Underwhelmed

Data and Methodology

If he lockdown was intended to protect the NHS then it might have worked a bit too well. We were told we had to flatten the curve and we did. But by how much? We've seen the stories of empty hospitals and because elective and non urgent surgery cancelled.

Here's a chart generated from https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-daily-deaths/. I haven't done anything with it except cut and paste the totals of daily deaths by age into Libreoffice calc, Transform it from columns to rows and then copy it to Google sheets, which I've used for all the other manipulation.

And here's a chart I made from publically available data.

The blue bars are daily hospitalisations derived from 

• Daily deaths as reported on Worldometer (this snapshot was taken when only hospital deaths were reported)
• I've applied a 4 day smoothing to account to try to smooth out the weekend reporting systemic errors.
• I've multiplied the deaths by 3 as only one third of long term hospitalised patients survive. https://news.sky.com/story/coronavirus-a-third-of-all-covid-19-hospital-patients-die-with-dementia-and-obesity-carrying-the-highest-risk-11980894
• I've assumed that these are the patents that are occupying the critical care beds.

The red line is:

• On April 12th there were 2295 available NHS critical care beds. https://www.reuters.com/article/health-coronavirus-britain-nhs-idUSL9N26V04T
• I've added 2295 to the April 12th calculated hospitalisations
• this excludes the 4000 beds at the nightingale hospital which were not fully available at the time.

That's all data. I'm now going to step into the realm of models and speculation.

The big surprise came when I came to construct a tall thin bell curve with the same area which just failed to breach the capacity line.

The tall thin curve came later with a slower incremental part.

I know this can't be right. But as they say, "all models are wrong and some are useful."

This one is obviously wrong and not very useful. If you think you can improve it please do.

If I get the time and the inclination I will generate some numbers from my RCalc program to try to make a different shaped curve. I'll need to make a branch of the code so I can add add some fudge factors (something I  because the aim of the code was to find the bell curve, not fit it to real life) the results of R0=3 has 70 million people infected in 17 iterations and the opportunity factor doesn't get a chance to pull the curve down. The spreadsheet calculations are obviously crude and somehow wrong. My focus was to get a bell curve with the right shape and the same end total. The fact it had the same width is a mystery to me. It is not designed in to the formula. And I messed up the horizontal axis labels.

As ever all source data is on github here:

https://github.com/davidsinfield/RValue/blob/master/Underwhelmed.ods

It's freely available, do with it what you will.

Before you comment

• There is no doubt that this is a dangerous disease to the vulnerable. I am not trivialising it.
• The hospitals have done a grand job and the lack of masks and gowns was a fiasco. I'm not sure what could have been done about it. And I have no intention of being drawn in to a recriminations.
• I have no wish to kill you or your granny. I'm a grandad I'm well into the age danger zone with a highish BMI and I would be considered quite vulnerable. 
• The third chart is very definitely wrong. I don't need to be told I am open to suggestions as to how it can be improved.