Fig. 5.

Mathematical representations of dynamical coefficients with respect to isolation policy and identification policies respectively. (a) tuning the parameter b of α can subtly regulate the implement schedule of isolation policy. We choose $\alpha =0.4$ as the critical value for daily isolation rate at which this policy is fully implemented. The practical isolation policy curve $b=0.10$ (Feb. 17th) is selected as the baseline to compare results calculated by advancing or postponing of this policy. The boundaries of α ∈ [1.8, 0.2] are determined by the basic reproduction number R₀ and the duration from infected to infected. (b) tuning the parameter v of η can reflect the rate of community identification for the infected but undiagnosed patients. We choose $\eta =0.5$ as the threshold of daily identification rate and $v=0.05$ (Feb. 24th) as the baseline to compare the impact of the implement schedule of identification policy to the pandemic trend. The boundaries of η ∈ [0.2, 0.7] are determined by the testing ability of laboratories.