governmental action are involved.
The main purpose of this work is to propose a conceptual model to address the individual reaction (controlled by κ) and governmental action (controlled by α), as well as time-varying reporting rate. We perform a simple sensitivity ity analyses on α and κ in Figure 5 , where we can see that both α and κ are needed to capture the observed pattern. In particular, when α is around 0.9 and κ is greater than 110, the simulated largely match the observed.
Figure 5 Sensitivity analyses on α and κ. We simulate the base model with both individual reaction and governmental action while varying α and κ. We show model outcome when (a) α = 0.5 (black solid), 0.6 (red dashed), 0.7 (green dotted), 0.8 (blue dash-dotted) and 0.9 (cyan long dashed curve), while κ = 1117.3, when (b) κ = 100 (black solid), 500 (red dashed), 900 (green dotted), 1300 (blue dash-dotted) and 1700 (cyan long dashed curve), while α = 0.8478. Grey dots show the reported cases.