Policies should be implemented if their cost-benefit ratio is favorable compared to other options, including no action. As a simple illustration, suppose the per-capita costs of mandatory contact reduction policies, denoted C, are fixed and that the benefits are linear in avoided cases, ΔF = F no policy – F policy. Ignoring uncertainty, and hence issues of policymaker risk aversion, mandatory measures should be implemented if bΔF > C, where b is the benefit per avoided case. In the scale-free case, ΔF = 0.75 for the H= case but falls to 0.59 in the H≠ condition (see the supplement). For 0.59 ≤ C/b ≤ 0.75, whether mandatory measures are indicated depends on whether the population is homogeneous or not. Uncertainty, nonlinear costs and benefits, or risk averse policymakers will change the width of this interval of policy sensitivity but not the principle that the choice among policies may be sensitive to network type, inpidual heterogeneity and other assumptions.
The size of the region of policy sensitivity also depends on the model boundary. For example, if awareness of the epidemic arising from, e.g., media reports causes inpiduals to engage in social distancing spontaneously, contacts will fall even without quarantine and travel restrictions, reducing the benefits of mandatory measures. If spontaneous social distancing reduces R0 persistently below one, mandatory measures would not be needed to quench the epidemic and would not be justified on cost-benefit grounds. At the other extreme, if the public’s
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