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Several predictions made by experts ahead of the UK-wide lockdown in March are confirmed in a new detailed analysis of data released by The BMJ today.
A report by researchers from Imperial College London was reported to be the main evidence behind the 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-analyzed the results of this report using updated data in a detailed simulation model (“CovidSim”).
The new analysis confirms that the information used by SAGE’s advisory committee to advise on the closure showed that school closures would result in more COVID-19 deaths overall than no school closings, and that social distancing in those older than 70 would only be more effective in reducing covid. -19 deaths than general social distancing.
It also confirms that none of the proposed mitigation strategies modeled in the original report, apart from the effective implementation of a vaccine, would reduce the total predicted 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 result in terms of reducing the peak demand for beds in intensive care units (ICUs), but are also known to prolong the epidemic, resulting in more deaths from covid. -19 long-term unless an effective vaccination program is implemented.
It confirms that adding the closure of schools and universities to other measures (isolation of cases, home quarantine and social distancing in people over 70 years old) would increase the overall total number of deaths from COVID-19 compared to no closure.
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 to social distancing of more than 70 years only. This is because Covid-19-related deaths are highly skewed towards older age groups.
More than 97% of deaths from covid occur in those over 65, compared to 5% from the Spanish flu. As such, they conclude that mitigating a covid-19 epidemic “requires a different strategy than an influenza epidemic, with more emphasis on protecting the elderly and vulnerable.”
The model clearly predicts a second wave, which initially grows more slowly, but becomes larger than the first wave unless the interventions are re-implemented. The researchers emphasize that the currently available data is insufficient to reliably predict exactly where localized peaks will occur.
However, they note that UK policy advice has focused on reducing the total number of COVID-19 cases, not the number of deaths. Strategies that minimize deaths “involve focusing the strictest social distancing measures in nursing homes where people are likely to die rather than in schools where they are not.”
In all mitigation scenarios, epidemics modeled with CovidSim eventually end with widespread infection and immunity, and the final number of deaths depends primarily on the age distribution of those infected and not on the total number, they write.
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Peer reviewed? yes
Type of evidence: observational
Subjects: critically ill adults with covid-19
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