Re-analysis shows that school closures would lead to lower demand for ICU beds at the cost of more deaths long term from covid-19
Several predictions made by experts ahead of the UK-wide lockdown in March are confirmed in a detailed re-analysis of the data published by The BMJ today.
A report produced by researchers from Imperial College London was reported to be the main evidence behind lockdown decisions taken by the UK government in March 2020.
The Imperial College report was based on a detailed model of interactions between people in the UK. The model predicted how the virus would spread, how the NHS would be affected, and how many would die in different scenarios.
Now researchers at the University of Edinburgh have re-analysed the results from this report using updated data in a detailed simulation model (“CovidSim”).
The new analysis confirms that information used by the SAGE advisory committee to advise on lockdown showed that school closures would result in more overall covid-19 deaths than no school closures, and that social distancing in the over 70s only would be more effective in reducing covid-19 deaths than general social distancing.
It also confirms that none of the proposed mitigation strategies modelled in the original report, apart from effective implementation of a vaccine, would reduce the predicted total number of covid-19 deaths in the UK below 200,000, more than three times the current number.
Their analysis suggests that the interventions implemented in March gave the best possible outcome in terms of reducing peak demand for intensive care unit (ICU) beds, but were also known to prolong the epidemic, resulting in more long-term covid-19 deaths unless an effective vaccination programme is implemented.
It confirms that adding school and university closures to other measures (case isolation, household quarantine, and social distancing in people older than 70) would increase the overall total number of covid-19 deaths compared with no closures.
It supports the projection that while general social distancing would reduce the number of covid-19 cases, it would increase the total number of deaths compared with social distancing of over 70s only. This is because covid-19 related deaths are highly skewed towards older age groups.
Over 97% of covid deaths occur in over 65s, compared with 5% for Spanish ‘flu. As such, they conclude that mitigating a covid-19 epidemic “requires a different strategy from an influenza epidemic, with more focus on shielding elderly and vulnerable people.”
The model clearly predicts a second wave, initially growing more slowly, but becoming larger than the first unless interventions are reimplemented. The researchers stress that currently available data are insufficient to reliably predict exactly where localised spikes will occur.
Nevertheless, they point out that UK policy advice has concentrated on reducing the total number of covid-19 cases, not the number of deaths. Strategies which minimise deaths “involve focusing stricter social distancing measures on care homes where people are likely to die rather than schools where they are not.”
In all mitigation scenarios, epidemics modelled using CovidSim eventually finish with widespread infection and immunity, and the final death toll depends primarily on the age distribution of those infected and not the total number, they write.