Latest Cases Heatmap Analysis: 22 cases per 100,000 over-80-year-olds

Today’s analysis shows 22 cases per 100,000 in the over-80s population in England.

To put this into context, the Government uses a rate of 20 cases per 100,000 in order to determine (with other factors) whether you should self isolate when you return from a country with this incidence of Covid-19.

An interpretation would be: if you went to a country consisting of only over-80s, you would have to self-isolate when returning to the UK.

Click here for:

Background

Why It Matters

High Resolution Versions:

Green Amber Red (Traffic Light) Version

White to Red (Colourblind-Safe) Version

Guardian Article

Civil Servants Write Things Down

One thing civil servants learn is to write things down. Here is Academy of Medical Sciences 14 July report commissioned by the UK Chief Scientific Adviser. For the record.

It sets out what was known in July, and clearly sets out what the Government needed to do at the time. Straight off the bat, we have the executive summary.

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Line one: “July and August must be a period of intense preparation for our reasonable worst-case scenario for health in the winter that we set out in this report, including a resurgence of COVID-19, which might be greater than that seen in the spring.”

Here are the challenges expected under a reasonable worst case scenario:
1. A large resurgence of COVID-19 nationally, with local or regional epidemics
2. Disruption of the health and social care systems
3. A backlog of non-COVID-19 care
4. A possible influenza epidemic

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And sets out what we should have done:
– public engagement
– extensive public information campaign
– tailoring guidance –
and…

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Here we go: “Significantly expanding the capacity of the TTI programme to cope with increasing demands over the winter and ensure that it can respond quickly and accurately.”

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Improving public health surveillance: “Maintaining a comprehensive, population-wide, near-real-time, granular health surveillance system to ensure rapid identification, investigation and management of local COVID-19 outbreaks across community, work, and health and social care”.

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But why does this matter? What would happen if we got this wrong? “Even scenarios with Rt in the 1.1-1-5 are likely to stretch the NHS”

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So, what was R? The UK Government estimated it to be 1.0-1.2 (so say 1.1). That was on 11 September. https://gov.uk/guidance/the-r

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But look at the caveat that goes with that estimate “The latest published figures represent the situation over the past few weeks rather than today. These estimates do not yet fully reflect any very recent changes in transmission due to, for example, the reopening of schools…”

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The REACT survey estimated R to be 1.7 https://imperial.ac.uk/news/203873/largest-covid-19-testing-study-shows-cases/

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Now re-read the @uksciencechief‘s report “Even scenarios with Rt in the 1.1-1-5 are likely to stretch the NHS”

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But what is this reasonable worst case scenario? Back to the report. Oh, and there’s talk of R being 1.7 again:

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“infections could be expected to rise gradually with a peak in hospital admissions and deaths of a similar magnitude to the first wave (Figure 4). This is projected to occur in January/February, coinciding with a period of peak demand on the NHS….

“The broader shape of the epidemic curve reflects the lower Rt assumed, but would result in an estimated total number of hospital deaths (excl. care homes) between September 2020 and June 2021 of 119,900 … over double the number occurring during the first wave in spring 2020

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Here is the full report. It’s worth a read. And this is what I wrote at the time of publication: ‘don’t say we weren’t warned’.

Heatmaps of COVID Cases in England

Click here to link to Loughborough University press release

Public Health England have released their data on cases split by age and week. We can turn these into a map visualizing the transmission of the epidemic through ages of cases and through time.

We do this by plotting a three-dimensional chart, a heatmap, where the x axis shows time (split into weeks) and the y axis shows the age of individuals who test positive (split roughly into 10-year groups). The colour of the chart shows the number of cases in each age/week cell.

We work out the cases per 100,000 (a standard epidemiological way of presenting incidence numbers) by finding the population in each age group and dividing the cases by that number (population estimates are from 2018).

The beginning of the epidemic

We can see clearly the very high incidence in the over 80s. We now know that many of these were in care homes (although many were in the community). By 28 June (the last day of this chart), the numbers in each age cohort were relatively low, with an incidence of 18 per 100,000 in the over 80s, but a maximum of 11 cases per 100,000 in the under 80s.

The resurgence

We have produced a new heatmap and scaled the reds to the maximum numbers – so the reds in this heatmap (up to 46 cases per 100,000 in 20 to 29 year-olds) are not as high as the reds in the first heatmap (where we saw a maximum incidence of 232 cases per 100,000 in the over 80s)

What we do see however is a movement from young people (20 to 29-year-olds) to the remainder of the working population (certainly up to 60 year-olds).

Based on data from France, the US, and Spain, that I expect that cases will move to the more vulnerable older population, with the very real risk of hospitalizations and deaths increasing over the weeks ahead. Public Health England has already detected new cases in care homes, and we need to be extremely vigilant and aware to ensure we do not repeat the mistakes of the early part of the epidemic.

Update 18 September

Latest version of my heatmap – shows cases established in the working population and the over-80s.

Read here to explain why this is a problem: Should We Be Concerned About COVID Transmission In Young People? Yes.

Should We Be Concerned About COVID Transmission In Young People? Yes.

The case numbers for COVID-19 have risen significantly over the last few days and are now at just under 3,000 cases per day.

We have been told by Minsiters and the Deputy Chief Medical Officer that these cases are primarily in young people. So, why should we be concerned
with COVID transmission in young people when they are statistically unlikely to have severe symptoms or be hospitalised or die?

We can look at other countries to see what may happen in the coming weeks.

Various authors have plotted cases vs age vs time. On the x axis is time, on the y axis are ages. Look at weeks S31/S32 (semaine/week 31 and 32). Some incidence in 20-29 year olds. But in week S33, this spreads to 30-70 year olds. And then in week S35 and S36, cases in 70+ year olds.

We have known this for some time. Here is data from Florida from July.
Same thing. Starts with young people and spreads to older age groups.

Here is the UK data for COVID mortality from Public Health England / Joint Biosecurity Centre / NHS Test and Trace. Very few (but some) deaths in young people. So we may not see significant deaths filtering through for a few weeks

Chart 2(b) in the PHE Surveillance report is the one to watch. These data lag by a couple of weeks

but I anticipate cases spreading up through the age pyramid in the next couple of weeks. Which I anticipate will lead to increased hospitalizations in the week after that, and increased deaths a few weeks from that. But this is not inevitable: we need to go back to the fundamental mitigations of social distancing, hand washing, and mask wearing, and not forgetting that the virus is still very much with us.

Update 13 September 2020

Public Health England have released their latest surveillance report and I have made a heatmap for English cases. The data is a week old. We can see high incidence in the 20 to 29 year olds spreading to older ages. I expect this to continue over the coming weeks.

Update 20 September 2020

Here is the heatmap produced for the data published on 18 September. We see an incidence of 20 cases per 100,000 in the over 80s for the most recent week. But look closely at the figure to the left – 21. This is the same as the top right cell in the heatmap above. What is very worrying is that this figure has changed, since PHE publish their data a week in arrears. This imples that indiviuals are having cases included over a week late. This indicates a potential failure in getting these results processed by NHS Test and Trace.

Update 12 October 2020

Latest heatmap. See here for discussion.



Show Your Working: Model Quality Assurance in Government & Letter in Financial Times

School pupils have had a tough year. For those with examinations, such as A-levels, it has been even tougher. The Department for Education decreed that A-levels and GCSEs should not take place due to the COVID crisis.

This meant that an alternative way of allocating grades to students needed to be found.

To set the context, Ofqual, the Office of Qualifications and Examinations Regulation, regulates qualifications, examinations and assessments in England. It is a Non-Ministerial Government Department constituted under the Apprenticeships, Skills, Children and Learning Act 2009. Now, it is evident that, despite being a non-ministerial department, the Department for Education has a responsibility for setting policy.

Therefore, a Memorandum of Understanding exists between Ofqual and DfE setting out how the two organizations will work together. Section 2 sets out responsibilities:

On 31 March, the Secretary of State, Gavin Williamson, wrote to Ofqual, setting out a ministerial direction. These are the salient points in the Direction:

Firstly, there needs to be a calculation, and secondly ‘as far as possible, the qualification standards are maintained and the distribution of grades follows a similar profile to that in previous years’.

This is a very strong constraint, and to be fair, one that Ofqual met in their initial calculated grade. The problem was it was not fair.

Much debate has been generated as to algorithms, models, and their use in Government (and arm’s length bodies such as Ofqual). But this is not a new problem.

In 2012, the West Coast rail franchise was awarded to FirstGroup. Virgin Trains complained, serious errors were found in the model used by DfT, and the award to FirstGroup was cancelled.

This cost taxpayers £54 million, and, as a result, and report was commissioned to prevent this happening again.

In 2013, Nick Macpherson, Permanent Secretary of the Treasury, published a Review of Quality Assurance of Goverment Analytical Models.

Macpherson’s report was operationalized by HM Government by The Aqua Book: Guidance on producing quality analysis for Government.

The Aqua Book recommends that there should be a Senior Responsible Owner for each model (for Government departments and their arm’s length bodies, such as Ofqual).

Ofqual’s model documentation was set out in their 318-page report Awarding GCSE, AS, A level, advanced extension awards and extended project qualifications in summer 2020: interim report, but the model code has not yet been published.

I cannot find any reference to the Aqua book or ‘quality assurance’ in this model documentation.

Here is my letter about this in the Financial Times

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Data Sources for COVID-19 in England – Letter from PHE to Local Authorities

I have received a copy of the following letter from Public Health England to Local Authorities setting out the data sources available to local authories and the public. The letter is dated 9 July 2020 and I have redacted certain information.

This should be useful for people wishing to understand what data is (and was) available on COVID-19 cases in England.

Data Sources for COVID-19 Analysis in England

Since the early Number 10 Downing Street press conferences, the data available to analyze the progression of the COVID-19 epidemic in the UK has become somewhat fragmented. This is an overview of the major sources of data.

coronavirus.data.gov.uk

This shows data for testing, cases, healthcare, and deaths, updated daily.

More detail is shown on each data set, for example cases:

which is broken down by Nation, Region, Upper Tier Local Authority (‘UTLAs’ / counties) and Lower Tier Local Authorities (‘LTLAs’ / districts). Note that some councils, such as Leicester, are Unitary Authorities, and are both UTLAs and LTLAs and their data is disclosed in both UTLA and LTLA data sets. Currently, this only shows the latest data, and cases per 100,000 people (making it easier to compare different sized locations).

This data is shown as a map at Middle Layer Super Output Area (‘MSOA’) level (although the colour bar makes interpretation a little difficult) and shows cases per week. The mean population of a MSOA is around 7,200 people, so the key is not very useful.

Data for UTLAs and LTLAs used to be reported by specimen date, but it is not clear where these data are now available.

Public Health England Surveillance Reports

Public Health England (‘PHE’) produce a COVID-19 surveillance report each week. This now shows a list of watchlist local authorities.

These data are shown on a


together with a chart of the number of English cases per week

and the history of the highest rated UTLAs

There is also a report of the number of ‘incidents’ (what are colloquially described as outbreaks) and where they originate from.

Total (Cumulative) Deaths from COVID-19 to 7 July 2020

I have analyzed the death data from coronavirus-staging.data.gov.uk and produced the maps below. These are for total deaths since the beginning of the epidemic (not total cases and not current deaths). Leicester (currently locked down with a large number of cases) does not have a relatively high number of deaths. Areas that are dark green do not imply that they are resistant – just that the epidemic has not reached that area in relatively large numbers.

In London, Tower Hamlets is relatively low, which could be due to the relatively young population in that area and the lack of care homes in the centre of London. It is also interesting to note that parts of London have relaively low deaths despite reportedly high levels of serroprevalence.