Coronavirus (COVID-19) Infection Survey, UK: 4 March 2022

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 Office for National Statistics (ONS) and the Department for Health and Social Care (DHSC) working with the University of Oxford and Lighthouse laboratory to collect and test samples. 

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Contact:
Email Kara Steel and Mike Bracher

Release date:
4 March 2022

Next release:
11 March 2022

1. Main points

  • In England, the percentage of people testing positive for coronavirus (COVID-19) continued to decrease in the week ending 26 February 2022; we estimate that 1,933,500 people in England had COVID-19 (95% credible interval 1,861,700 to 1,992,300), equating to 3.55% of the population or around 1 in 30 people.

  • In Wales, the percentage of people testing positive for COVID-19 decreased in the two weeks up to 26 February 2022, but the trend was uncertain in the most recent week; we estimate that 94,200 people in Wales had COVID-19 (95% credible interval: 80,000 to 109,700), equating to 3.10% of the population or around 1 in 30 people.

  • In Northern Ireland, the percentage of people testing positive for COVID-19 decreased in the week ending 26 February 2022; we estimate that 106,300 people in Northern Ireland had COVID-19 (95% credible interval: 90,700 to 123,700), equating to 5.79% of the population or around 1 in 17 people.

  • In Scotland, the percentage of people testing positive for COVID-19 increased in the week ending 26 February 2022; we estimate that 280,500 people in Scotland had COVID-19 (95% credible interval: 251,800 to 311,900), equating to 5.33% of the population or around 1 in 19 people.

  • In the week ending the 26 February 2022, the percentage of infections compatible with the Omicron BA.2 variant increased in England, Wales, and Scotland and decreased in Northern Ireland; the percentage of cases compatible with the Omicron BA.1 variant decreased in England, Wales, and Northern Ireland and increased in Scotland over the same period.

We are currently working with a temporary issue affecting statistical processing. This means that this publication does not include all results normally released in our Friday publication. This has been noted in the relevant sections. These results will be reintroduced as soon as possible.

Within this bulletin, we summarise some of the latest results from the Coronavirus (COVID-19) Infection Survey. For more detailed information on our methods see our Coronavirus (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. The impact of excluding inconclusive results 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. During the period of high infections from the start of 2022, we temporarily published early headline results on Wednesdays. We have now stopped this temporary publication, but will continue to regularly review. 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

The results in this bulletin are:

  • provisional and subject to revision

  • based on infections occurring in private households

  • subject to uncertainty, a credible or confidence interval gives an indication of the uncertainty of an estimate from data analysis

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2. Percentage of people who had COVID-19 in UK countries

In this publication, the reference week is 20 to 26 February 2022 for England, Wales, Northern Ireland, and Scotland.

In England and Northern Ireland, the percentage of people testing positive for coronavirus (COVID-19) decreased in the week ending 26 February 2022. In Wales the percentage of people testing positive decreased in the two weeks up to 26 February 2022, but the trend was uncertain in the most recent week. In Scotland, the percentage of people testing positive for COVID-19 continued to increase in the week ending 26 February 2022. Our positivity estimates contain Omicron BA.1 and BA.2 variants and all other variants.

All estimates are based on statistical modelling of the trend in rates of positive nose and throat swab results. All estimates are subject to uncertainty given that a sample is only part of the wider population. Additionally, the estimates for the very latest days may change as more test results are received. Therefore, caution should be taken in over-interpreting small movements in the latest trends.

Notes:
  1. The ratios presented are rounded to the nearest 100 if over 1,000, to the nearest 10 if under 1,000, to the nearest 5 if under 100 and to 1 if under 20. This may result in credible intervals that appear to be similar to the estimated average ratio.
  2. These ratios do not represent a person's risk of becoming infected, since risk of infection depends on a number of factors including contact with others or vaccination status.

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Because of a relatively smaller number of tests in Wales, Northern Ireland and Scotland in the sample, credible intervals are wider and results should be interpreted with caution. 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 percentage of people testing positive for COVID-19 decreased in England and Northern Ireland, increased in Scotland and the trend was uncertain in Wales in the most recent week

Estimated percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs, UK, 7 March 2021 to 26 February 2022

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Notes:
  1. Official reported estimates are plotted at a reference point believed to be most representative of the given week.

  2. Official estimates present 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.

  3. 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.

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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 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.

For more information on our methods and quality surrounding the estimates please see our Coronavirus (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 percentage of people who had COVID-19

In the week ending 26 February 2022, the percentage of people testing positive for coronavirus (COVID-19) remained high across all regions of England. The percentage testing positive increased in the South West in the week ending 26 February 2022. In the same week the percentage of people testing positive decreased in the North East, North West, Yorkshire and The Humber, East Midlands, London and the South East. The percentage of people testing positive has decreased in the West Midlands and the East of England in the two weeks up to 26 February 2022, however the trend is uncertain in the most recent week.

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, as indicated by larger credible intervals.

Figure 2: The percentage of people testing positive for COVID-19 decreased in most regions except the South West, West Midlands, and East of England in the week ending 26 February 2022

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by region, England, 16 January to 26 February 2022

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Notes:
  1. Credible intervals widen slightly at the end as there is 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 the reference day for that week.

  2. 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.

  3. The analysis is conducted over a six-week period, which means specific positive cases move in and out of the sample. This causes variability between estimates over time, which is expected given the lower number of positive tests in each region, compared with England as a whole.

  4. We describe trends by comparing the probability that the estimate for the reference day is higher or lower than the estimate for 7 and 14 days prior.

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Sub-regional analysis of the UK

We are currently working to resolve a temporary issue affecting statistical processing. Therefore sub-regional analyses have not been updated this week. Previous data that presents sub-regional breakdowns can be found in the Coronavirus (COVID-19) Infection Survey: England dataset.

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

Age analysis by category for England

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

  • "aged 2 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

Those aged from 11 to 12 years and those aged 16 to 17 years 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 26 February 2022, the percentage of people testing positive for coronavirus (COVID-19) decreased for all age groups except those aged 70 years and over. The percentage of people testing positive continued to fluctuate for those aged 70 years and over, with an increase in the most recent week.

Figure 3: The percentage of people testing positive decreased for all age groups except for those aged 70 years and over in the week ending 26 February 2022

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by age group, England, 16 January to 26 February 2022

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Notes:
  1. 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 the reference day for that week.

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We are unable to produce the same grouped analysis as presented in Figure 3 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 following section and the Coronavirus (COVID-19) Infection Survey datasets.

Age analysis by single year of age over time by country

In this section, we present modelled daily estimates of the percentage testing positive for COVID-19. These estimates are by single year of age over time from 16 January to 26 February 2022 for all four UK countries. They 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.

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Estimates are based on smaller sample sizes within each age group in comparison with the total sample size for each country. There is a higher degree of uncertainty as indicated by larger confidence intervals. These can be found in the Coronavirus (COVID-19) Infection Survey datasets.

The data presented in Figure 4 for England suggest that the percentage of people testing positive has decreased for all ages except for those aged 70 years and over in the most recent week.

In Wales, the trend in the percentage of people testing positive was uncertain for all ages in the most recent week.

In Northern Ireland, the percentage of people testing positive has decreased among children and young adults and there are possible early signs of an increase in those aged 70 years and over in the most recent week.

In Scotland, the percentage of people testing positive shows early signs of an increase in those around age 30 years and those around age 60 years in the most recent week, while the trend is uncertain among children and younger adults.

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

Figure 4: The percentage testing positive for COVID-19 by single year of age over time for England, Wales, Northern Ireland and Scotland

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by single year of age, UK, 16 January to 26 February 2022

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Notes:
  1. These estimates use a different method to modelled daily estimates of the percentage testing positive by age group for England in the previous section and are therefore not comparable.

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5. Number of new COVID-19 infections in UK countries

We are currently working to resolve a temporary issue affecting statistical processing. Therefore incidence analyses have not been updated this week. Previous estimates of incidence can be found in the Coronavirus (COVID-19) Infection Survey: England dataset.

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

We publish weekly Cycle-threshold (Ct) values and a breakdown of infections by variant, based on gene positivity patterns from our swab tests. The "Cycle threshold", known as a Ct value, is a proxy for the quantity of virus (also known as viral load), where a lower Ct value indicates higher viral load. We are currently working to resolve a temporary issue affecting our statistical processing. Therefore, Ct values have not been updated this week. Previous data on Ct values can be found in the technical dataset for this bulletin.

The Omicron variant BA.1 has changes in one of the three genes that the coronavirus swab test used in the survey detects, known as the S-gene, which means 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), not detecting the S-gene in combination with detecting the other two genes (ORF1ab and N-genes) is a reliable indicator of this Omicron BA.1 variant. However, as the viral load decreases (for example, if someone is near the end of their recovery from the infection), not detecting the S-gene is a less reliable indicator of this Omicron variant. The sub-variant Omicron BA.1.1 also mostly has gene pattern ORF1ab + N. Therefore, gene pattern matching used in our main variant analysis cannot distinguish between Omicron BA.1 and Omicron BA.1.1.

The Omicron variant BA.2 does not have changes in the S-gene, and therefore all three genes, or the S-gene and either ORF1ab or N, will usually be detected in infections with this variant. Delta also does not have changes in the S-gene, and therefore the same sets of genes will usually be detected with Delta and Omicron BA.2. However, our genome sequencing analysis shows that a clear majority of cases where we detect the S-gene are now Omicron BA.2, with relatively few being Delta. For this reason, we now label cases with gene patterns ORF1ab + N + S, ORF1ab + S and N + S as "compatible with the Omicron BA.2 variant" in our main variant analysis. This is because estimates are now likely to mostly reflect trends in BA.2, although Delta may still be having a very small impact.

Up to the 13 February, 75.7% of all sequenced COVID-19 infections from the survey were compatible with the Omicron BA.1 variant or its sub-variants, and 24.3% were compatible with the Omicron BA.2 variant. Our latest complete sequenced data lags the main variant analysis and these percentages are an average over a whole week to 13 February 2022.

Our main variant analysis is for a reference day, and therefore is not directly comparable with the sequencing data. The following analysis looks at the percentage of the population with a positive test compatible with the Omicron BA.1 variant or with the Omicron BA.2 variant in England, Wales, Northern Ireland and Scotland, and the regions of England.

During periods of change in COVID-19 variants we will include a breakdown of estimated infections by variant to illustrate how the estimated percentage of people infected in the population is changing by variant (Figure 5). When nearly all infections are compatible with a dominant variant, we will no longer include this breakdown.

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Data should be treated with caution. There could be small numbers of positive cases compatible with a particular variant in Wales, Scotland and Northern Ireland, 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 BA.1 variant, and not all cases that have a detectable S-gene will be the Omicron BA.2 variant.

In this publication, the reference week for England, Wales, Northern Ireland, and Scotland is 20 to 26 February 2022.

The percentage of cases compatible with the Omicron BA.2 variant increased across England, Wales, and Scotland and decreased in Northern Ireland in the week up to 26 February 2022. In the same week, the percentage of cases compatible with the Omicron BA.1 variant decreased in England, Wales and Northern Ireland and increased in Scotland. Caution should be taken in over-interpreting any small movements in the latest trend. These modelled estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

Figure 5: The percentage of cases compatible with the Omicron BA.2 variant increased in England, Wales, and Scotland and decreased in Northern Ireland in the most recent week

Modelled percentage of the population testing positive for cases compatible with the Omicron BA.1 variant and Omicron BA.2 variant, based on nose and throat swabs, daily, UK, 16 January to 26 February 2022

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Notes:
  1. Omicron BA.1 variant-compatible positives are defined as those that are positive on the ORF1ab-gene and N-gene, but not the S-gene. This group includes Omicron BA.1.1.

  2. Omicron BA.2 variant-compatible positives are defined as those that are positive on the ORF1ab-gene, N-gene and S-gene, or on the ORF1ab-gene and S-gene or on the N-gene and S-gene.

  3. Data should be treated with caution. Not all cases positive on the S-gene will be the Omicron BA.2 variant, and some cases with pattern ORF1ab+N will also be the Omicron BA.2 variant where the S-gene was not detected for other reasons, such as low viral load.

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In the week ending 26 February 2022, the percentage of cases compatible with the Omicron BA.2 variant increased in all regions of England. In the same week, the percentage of cases compatible with the Omicron BA.1 variant decreased in all regions of England. Caution should be taken in over-interpreting any small movements in the latest trend. These modelled estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

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.1.1, BA.2 and BA.3)

Our Coronavirus (COVID-19) Infection Survey: technical dataset contains several tables relating to analysis on variants. More information on how we measure variants from positive tests on the survey can be found in our Understanding COVID-19 variants blog. Our Coronavirus (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 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 Coronavirus (COVID-19) Infection Survey methods article and our blog that explains why we trust the data from the Coronavirus (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 4 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for England.

Coronavirus (COVID-19) Infection Survey: Northern Ireland
Dataset | Released 4 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Northern Ireland.

Coronavirus (COVID-19) Infection Survey: Scotland
Dataset | Released 4 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Scotland.

Coronavirus (COVID-19) Infection Survey: Wales
Dataset | Released 4 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Wales.

Coronavirus (COVID-19) Infection Survey: technical data
Dataset | Released 4 March 2022
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

  • Anna Seale - University of Warwick, Warwick Medical School: Professor of Public Health; UK Health Security Agency, Data, Analytics and Surveillance: Scientific Advisor

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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 our 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 coronavirus (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 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.

Incidence rate

The incidence rate is a measure of the estimated number of new polymerase chain reaction (PCR)-positive cases per day per 10,000 people at a given point in time. It is different to positivity, which is an estimate of all current PCR positive cases at a point in time, regardless of whether the infection is new or existing.

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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 20 to 26 February 2022 for England, Wales, Northern Ireland, and Scotland.

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 were 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 23 February 2022 for England, Wales, Northern Ireland, and Scotland.

Response rates

Enrolment for this wave of recruitment for the Coronavirus (COVID-19) Infection Survey ceased on 31 January 2022. Response rates for England, Wales, Northern Ireland and Scotland can be regarded as final response rates to the survey. 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 Coronavirus (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.

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 5: Quality characteristics of the Coronavirus (COVID-19) Infection Survey (coherence and comparability), revised 16 July 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 trustworthiness, quality 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 Coronavirus (COVID-19) Infection Survey.

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Contact details for this Statistical bulletin

Kara Steel and Mike Bracher
infection.survey.analysis@ons.gov.uk
Telephone: +44 1633 560499