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Why lockdown could cost more lives than it saves – The Telegraph

On March 25, just a day after Britain shut down, economist Professor Philip Thomas, of Bristol University, made a grim prediction.

If the country remained in lockdown for longer than two months, he warned, any lives saved would be wiped out by those lost from the impact of the inevitable recession.

Britain hit that timeline more than a fortnight ago, but restrictions largely remain in place and there is growing alarm among economists that the cure has become far deadlier than the disease.

Prof Thomas now estimates that 150,000 people could die from Covid-19 over five years under the intermittent lockdown conditions necessary to keep infection rates, or the reproduction ‘R’ number, below one if a vaccine is not found.

https://www.telegraph.co.uk/news/2020/06/07/lockdown-restrictions-not-simple-lives-versus-livelihoods/

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Coronavirus infections in England and Wales hit peak days before lockdown, study finds – The Telegraph

Modelling by Professor Simon Wood, of the school of mathematics at the University of Bristol, shows that the majority of people who died at the peak would have been infected roughly five days before the lockdown was introduced.

https://www.telegraph.co.uk/news/2020/06/04/coronavirus-infections-england-wales-hit-peak-days-lockdown/

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UK Covid-19 infection peak may have fallen before lockdown, new analysis shows – Professor Simon Wood, University of Bristol

By simply separating out weekly reporting variability, the long-term death rate profile becomes clear, and its peak can be located with confidence. Using the distribution of times from disease onset to death, it is possible to extend the model to infer the time course of fatal infections required to produce the later deaths. Because of the wide variability in onset to death times, a quite sharply peaked infection curve produces a death curve that declines only slowly. The inferred infection curve peaks a few days before lockdown, with fatal infections now likely to be occurring at a much-reduced rate.

Diagram shows the inferred time course of the number of fatal infections, where day 0 is March 13th. The continuous curve is the median estimate. The dashed curves delimit 80% and 95% credible intervals. The vertical grey line shows day of lock down. The overlaid scaled bar chart summarizes the probability distribution for the day of the infection peak.

http://bristol.ac.uk/maths/news/2020/peak-lockdown.html