The failure of the government’s testing strategy (Report, September 22) is a lesson in confusing resources with capabilities. Commercial NHS test and trace has resources but not capabilities. NHS labs and local authority directors of public health supported by Public Health England have capabilities but not resources.
In order to resolve this conundrum, we should provide the experts who are custodians of those capabilities with the resources they need to do their job.
Duncan Robertson School of Business and Economics, Loughborough University Leicestershire, UK
Long Interview on BBC Five Live debating against a herd immunity strategy
Interview on LBC (Nick Ferrari) and LBC (Iain Dale)
Here is the heatmap of cases for PHE week 41 using week 40 data.
Studies in Spain, France, and the US have all shown that although the second wave may start in young people, it will inevitably move to older people.
The remarkable thing about this disease is that the death rate increases massively with age.
Students are unlikely to die of Covid-19, although some may, and we are still unsure about the long-term health consequences from catching the disease.
The heatmap of cases shows how the disease has travelled through the age groups. As you go from left to right through the weeks, you can see a gradual rise upwards through the population.
These figures should be seen as a minimum. Lack of testing capacity has meant that not everyone can get a test. For example, we do not know whether delays in testing may be concentrated in certain groups such as care home residents.
The latest figures (which will be revised upwards as new cases are recorded) show a very worrying number of cases in the over-80s.
A case rate of 53 per 100,000 over-80s is very concerning. The Department of Health and Social Care have this week stopped publishing the COVID-19 surveillance report which broke down numbers of people with the disease. However, we can estimate that over 1,000 over-80s tested positive last week. Given the very high fatality rate in over-80s, we can confidently predict that over 100 over-80s will die of infections caught in the last week.
This is one of many reasons why interventions are so critical – by not clamping down hard on the disease now, we will sleep walk into a situation as bad or worse than the first wave. The mid-July Academy of Medical Sciences report commissioned by the Chief Scientific Adviser set out a reasonable worst case scenario of 119,000 deaths in this second wave excluding those in care homes. We have a choice as to whether we as a nation repeat the mistakes of the past.
We also know that we are not doing enough testing as the positivity rate is so high (7% overall for Pillar 2 tests and up to 15% in some areas such as Liverpool) (see this thread)
So, how do we go about estimating R? Here’s a post I wrote in January explaining R in relation to Covid-19 (which then didn’t have an official name) in relation to Covid-19 (which then didn’t have an official name)
To estimate R, we carry out surveys – which means you pick a representative group of people, either households or individuals, and test them repeatedly. There are two main surveys: ONS and REACT
ONS excludes student halls of residence, as ‘only private residential households, otherwise known as the target population in this bulletin, are included in the sample. People in hospitals, care homes and other institutional settings are not included’. This is confirmed here.
The REACT survey uses GP lists to generate its sample of people who are tested. But of course, new students are only just registering with their GPs, and it is unclear when the GP lists were pulled for the latest study (Round 5 of REACT-1, 18-26 Sep)
We know that halls of residence are a significant driver of transmission.
We may be systematically under-sampling from halls of residence and therefore systematically underestimating R.
The Wall Street Journal is reporting that “New York City on Wednesday will close public schools and nonessential businesses in parts of Brooklyn and Queens that have registered a week-long spike in coronavirus cases”
Let’s look at New York and then compare to a UK city, Liverpool.
Cases are high in some New York boroughs. Up to 216 cases per 100,000 per week. But school closures are also being implemented in areas with 89 cases per 100,000 (source: New York Times)
Let’s compare with Liverpool. Here is the latest @PHE_uk report. Liverpool has cases of 238 cases per 100,000 in a week. Which is slightly higher than the highest rate ZIP code in NYC.
But remember, Liverpool’s figures are for the whole local authority.
Let’s dig a little deeper into Liverpool. Here’s the map. We can see some areas with incidence in excess of 1200 cases per 100,000. That’s very high. And don’t forget this is detected cases. The number of cases will be much higher.
But how do we know that there hasn’t been enough testing? We look at positivity. Positivity is the number of people who test positive divided by the number of people tested. And this is what NYC uses to determine whether schools should be closed.
If an area of NYC has positivity greater than 3% – three in every 100 tests being positive – then schools close. What does positivity tell us? Whether enough tests are being performed.
“the World Health Organization recommended in May that the percent positive remain below 5% for at least two weeks before governments consider reopening.” (Johns Hopkins University)
So, given that positivity is set at a threshold of 3% for school closures in NYC and WHO suggest 5% before reopening, this begs the question – What is the positivity in Liverpool?
Just under 15%, according to the latest published data (PHE week 40 reporting). Which means that around 15% of all tests in Liverpool come back positive. That’s *very high*. And means not enough testing is being carried out. And this is a problem.
This is just an example of a city with large positivity. Extra testing capacity has been sent to Liverpool presumably due to students returning to universities there. This is not a Liverpool problem – it’s a national problem.
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.
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.
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
And sets out what we should have done: – public engagement – extensive public information campaign – tailoring guidance – and…
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.”
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”.
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”
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…”
Now re-read the @uksciencechief‘s report “Even scenarios with Rt in the 1.1-1-5 are likely to stretch the NHS”
But what is this reasonable worst case scenario? Back to the report. Oh, and there’s talk of R being 1.7 again:
“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
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’.
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.
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.