The effect of school closures on COVID mortality: old and new predictions

Objective: to establish what information was available to government when the lockdown decision was taken.
Design: Independent calculations using data known in March 2020 with the CovidSim code which implements the Imperial College individual-based model of the COVID epidemic.
Main Outcome Measures: Replication of summary data reported to SAGE. Detailed study of unpublished results, especially the effect of school closures.
Results: CovidSim would have given a good forecast of the subsequent data if initialised with a reproduction number (R0) about 3.5. We confirm the little-reported forecast that school closures and isolation of younger people were predicted to increase the final number of deaths, albeit postponed to a second and subsequent waves. We find that prompt interventions are highly effective at reducing peak ICU demand, but they also prolong the epidemic, in some cases causing more deaths long term. In the absence of an effective vaccination programme, none of the proposed mitigation strategies reduces the predicted total number of deaths below 200,000. This happens because COVID mortality is highly skewed towards older age groups.
Conclusions: It was predicted in March 2020 that a broad lockdown, as opposed to a focus on shielding the most vulnerable, would reduce immediate ICU demand at the cost of more deaths long-term. The optimal strategy for saving lives in a COVID pandemic is different from that anticipated for an influenza epidemic with different mortality age-profile.