range was 7.5‐90μg<sup>23</sup> . The model is mathematical, relating the attack rate to the protection offered by a vaccine and to _R0_ (for a homogenous population). In their most involved model variant (a ‘leaky’ policy), they assume that the vaccines could offer partial protection in some individuals even with the maximum dose, i.e., the population is heterogeneous in the efficacy of the vaccine. In this variant, the model is calibrated to a predicted attack rate (73%) at _R0_ =1.8; derived from the simple, homogenous form of the model<sup>53</sup> .

For all three vaccines, increasing population coverage with the minimum dose leads to lower infection attack rates. As an example, assume that for one of the vaccines, an adjuvanted influenza A (H5N1) vaccine, there is a stockpile such that the maximum dose allows coverage of 20 out of 300 million Americans and yields an attack rate of 67.6%. Then the authors find that for a heterogeneous population using the minimum dose is optimum, producing an absolute reduction in the attack rate of 8.9 percentage points. Even if healthcare workers are prioritized (up to 45% reservation of the same stockpile) the minimum dosing policy would still be superior, reducing the attack rate by 4.8 percentage points. The insights are as usual subject to the caution that the clinical trials involved poorly matched pre‐pandemic vaccines, and that the dependence on _R0_ in the involved model variant is a source of uncertainty. These caveats are discussed in a related review note54.

# 2. **Community policies** : _Case isolation & contact tracing, socia distancing, quarantinesl_

Community‐level nonpharmaceutical interventions (NPIs) figure across the containment and mitigation focused studies above. These form the core of the WHO _Interim Protocol_ , aimed at developing countries, as well as the DHHS/CDC<sup>7</sup> plan, where different NPIs are recommended based on expected severity. Since it is difficult to predict the severity in advance, the prioritization may be difficult to implement. There are two reasons to consider NPIs in further detail. First, community‐level policies are likely to be of importance in resource‐poor settings. Second, the comparative studies produced a dichotomy that goes beyond containment vs. mitigation focus. Generally, social distancing and quarantines were effective and robust to an increase in _R0_ for containment in SE Asia (see policy **_f_** in Table 6, and compare policy **_4_** to **_1_** in Table 7), but not for mitigation in the US (e.g., review policies **_7_** ‐ **_10_** in Table 9 at _R0_ =1.6, and then across _R0_ :1.6‐1.9). This counters the logic that policies successful at containment should also mitigate successfully. If there are factors beyond methodology (e.g., different objectives or core assumptions) that make community‐level policies ineffective in some contexts, it should interest policymakers. This issue can be examined with recent studies that specifically analyze these policies, beginning with analyses of historical data on community‐level nonpharmaceutical policies.

_Historical evidence_ : A WHO review<sup>55</sup> surveyed the accounts from the 1918 pandemic (when almost all control policies were nonpharmaceutical) and found public health officials of the period skeptical on the success of quarantines or case isolation. Early case detection and isolation supplemented by movement restrictions had more impact on attack rates in closed settings (e.g., military barracks and college dormitories). Social distancing, especially school closure, may have more value, as suggested by studies of seasonal influenza epidemics in Israel and France<sup>55</sup> . However, in some contexts school closure or holidays can lead to children becoming more mobile in the community, thus leading to higher transmission. The WHO review provides some evidence for this from US cities during the 1918 pandemic. In this case, school closure without additional household restrictions on 27