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expert reaction to latest data from the ONS COVID-19 Infection Survey

The Office for National Statistics (ONS) have released the latest data from their COVID-19 Infection Survey.


Prof Kevin McConway, Emeritus Professor of Applied Statistics, The Open University, said:

“Today’s weekly update from ONS on their Coronavirus Infection Survey (CIS) brings the estimates of the numbers of people who would test positive for the virus at any one time, the positivity or prevalence, up to the week ending 15 January, and the estimate of the number of new infections each day, the incidence, up to the week ending 1 January. (The incidence figures are always two weeks behind the prevalence figures, for technical reasons.)

“The headline results on prevalence were published early, as ONS have done for some weeks now, on Wednesday (19th January). I commented on them* when they came out, and those comments still apply to the more detailed release today. Briefly, the good news is that numbers who would test positive in the week ending 15 January were falling in England, Scotland and Wales, though the trend was uncertain in the most recent week in Northern Ireland. Also, infection levels were falling in seven of the nine regions of England and, in England, in all but one of the age groups that ONS use. In fact, these encouraging signs are, if anything, made more encouraging in the more detailed release today. The daily modelled estimates for the places where the latest trend was said to be uncertain in the weekly official estimates – Northern Ireland, North East England and South West England – are also showing decreases in the most recent days covered (up to 15 January), even though the statistical uncertainty that always arises with survey results means that these falling trends really are uncertain. The bad news is that infection rates across all the UK countries, the English regions and age groups do remain very high, and also that the trend in infections in the youngest age group (age 2 to school year 6) is still upwards. Overall, though, an encouraging picture.

“The incidence results don’t appear in the headline release, presumably because they aren’t so prompt, and maybe also because the margins of statistical uncertainty are relatively wider than for the prevalence. But there’s some encouraging news here too. The official weekly estimates don’t look wonderful – the total of the ONS estimates for daily infections in the week 26 December to 1 January was 479,100, so not all that much short of half a million new infections each day, and a third higher than the previous week. But we know from other sources such as the Government dashboard that cases were rising very fast then. The encouraging news is that, for all four UK countries, the daily modelled incidence rate estimated from the CIS had begun to fall, for the latest few dates included in the release (up to 5 January). There’s a lot of statistical uncertainty, particularly for Northern Ireland where the number of people swabbed for the survey is relatively small, and also in Northern Ireland the downturn in the daily estimates only happens on the very last day included. So we really can’t be certain of these trends yet on the basis of CIS results – but generally they do seem to be confirming the impression given by the daily confirmed cases numbers on the Government dashboard (which are a different kind of incidence estimate), that the peak of new infections passed at around the turn of the year. That doesn’t mean infections are falling absolutely everywhere in the UK or in every age group – the CIS doesn’t provide incidence estimates for regions or age groups – but it’s pretty good news nevertheless.

“As always, these estimated daily numbers of new infections are a lot higher than the figure for new confirmed cases on the Government dashboard. That’s because those confirmed case counts include only people who tested positive as part of routine testing, and not everyone who is infected has a routine test. Just to show the size of the difference, the total of the daily modelled estimates of new infections from the CIS every day, for the latest week for which they provided these estimates today (30 December to 5 January), is almost exactly 3 million (or about 430,000 new infections each day that week, on average). The margin of uncertainty around that figure is quite wide. But the number of new confirmed cases on the dashboard for the UK for the same week was about 1.3 million. Even allowing for the margin of error in the survey results, it’s very clear that the confirmed case count misses a large proportion of new infections, very probably more than half of them.”



Prof James Naismith, Director of the Rosalind Franklin Institute, and Professor of Structural Biology, University of Oxford, said:

“Today’s release has more detail than the headline figures on Wednesday and covers the week to 15th January.

“Prevalence has dropped in all home nations with 50 per 1000 people in England, NI & Scotland and 40 in Wales.

“Based on what was seen in South Africa and can be seen in London and North West, prevalence will start to fall rapidly.

“Omicron for the unvaccinated and vulnerable remains a potentially serious disease. At peak over 2000 a people a day were hospitalised with covid19 and deaths look to be at their peak at an average of around 2000 in a week.

“The hospitalisations  has burdened an already stretched care system and the deaths represent personal tragedies.

“The very high prevalence has exposed a large number of people to the risk of long covid, we can only hope this is less common with omicron.

“Omicron as expected was less severe in the vaccinated or those with previous infection, it was even less severe for the triple boosted.

“By the time South African data clearly showed that Omicron was intrinsically less severe than Delta, Omicron had hit the UK.

“The triple boost campaign has saved lives and lowered the pressure on the NHS. I believe vaccination is the best way to keep covid19 at bay.

“The deployment of new medicines to treat severe disease is encouraging. 

“As we look back on the Omicron wave, there are lessons to learn:

1 Given the immunity in the population from vaccination and the progress of the booster, we were very unlikely to see deaths spiral to thousands a day. It was not impossible but the low probability should have been more clearly communicated.

2 Partial travel bans, once a variant of concern is detected, serve only PR purposes. It was disappointing to see them imposed and supported by some scientists in the face of the evidence of their lack of utility.

3 Modelling is vital but can only ever present a range of future scenarios, the science community needs to find a better way to explain this. It was very dispiriting and dangerous to see bad faith actors attack the modellers as a means to advance their political goals. 

4 Despite the advanced warning from South Africa, almost two years of experience, early imposition of plan B and existing measures the Omicron wave reached an astounding prevalence in only a few weeks. It did so whilst we were unsure of its severity. Had it been more severe, we would have been in dire straits. Our entire system of pandemic preparedness (from public policy to debate to track /trace and hospital capacity) is not fit for purpose. Omicron should be a flashing red light or a blaring klaxon. 

5 A more honest assessment of NPIs is needed, there was a tendency for these to become politicised and consequently tribalised. The harsh realities of the virus are not susceptible to political posturing. Certainly it is hard to build a compelling case that short of a lockdown we have found a way to control spread of something as infectious as Omicron.”



All our previous output on this subject can be seen at this weblink:



Declared interests

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.”

None others received.

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