The Office for National Statistics (ONS) have released the latest data from their COVID-19 Infection Survey.
Prof James Naismith, Director of the Rosalind Franklin Institute, and Professor of Structural Biology, University of Oxford, said:
“Today’s ONS data cover the period to 31 December. The ONS is now giving a snapshot on the Wednesday with fuller analysis on Friday.
“The headlines are more useful to policy makers, so release on Wednesday means they are more current.
“It is always worth looking at the full data to try to learn lesson for the future. What can we learn?
“Omicron has spread rapidly up to 31st Dec, reaching prevalence of around just under 7 in 100 in England and 5 in 100 Scotland & Wales; 4 in 100 in Northern Ireland.
“Within England, prevalence varies just below 4 in the South West to 9 in 100 in London. A wider range than seen between the home nations.
“The fall in London is encouraging and mirrors South Africa, it also sets an upper limit elsewhere in the UK. This upper limit will seriously stretch NHS and society where it is reached..
“That Omicron could have been worse should not blind us to some important observations that might help us in the future.
(1) We were unable to meaningfully control the spread of a highly infectious virus despite warning; the prevalence is staggering. The public sphere struggles to make decisions, a wait and see approach with a rapidly spreading virus should be better understood as decision to hope for the best. Obviously a more severe virus would have had dire consequences.
(2) Many of our control measures do not work despite nearly two years of effort. Track and trace did very little if anything to blunt omicron, it spreads as rapidly here as everywhere else. We have been unable to implement quite simple long term beneficial control measures such as ventilation. Other effective measures such as universal masking have proven particularly effective at generating hot air. Lack of compliance with and / or broad exceptions in public areas to masking renders it much less effective.
(3) The virus tends to be uninterested in clever rhetoric and political boundaries. The tendency to attack modelling or modellers is a means to obfuscate not illuminate the choices we face. Our failure to agree on island wide policies on an island with free movement creates an opportunity for both politicians and the virus.
“I would add Omicron is less severe than Delta (hospitalisations per 1000 cases), particularly in the vaccinated and previously infected. The most effective defence is immunisation; boosters reduce the risk of infection.
“It is my hope that Omicron causes less long covid and that those it does cause are less severe, given the very high numbers of infections.
“Efforts to understand and treat long covid19 are likely to be very important for society.
“The modelling of the spread of Omicron has largely proven correct. Many scientists, including myself, hoped and expected that with vaccines it would be prove to be a less severe disease and there were encouraging signs from South Africa. However, we only knew this quite recently, modelling has to consider all possibilities.
“With the arrival of effective therapeutics, there is an end to severe covid19. However, the costs to the UK, 150, 000 dead, around 1 million long covid, disruption to lives and economic dislocation demand we do better next time.”
Prof Kevin McConway, Emeritus Professor of Applied Statistics, The Open University, said:
“Today’s standard weekly release from the ONS Coronavirus Infection Survey (CIS) takes the date up to the last week in December. ONS have started publishing the main headline results and data earlier in the week, so most of the key results for that last week in December already appeared on Wednesday 5 December, and my comments on those (with others) are on the SMC website*.
“There are some new things in today’s release that didn’t appear on Wednesday, and there’s also one thing that was in the Wednesday release but is not here. I have also added a comment (at the end) about a change, announced today, in this week’s ONS release on death registrations in England and Wales.
“In my view, the main interesting new data today are those on incidence – that is, estimates of the daily numbers of new infections. Most of the CIS results relate to what’s called prevalence – the estimated numbers of people who are infected at a given time. (To be precise, these are estimates of the numbers who would test positive on a PCR test, which isn’t quite the same thing, but PCR tests are pretty accurate and it’s the best we can get.) The prevalence figures will include people who have just got a detectable infection on the day in question, but also people who have already been infected for a few days or even, in some cases, a few weeks. The incidence results aim to estimate how many people became infected daily. So they ought to correspond, for instance, to the numbers of new confirmed cases on the Government dashboard at coronavirus.data.gov.uk.
“CIS incidence estimates are never as up to date as the prevalence figures, because they depend more on having the latest swab results. They are also statistically less precise, inevitably so because of the way the survey works. So the latest estimates are for the week 11-17 December, even though the prevalence figures go up to the week ending 31 December. It’s particularly interesting to look at those figures this week, because new cases have been rising so fast according to all other data sources, and also because no new incidence estimates have been published by ONS since 17 December (taking the incidence data only up to 27 November).
“The new incidence results for the week 11-17 December give a total number of daily new infections, for the whole UK, of 221,200. Of those estimated daily cases, the great majority (197,500 of them) were in England (with 7,300 a day in Wales, 4,600 in Northern Ireland, and 11,800 in Scotland). Though these results are the average for the whole of that week, I must emphasise that they estimate daily numbers of new cases. Over 220,000 new cases each day is an extremely high number indeed. The rate of new cases that week is the highest since the CIS began in three of the UK countries, and only just misses being the highest ever in Wales by a very small amount. The average daily number of new confirmed cases on the Government dashboard for that week was about 80,400, a great deal smaller. Even though there’s considerable statistical uncertainty in the CIS estimate, that uncertainty comes nowhere near accounting for the very big difference compared to the dashboard confirmed case counts. So it’s apparent that the confirmed case figures are missing a lot of new infections. That’s no surprise – it’s been the general position since the CIS began.
“The CIS data release on Wednesday gave estimates, just for London, of the percentage of infected people for each single year of age and each day. (All infected people, not just new infections.) There is no equivalent for other English regions in today’s release, though there are figures for single years of age and single days for the whole of the country. Perhaps it’s wise not to go into more detail. ONS were very cautious about the interpretation of those London figures, because of the very wide margins of error in the estimates. Others did take them to show that infection rates had peaked in younger people in London, around Christmas Day, though the trends in older people weren’t so optimistic. That might be true but it might well have been over-interpreting the data, because of the statistical uncertainty, and we’ll eventually see.
“However, we can’t look in the same way at other regions anyway, because the results haven’t been released. There are some estimates in today’s release that divide the population up by both age group and regions, but they give estimates only for whole fortnights, so the most recent comparison that can be made is between 4-17 December and 18-31 December. Those figures essentially show infection rates rising in all regions and age groups, even in London. We’ll have to wait longer to see how the data by age group change over time within regions.
“I’ll mention another ONS release today. The weekly release of provisional numbers of death registrations in England and Wales, for deaths from all causes and deaths involving Covid-19, appears weekly, usually on Tuesdays but this week’s release was on Wednesday 5 January because of the bank holiday. Wednesday’s release provided a little optimism amongst the general gloom on Covid data, because it said that the death registrations involving Covid for the most recent available week, ending 24 December, had decreased compared to the previous week. That would have made it the sixth week in a row that Covid-related death registrations had fallen compared to the week before, and the fall was really pretty substantial, 22% compared to the previous week.
“That large fall wasn’t in accord with the main figures for deaths on the Government dashboard, though they are defined in a different way and generally I would consider the figure defined by death registrations to be more accurate and appropriate.
“However, it turns out that any optimism based on those figures was misplaced. Today ONS announced that there was quite a substantial error in the 5 January release, because of “an issue with [their] automated coding system”. I should say that errors by ONS on a substantial scale are really uncommon, and they have acknowledged this one very promptly and published** a corrected version.
“In the corrected version, the numbers of deaths from all causes have barely changed (one additional registration recorded in Wales). But the number of deaths where Covid-19 is mentioned on the death certificate, in the week ending 24 December, has been revised upwards to 852. (The previous incorrect number was given as 591.) This means that the number of Covid-related registrations for that week was 13% higher than the previous week. That’s disappointing, and emphatically ends the run of decreasing numbers of Covid-related deaths, but at least it is more in accord with other Covid data.”
All our previous output on this subject can be seen at this weblink:
Prof Kevin McConway: “I am a Trustee of the SMC and a member of its Advisory Committee. I am also a member of the Public Data Advisory Group, which provides expert advice to the Cabinet Office on aspects of public understanding of data during the pandemic. My quote above is in my capacity as an independent professional statistician.”