Coronavirus (COVID-19) Infection Survey, UK: 17 December 2021

Estimates for England, Wales, Northern Ireland and Scotland. This survey is being delivered in partnership with University of Oxford, University of Manchester, UK Health Security Agency and Wellcome Trust. This study is jointly led by the ONS and the Department for Health and Social Care (DHSC) working with the University of Oxford and Lighthouse laboratory to collect and test samples.

Nid hwn yw'r datganiad diweddaraf. Gweld y datganiad diweddaraf

Cyswllt:
Email Rhiannon Yapp and Byron Davies

Dyddiad y datganiad:
17 December 2021

Cyhoeddiad nesaf:
To be announced

1. Main points

  • In England, the trend in the percentage of people testing positive was uncertain in the week ending 11 December 2021; we estimate that 936,000 people in England had coronavirus (COVID-19) (95% credible interval: 883,900 to 989,100), equating to around 1 in 60 people.
  • In Wales, the trend in the percentage of people testing positive was uncertain in the week ending 11 December 2021; we estimate that 56,200 people in Wales had COVID-19 (95% credible interval: 44,900 to 68,800), equating to around 1 in 55 people.
  • In Northern Ireland, the percentage of people testing positive for COVID-19 decreased in the week ending 11 December 2021; we estimate that 37,100 people in Northern Ireland had COVID-19 (95% credible interval: 28,700 to 46,800), equating to around 1 in 50 people.
  • In Scotland, the trend in the percentage of people testing positive was uncertain in the week ending 11 December 2021; we estimate that 67,100 people in Scotland had COVID-19 (95% credible interval: 54,300 to 81,600), equating to around 1 in 80 people.
  • In the week ending 11 December 2021, while Delta continues to be the most common variant, the percentage of cases compatible with the Omicron variant (B.1.1.529) increased in England and Scotland, and there were early signs of an increase in Wales.

Within this bulletin, we summarise some of the latest results from the Coronavirus (COVID-19) Infection Survey. For more detailed information on our methods you can view our COVID-19 Infection Survey methodology article. You can also find out more about comparing methods used in the Coronavirus (COVID-19) Infection Survey and NHS Test and Trace in our article, to better understand comparisons in data sources.

About this bulletin

In this bulletin, we refer to the number of current COVID-19 infections within the population living in private residential households. We exclude those in hospitals, care homes and/or other communal establishments. In communal establishments, rates of COVID-19 infection are likely to be different. More information about the COVID-19 pandemic from the Office for National Statistics (ONS) and other sources can be found in our Coronavirus (COVID-19) latest insights.

The positivity rate is the percentage of people who have tested positive for COVID-19 on a polymerase chain reaction (PCR) test at a point in time. We use current COVID-19 infections to mean testing positive for SARS-CoV-2, with or without having symptoms, on a swab taken from the nose and throat. This is different to the incidence rate, which is a measure of only the new PCR positive cases in a given time period. All analysis was produced with our research partners at the University of Oxford.

Our estimates are based on confirmed positive test results. The remaining swabs are either negative, which are included in our analysis, or are inconclusive, which are not included in our analysis. Some swabs are test failures, which are also not included in our analysis. We are working with the laboratories to understand consistency in the identification of inconclusive results, that could be weak positive results. The impact of this on our estimates of positive infections is likely to be very small and unlikely to affect the trend.

More about coronavirus

Early management information from the Coronavirus (COVID-19) Infection Survey is made available to government decision-makers to inform their response to COVID-19. Occasionally we may publish figures early if it is considered in the public interest. We will ensure that we pre-announce any ad hoc or early publications as soon as we can. These will include supporting information where possible to aid user understanding. This is consistent with guidance from the Office for Statistics Regulation (OSR).

How the data in this bulletin can be used

The data can be used for:

  • estimating the number of positive cases among the population living in private households, including cases where people do not report having any symptoms
  • identifying differences in numbers of positive cases between UK countries and different regions in England
  • estimating the number of new cases and change over time in positive cases

The data cannot be used for:

  • measuring the number of cases and infections in care homes, hospitals and/or other communal establishments
  • providing information about recovery time of those infected
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2. Percentage of people who had COVID-19 in England, Wales, Northern Ireland and Scotland

In England and Wales, the trend in the percentage of people testing positive for coronavirus (COVID-19) was uncertain in the week ending 11 December 2021. The percentage of people testing positive in Scotland decreased over the most recent two weeks up to 11 December; however, the trend was uncertain in the most recent week. In Northern Ireland, the percentage of people testing positive for COVID-19 decreased in the week ending 11 December 2021. Our reported headline positivity estimates contain both Omicron (B.1.1.529) and Delta (B.1.617.2 and its genetic descendants) variants.

All estimates are based on statistical modelling of the trend in rates of positive nose and throat swab results. All our estimates are subject to uncertainty given that a sample is only part of the wider population. Therefore, caution should be taken in over-interpreting any small movements in the latest trends.

Notes:
  1. These statistics refer to infections occurring in private households.
  2. All estimates are subject to uncertainty given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis.
  3. The ratios presented are rounded to the nearest 100 if over 1,000, to the nearest 10 if under 1,000, and to the nearest 5 if under 100.
  4. These ratios do not represent a person's risk of becoming infected, since risk of infection depends on a number of factors such as contact with others or whether a person has been vaccinated.

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Because of the relatively small number of tests in Wales, Northern Ireland and Scotland in our sample, credible intervals are wider and therefore results should be interpreted with caution. These wide credible intervals mean that differences between the central estimates within and between nations may appear smaller or more exaggerated than they really are.

Figure 1: The trend for the percentage of people testing positive for COVID-19 was uncertain in England, Wales and Scotland and decreased in Northern Ireland, in the week ending 11 December 2021

Estimated percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs, UK, 12 December 2020 to 11 December 2021

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Notes:
  1. Modelled results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis.
  4. Official reported estimates are plotted at a reference point believed to be most representative of the given week.
  5. The official estimate presents the best estimate at that point in time. Modelled estimates are used to calculate the official reported estimate. The model smooths the series to understand the trend and is revised each week to incorporate new test results, providing the best indication of trend over time.
  6. Official estimates are displayed over a rolling year up to the most recent week. The full time series of our official estimates from 27 April 2020 onwards are available in the Coronavirus (COVID-19) Infection Survey datasets.

Download the data

About our estimates

Our headline estimates of the percentage of people testing positive in England, Wales, Northern Ireland and Scotland are the latest official estimates. We include different measures to support our estimation and this section outlines the appropriate uses of all the approaches.

Official estimates should be used to understand the positivity rate for a single point in time. This is based on the modelled estimate for the latest week and is our best and most stable estimate, used in all previous outputs. The modelled estimate is more suited to understanding the recent trend. This is because the model is regularly updated to include new test results and smooths the trend over time. These modelled estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) and the unweighted sample counts are included in the Coronavirus (COVID-19) Infection Survey datasets. These estimates are produced using a different method of weighting to the model and are available for people who wish to compare infection levels over time in this way. For more information on our methods and quality surrounding the estimates please see our COVID-19 Infection Survey methods article and Quality and Methodology Information report.

All estimates presented in this bulletin are provisional results. As swabs are not necessarily analysed in date order by the laboratory, we have not yet received test results for all swabs taken on the dates included in this analysis. Estimates may therefore be revised as more test results are included.

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3. Sub-national analysis of the number of people who had COVID-19

The percentage of people testing positive for coronavirus (COVID-19) continued to fluctuate across regions in England. In the week ending 11 December 2021, the percentage of people testing positive increased in the East of England and London. In the week ending 11 December 2021, the percentage of people testing positive decreased in the North East and Yorkshire and The Humber. In the same week, the trend in the percentage of people testing positive was uncertain for all other regions. Caution should be taken in over-interpreting any small movements in the latest trend.

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In the data used to produce these estimates, the number of people sampled in each region who tested positive for COVID-19 was low relative to England overall. This means there is a higher degree of uncertainty in the regional estimates for this period, as indicated by larger credible intervals.

Figure 2: The percentage of people testing positive increased in East of England and London, and decreased in the North East and Yorkshire and The Humber, in the week ending 11 December 2021

Estimated daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by region, England, 31 October to 11 December 2021

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Notes:
  1. All results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis.
  4. The credible intervals widen slightly at the end as there is a delay between the swab being taken and reporting of results.
  5. The percentage of people testing positive by region was calculated using a similar modelling approach to the national daily estimates in Section 2: Percentage of people who had COVID-19 in England, Wales, Northern Ireland and Scotland.
  6. The analysis is conducted over a six-week period, which means specific positive cases move into and then out of the sample. This causes variability between estimates over time, which is expected given the lower number of positive tests within each region, compared with England as a whole.

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Sub-regional analysis of the UK

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Sub-regional estimates are based on a different model to our headline national estimates and should not be compared with one another. The number of people sampled in each sub-regional area who tested positive is lower compared with the number testing positive in their respective national samples. This means there is a higher degree of uncertainty in the sub-regional estimates and caution should be taken when interpreting or ranking them.

The percentage of people testing positive for COVID-19 also varies across sub-regions of the UK. In Figure 3, we have presented modelled estimates for sub-regions of England, Wales, Northern Ireland and Scotland in the week ending 11 December 2021.

Figure 3: The percentage of people testing positive for COVID-19 by sub-regions of the UK

Estimated percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by sub-regional geography, UK, 5 to 11 December 2021

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Notes:
  1. All results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis.
  4. Sub-regional estimates are based on a different model to our headline estimates. Our sub-regional estimates are calculated as an average over a seven-day period and should not be compared with our headline positivity estimates, which are for a single reference date. Therefore the subregional figures may differ from the headline estimates because they are averaged over a longer time period. If a trend is changing, the figures shown in Figure 3 may not reflect the change we are seeing in our headline estimates.
  5. We have modelled Wales and Scotland separately to England. Northern Ireland is always modelled separately as it does not share a land border with the other UK countries and so requires a different geospatial modelling approach.

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4. Age analysis of the number of people who had COVID-19

Age analysis by category for England

Our age categories separate children and young people by school age:

  • "aged two years to school Year 6" includes children in primary school and below
  • "school Year 7 to school Year 11" includes children in secondary school
  • "school Year 12 to those aged 24 years" includes young adults who may be in further or higher education

This means that 11- to 12-year-olds and 16- to 17-year-olds have been split between different age categories depending on whether their birthday is before or after 1 September.

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Estimates are based on smaller sample sizes within each age group relative to England overall. There is a higher degree of uncertainty as indicated by larger credible intervals. These can be found in the Coronavirus (COVID-19) Infection Survey: England dataset.

In the week ending 11 December 2021, the percentage of people testing positive for coronavirus (COVID-19) increased for those aged two years to school Year 6, and for those aged 35 to 49 years. In the week ending 11 December 2021, the percentage testing positive decreased for those in school Year 7 to school Year 11, and those aged 50 to 69 years. The trend in the percentage testing positive was uncertain for all other age groups in the week ending 11 December 2021.

The percentage of people testing positive for COVID-19 was highest in school aged children: 5.56% (95% credible interval: 4.88% to 6.28%) of those aged two years to school Year 6 tested positive and 2.82% (95% credible interval: 2.33% to 3.38%) of those in school Year 7 to school Year 11 tested positive in the week ending 11 December 2021.

Figure 4: The percentage of people testing positive for COVID-19 remained highest among those aged 2 years to school Year 6

Estimated daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by age group, England, 31 October 2021 to 11 December 2021

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Notes:
  1. All results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis.
  4. The credible intervals widen slightly at the end as there can be a delay between the swab being taken and reporting of results. Because of this greater uncertainty in the most recent days, we report latest figures based on a reference day during that week. This week the reference day is 8 December 2021.

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Estimates for non-overlapping 14-day periods (which underpin our modelled estimates) by age group are available in our Coronavirus (COVID-19) Infection Survey datasets and are provided as an alternative measure over time for context.

We are unable to produce the same grouped analysis as presented in Figure 4 for the devolved administrations because of smaller sample sizes within each age group. We are able to produce analysis on positivity by single year of age for Wales, Northern Ireland and Scotland using a different model and these estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

Age analysis by single year of age over time by country

Our modelled daily estimates of the percentage testing positive for COVID-19 by single year of age over time for all four UK countries, 31 October to 11 December 2021 can be found in our accompanying dataset. These estimates are produced using a different method to the grouped age analysis for England presented previously and are therefore not comparable. Caution should be taken in over-interpreting small movements in positivity day to day.

Further analysis on age for WalesNorthern Ireland and Scotland is published by their respective statistical agencies. Analysis for Wales is published in English and Welsh.

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5. Number of new COVID-19 infections in England, Wales, Northern Ireland and Scotland

The incidence rate is a measure of new polymerase chain reaction (PCR)-positive cases in a given time period. We include estimates of the incidence rate in our Coronavirus (COVID-19) Infection Survey datasets.

In the week ending 27 November 2021, the number of new PCR-positive COVID-19 cases per day increased in England, decreased in Scotland, and the trend was uncertain in Wales and Northern Ireland. Credible intervals are very wide because of relatively small sample sizes, and care should be taken in interpreting results.

The reference date used for our official estimates of incidence of PCR-positive cases is 14 days before the positivity reference day, meaning that there is a two-week lag between the incidence estimate and the positivity estimate. This is necessary as estimates later than this date are more likely to change as we receive additional data. While we believe that the incidence estimates are useful, they can be volatile and subject to change as more data become available. For more information on how we calculate estimates of incidence please see COVID-19 Infection Survey: methods and further information.

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6. Analysis of viral load and variants of COVID-19

Each week, we publish Cycle-threshold (Ct) values, which indicate viral load and act as a proxy for the strength of the virus. We also break down infections by variant based on gene positivity patterns from our swab tests.

A "cycle threshold", known as a Ct value, are used as a proxy for the quantity of the virus, also known as the viral load. The higher the viral load, the lower the Ct value. These values are helpful for monitoring the strength of the virus and for identifying patterns that could suggest changes in the way the virus is transmitting. The Ct values of coronavirus (COVID-19) positive tests are provided in the technical dataset that accompanies this bulletin.

The Omicron variant (B.1.1.529) of COVID-19 has changes in one of the three genes that coronavirus swab tests detect, known as the S-gene. This means in cases compatible with the Omicron variant, the S-gene is no longer detected by the current test. When there is a high viral load (for example, when a person is most infectious), absence of the S-gene in combination with the presence of the other two genes (ORF1ab and N-genes) is a reliable indicator of the Omicron variant (B.1.1.529). However, as the viral load decreases (for example, if someone is near the end of their recovery from the infection), the absence of the S-gene is a less reliable indicator of the Omicron variant.

The World Health Organization (WHO) have defined names for Variants of Concern. These are variants that the UK government has under surveillance. You can find out more in the latest SARS-CoV-2 variants of concern and variants under investigation in England briefing document.

UK Variants of Concern:

  • Alpha: B.1.1.7
  • Beta: B.1.351
  • Gamma: P.1
  • Delta: B.1.617.2 and its genetic descendants
  • Omicron: B.1.1.529 (which includes sublineages BA.1, BA.2 and BA.3)

Infections compatible with the Delta variant have been the most common since the end of May 2021 in England, and since the end of July 2021 in all four UK countries. In the most recent four weeks up to 29 November 2021, results show over 99% of all coronavirus (COVID-19) infections, from which we obtained a genetic sequence, were genetically compatible with the Delta variant or a descendant of the Delta variant.

The following analysis looks at the percentage of positive tests that are compatible with the Omicron variant and Delta variant of the virus in England, Wales and Scotland, and the regions of England. Estimates for Northern Ireland have not been provided in this bulletin, as we do not have enough data to provide a breakdown of positivity by variant at this stage.

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Data should be treated with caution. In particular, there are small numbers of positive cases detected in Wales and Scotland leading to considerable uncertainty surrounding these estimates. There are further uncertainties given that not all cases that are positive on the ORF1ab and N-genes will be the Omicron variant.

In the week ending 11 December 2021, the percentage of cases compatible with the Omicron variant (B.1.1.529) increased in England and Scotland, and there were early signs of an increase in Wales. For the same week, the percentage of cases compatible with the Delta variant (B.1. 617.2 and its genetic descendants) decreased in England and Scotland, and the trend was uncertain in Wales.

Figure 5: The percentage of cases compatible with the Omicron variant has increased in England and Scotland, and showed early signs of an increase in Wales, in the week ending 11 December 2021

Modelled percentage of positive cases compatible with the Delta variant, compatible with the Omicron variant and where the virus is too low for the variant to be identifiable, based on nose and throat swabs, daily, from 31 October to 11 December 2021, UK

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Notes:
  1. All results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. Omicron variant compatible positives are defined as those that are positive on the ORF1ab-gene and N-gene, but not the S-gene. Delta variant compatible positives are defined as those that are positive on the ORF1ab, N-gene and S-gene. Positives where the virus is too low for the variant to be identifiable are defined as those that are positive with all other gene patterns. These definitions are regardless of cycle threshold (Ct) value.
  4. Data should be treated with caution. There are several variants with gene pattern ORF1ab+N, and many with pattern S+ORF1ab+N. We label these as Omicron compatible and Delta compatible respectively. At present, Delta compatible is the dominant variant in the UK. This means that most cases with pattern S+ORF1ab+N will be the Delta variant, but also that some portion of cases with pattern ORF1ab+N will be Delta variant cases where the S gene was not detected for other reasons.
  5. Cases where the virus is too low for the variant to be identifiable are likely to be people very recently infected or those who are recovering from their infection; people who get new infections after vaccination may also be in this group.

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In the week ending 11 December 2021, the percentage of cases compatible with the Omicron variant (B.1.1.529) increased in the North West, East of England, London, South East and South West. The trend in the percentage of cases compatible with the Omicron variant (B.1.1.529) was uncertain for the remaining regions in the same week.

In the week ending 11 December 2021, the percentage of cases compatible with the Delta variant (B.1. 617.2 and its genetic descendants) decreased in the North East, Yorkshire and The Humber and the South East, and the trend was uncertain for the remaining regions.

Caution should be taken in over-interpreting any small movements in the latest trend. In particular, these regional data have small numbers of positive cases compatible with the Omicron variant (B.1.1.529), leading to considerable uncertainty surrounding these estimates.

Figure 6: The percentage of cases compatible with the Omicron variant increased in the North West, East of England, London, South East and South West, in the week ending 11 December 2021

Modelled percentage of positive cases compatible with the Delta variant, compatible with the Omicron variant and where the virus is too low for the variant to be identifiable, based on nose and throat swabs, daily, from 31 October to 11 December 2021, England

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Notes:
  1. All results are provisional and subject to revision.
  2. These statistics refer to infections occurring in private households.
  3. Omicron variant compatible positives are defined as those that are positive on the ORF1ab-gene and N-gene, but not the S-gene. Delta variant compatible positives are defined as those that are positive on the ORF1ab, N-gene and S-gene. Positives where the virus is too low for the variant to be identifiable are defined as those that are positive with all other gene patterns. These definitions are regardless of cycle threshold (Ct) value.
  4. Data should be treated with caution. There are several variants with gene pattern ORF1ab+N, and many with pattern S+ORF1ab+N. We label these as Omicron compatible and Delta compatible respectively. At present, Delta compatible is the dominant variant in the UK. This means that most cases with pattern S+ORF1ab+N will be the Delta variant, but also that some portion of cases with pattern ORF1ab+N will be Delta variant cases where the S gene was not detected for other reasons.
  5. Cases where the virus is too low for the variant to be identifiable are likely to be people very recently infected or those who are recovering from their infection; people who get new infections after vaccination may also be in this group

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Our Coronavirus (COVID-19) Infection Survey: technical dataset contains several tables relating to analysis on variants, including the genetic lineages of the virus seen in the samples we sequence. More information on how we measure variants from positive tests on the survey can be found in our Understanding COVID-19 Variants blog. Our COVID-19 Infection Survey methods article gives more detail about how we sequence the virus' genetic material.

The sequencing is produced by Northumbria University and analysis is produced by research partners at the University of Oxford. Of particular note are Dr Katrina Lythgoe, Dr David Bonsall, Dr Tanya Golubchik, and Dr Helen Fryer. Genome sequencing is funded by the COVID-19 Genomics UK (COG-UK) consortium. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research and Innovation (UKRI), the National Institute of Health Research (NIHR), and Genome Research Limited operating as the Wellcome Sanger Institute.

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7. Test sensitivity and specificity

The estimates provided in Sections 2 to 6 are for the percentage of the private-residential population testing positive for coronavirus (COVID-19), otherwise known as the positivity rate. We do not report the prevalence rate. To calculate the prevalence rate, we would need an accurate understanding of the swab test's sensitivity (true-positive rate) and specificity (true-negative rate).

While we do not know the true sensitivity and specificity of the test, our data and related studies provide an indication of what these are likely to be. In particular, the data suggest that the false-positive rate is very low - under 0.005%. We do not know the sensitivity of the swab test. However, other studies suggest that sensitivity (the rate of true-positive test results) may be somewhere between 85% and 98%.

You can find more information on sensitivity and specificity in our COVID-19 Infection Survey methods article and our blog that explains why we trust the data from the COVID-19 infection survey. You can find more information on the data suggesting that our test's false-positive rate is very low in a paper written by academic partners at the University of Oxford.

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8. Coronavirus (COVID-19) Infection Survey data

Coronavirus (COVID-19) Infection Survey: England
Dataset | Released 17 December 2021
Findings from the Coronavirus (COVID-19) Infection Survey for England.

Coronavirus (COVID-19) Infection Survey: Northern Ireland
Dataset | Released 17 December 2021
Findings from the Coronavirus (COVID-19) Infection Survey for Northern Ireland.

Coronavirus (COVID-19) Infection Survey: Scotland
Dataset | Released 17 December 2021
Findings from the Coronavirus (COVID-19) Infection Survey for Scotland.

Coronavirus (COVID-19) Infection Survey: Wales
Dataset | Released 17 December 2021
Findings from the Coronavirus (COVID-19) Infection Survey for Wales.

Coronavirus (COVID-19) Infection Survey: technical data
Dataset | Released 17 December 2021
Technical and methodological data from the Coronavirus (COVID-19) Infection Survey, England, Wales, Northern Ireland and Scotland.

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9. Collaboration

Logos for London School of Hygiene and Tropical Medicine and Public Health England

The Coronavirus (COVID-19) Infection Survey analysis was produced by the Office for National Statistics (ONS) in collaboration with our research partners at the University of Oxford, the University of Manchester, UK Health Security Agency (UK HSA) and Wellcome Trust. Of particular note are:

  • Sarah Walker - University of Oxford, Nuffield Department for Medicine: Professor of Medical Statistics and Epidemiology and Study Chief Investigator
  • Koen Pouwels - University of Oxford, Health Economics Research Centre, Nuffield Department of Population Health: Senior Researcher in Biostatistics and Health Economics
  • Thomas House - University of Manchester, Department of Mathematics: Reader in Mathematical Statistics
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10. Glossary

Confidence interval

A confidence interval gives an indication of the degree of uncertainty of an estimate, showing the precision of a sample estimate. The 95% confidence intervals are calculated so that if we repeated the study many times, 95% of the time the true unknown value would lie between the lower and upper confidence limits. A wider interval indicates more uncertainty in the estimate. Overlapping confidence intervals indicate that there may not be a true difference between two estimates. For more information, see methodology page on statistical uncertainty.

Credible interval

A credible interval gives an indication of the uncertainty of an estimate from data analysis. The 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

Cycle threshold (Ct) values

The strength of a positive COVID-19 test is determined by how quickly the virus is detected, measured by a cycle threshold (Ct) value. The lower the Ct value, the higher the viral load and stronger the positive test. Positive results with a high Ct value can be seen in the early stages of infection when virus levels are rising, or late in the infection, when the risk of transmission is low.

False-positives and false-negatives

A false-positive result occurs when the tests suggest a person has coronavirus (COVID-19) when in fact they do not. By contrast, a false-negative result occurs when the tests suggest a person does not have COVID-19 when in fact they do. For more information on false-positives and false-negatives, see our methods article and our blog.

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11. Measuring the data

Reference dates

We aim to provide the estimates of positivity rate (the percentage of those who test positive) and incidence that are most timely and most representative of each week. We decide the most recent week we can report on based on the availability of test results for visits that have already happened, accounting for the fact that swabs have to be couriered to the labs, tested and results returned. On most occasions, the reference dates align perfectly, but sometimes this is not feasible. This week, the reference week for positivity is 5 to 11 December 2021.

Within the most recent week, we provide an official estimate for positivity rate based on a reference point from the modelled trends. For positivity rates, we can include all swab test results, even from the most recent visits. Therefore, although we are still expecting further swab test results from the labs, there was sufficient data for the official estimate for infection to be based on a reference point after the start of the reference week. To improve stability in our modelling while maintaining relative timeliness of our estimates, we are reporting our official estimates based on the midpoint of the reference week. This week, the reference day for positivity rates is Wednesday 8 December 2021.

The reference date used for our official estimates of incidence of polymerase chain reaction (PCR)-positive cases is 14 days prior to the positivity reference day. This is necessary as estimates later than this date are more likely to change as we receive additional data. This week, the reference week for incidence is 21 to 27 November 2021 and the reference day is Wednesday 24 November 2021.

Response rates

Response rates for England, Wales, Northern Ireland and Scotland cannot be regarded as final response rates to the survey since those who are invited are not given a time limit in which to respond, and different modes of sampling are not comparable. Response rates for each nation are found in the Coronavirus (COVID-19) Infection Survey: technical dataset. We provide response rates separately for the different sampling phases of the study. Additional information on response rates can be found in our COVID-19 Infection Survey methods article.

Survey fieldwork

Survey fieldwork for the pilot study began in England on 26 April 2020. In Wales, fieldwork began on 29 June 2020, in Northern Ireland fieldwork began on 26 July 2020 and in Scotland fieldwork began on 21 September 2020.

Sub-regional geographies

We have presented modelled estimates for the most recent week of data at the sub-regional level. To balance granularity with statistical power, we have grouped together local authorities into COVID-19 Infection Survey sub-regions. The geographies are a rules-based composition of local authorities, and local authorities with a population over 200,000 have been retained where possible.

The boundaries for these COVID-19 Infection Survey sub-regions can be found on the Open Geography Portal.

Other Coronavirus Infection Survey (CIS) analysis and studies

This study is one of a number of studies that look to provide information around the coronavirus pandemic within the UK. For information on other studies see Section 11: Measuring the data in our previous bulletin dated 30 April 2021.

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12. Strengths and limitations

These statistics have been produced quickly in response to developing world events. The Office for Statistics Regulation (OSR), on behalf of the UK Statistics Authority, has reviewed them on 14 May 2020 and 17 March 2021 against several important aspects of the Code of Practice for Statistics and regards them as consistent with the Code's pillars of trustworthinessquality and value.

The estimates presented in this bulletin contain uncertainty. There are many sources of uncertainty, including uncertainty in the test, in the estimates and in the quality of data collected in the questionnaire. Information on the main sources of uncertainty are presented in our Coronavirus (COVID-19) Infection Survey Quality and Methodology Information report, our methodology article, and our blog that explains why we trust the data from the COVID-19 infection survey.

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Manylion cyswllt ar gyfer y Bwletin ystadegol

Rhiannon Yapp and Byron Davies
infection.survey.analysis@ons.gov.uk
Ffôn: +44 1633 560499