29 Oct 2020 Update
Here is a new plot:
As I usual I am using only the data from coronavirus.data.gov.uk. The above plot shows the number of UK COVID19 deaths per 1000 cases with a 28-day delay (the reason for the delay is because of the delay between confirmed cases and death).
The 28-day delay simply means we divide the number of deaths reported on day N by the number of cases reported on day N minus 28. It does NOT mean we are tracking whether the new cases died 28 days later.
Obviously, as I have explained in previous articles on this blog, there is a causal explanation for the higher numbers in May: 28 days prior to that it was mainly hospitalized people being tested and recorded as 'cases'. And there are lots of other causal explanations to consider, along with the general weakness of the data provided as was explained here. Moreover, as Clare Craig has shown COVID19 deaths are clearly being over-counted.
But, increasingly, it is clear that the continued response to the virus is not in proportion to its deadliness. It is time for the Government and SAGE to provide real evidence to support the continued lockdowns and infringements of civil liberties and they can start by putting some numbers on the factors here:
A full analysis should also factor in the personal costs/risks of those people advising and making the lockdown decisions. They are - without exception - those whose own jobs are not threatened as a consequence of their decisions to lockdown and (interestingly) those least likely to be denied or delayed treatment for non-COVID medical conditions.
And note the chart does not include the many billions of pounds already spent or committed on (highly questionable) research, equipment and apps dedicated to 'combatting COVID19'. Just as there was no cost-benefit analysis for lockdown there has been no cost-benefit analysis for most of that spending, which also comes at the expense of research and equipment needed for other more serious medical conditions that will be with us for much longer.
See also
- Why we know so little about COVID19 from the data provided
- Impact of false positives in Covid testing
- Covid19 hospital admissions data: evidence of exponenial increase?
- Don't panic: limits to what we know about Covid-19 PC testing, inferred infection rates and alse positive rates
- A privacy-preserving Bayesian network model for personalised COVID19 risk assessment and contact tracing
Covid-19: Infection rates are higher, fatality rates lower than widely reported - Coronavirus: country comparisons are pointless unless we account for these biases in testing
- Why most studies into COVID19 risk factors may be producing flawed conclusions - and how to fix the problem
- Causal explanations, error rates, and human judgment biases missing from the COVID-19 narrative and statistics
- Covid-19 risk for the black and minority ethnic community: why reports are misleading and create unjustified fear and anxiety
- UK Covid19 death rates by religion: Jews by far the highest and atheists by far the lowest 'overall' - but what does it mean?
- All COVID articles on this blog
This is brilliant work. It's utterly disgusting that it's likely to have no impact on the way our politicians are operating.
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