Dynamics and control strategies of infectious disease under different scenarios on hierarchical geographical networks<xref rid="cpb_28_12_128901_fn1" ref-type="fn">*</xref><fn id="cpb_28_12_128901_fn1"><label>*</label><p>Project supported by the National Key R&D Program of China (Grant No. 2018YFF0301005), the National Natural Science Foundation of China (Grant Nos. 71673161 and 71790613), and the Collaborative Innovation Center of Public Safety, China.</p></fn>

Dynamics and control strategies of infectious disease under different scenarios on hierarchical geographical networks**

Project supported by the National Key R&D Program of China (Grant No. 2018YFF0301005), the National Natural Science Foundation of China (Grant Nos. 71673161 and 71790613), and the Collaborative Innovation Center of Public Safety, China.

Ma Xun^{1, 2, 3}, Cui Ya-Peng^{1, 2, 3}, Yan Xiao-Li^{1, 2, 3}, Ni Shun-Jiang^{1, 2, 3, †}, Shen Shi-Fei^{1, 2, 3}

Comparison of the results of the three strategies with M_s in the case of different μ and p_s: (a) μ = −2, p_s = 0.4, (b) μ = 2, p_s = 0.4, (c) μ = −2, p_s = 0.6, (d) μ = 2, p_s = 0.6, (e) μ = −2, p_s = 0.8, (f) μ = 2, p_s = 0.8. The value of M_s corresponds to different screening ranges in each case. The solid points represent C(τ) and hollow points represent τ. Each point is generated from 500 simulations of global infection.