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. 2020 Jun 10;8:109719–109731. doi: 10.1109/ACCESS.2020.3001298

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This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

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FIGURE 4. — Parameter sensitivity. The three panels explore the expected total number of infections (population ) for various parameter values and (i.e and for ) and different control strategies (i.e. for different ). The four panels depicted here correspond to (a) ; (b) ; (c) (90%, 80%, 70% physical distancing as reported in the panel headings). In each case we computed 80 simulations of 300 days. Other parameters are as reported in Table 1). Note that panel (a) has a linear ordinate, panel (b) and (c) are depicted with a logarithmic scale. As in Fig. 3 we observe explosive growth in impact with lower levels of compliance.

Inline graphic — Parameter sensitivity. The three panels explore the expected total number of infections (population ) for various parameter values and (i.e and for ) and different control strategies (i.e. for different ). The four panels depicted here correspond to (a) ; (b) ; (c) (90%, 80%, 70% physical distancing as reported in the panel headings). In each case we computed 80 simulations of 300 days. Other parameters are as reported in Table 1). Note that panel (a) has a linear ordinate, panel (b) and (c) are depicted with a logarithmic scale. As in Fig. 3 we observe explosive growth in impact with lower levels of compliance.