Coronavirus (COVID-19) Infection Survey, UK: 11 June 2021

• In England, the percentage of people testing positive for coronavirus (COVID-19) has continued to increase in the week ending 5 June 2021; we estimate that 96,800 people within the community population in England had COVID-19 (95% credible interval: 80,500 to 114,400), equating to around 1 in 560 people.

• In Wales, the percentage of people testing positive has increased in the two weeks up to 5 June 2021, however, the trend is uncertain in the week ending 5 June 2021; we estimate that 2,300 people in Wales had COVID-19 (95% credible interval: 800 to 4,900), equating to around 1 in 1,300 people.

• In Northern Ireland, the trend in the percentage of people testing positive is uncertain in the week ending 5 June 2021; we estimate that 2,600 people in Northern Ireland had COVID-19 (95% credible interval: 1,000 to 5,200), equating to around 1 in 700 people.

• In Scotland, the percentage of people testing positive has increased in the two weeks up to 5 June 2021, however, the trend is uncertain in the week ending 5 June 2021; we estimate that 9,700 people in Scotland had COVID-19 (95% credible interval: 5,700 to 14,800) equating to around 1 in 540 people.

• In the week ending 5 June 2021, cases that are not compatible with the Alpha variant (first identified in the UK) in England have continued to increase and are now the most common variant group; these are likely to be the  Delta variant B.1.617.2 (first identified in India).

• In the week ending 5 June 2021, cases that are compatible with the Alpha (UK) variant in Wales have continued to increase.

About this bulletin

In this bulletin, we refer to the number of current COVID-19 infections within the community population; community in this instance refers to private residential households and it excludes those in hospitals, care homes and/or other institutional settings. In institutional settings, rates of COVID-19 infection are likely to be different. More information about the coronavirus  (COVID-19) pandemic from the ONS and other sources can be found in our latest insights.

The positivity rate is the percentage of people who have tested positive for COVID-19 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 polymerase chain reaction (PCR)-positive cases in a given time period.

All analysis was produced with our research partners at the University of Oxford.

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 possible. These will include supporting information where possible to aid user understanding. This is consistent with guidance from the Office for Statistics Regulation.

How the data in this bulletin can be used

The data can be used for:

• estimating the number of current positive cases in the community, including cases where people do not report having any symptoms
• identifying differences in numbers of positive cases between different regions
• 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 institutional settings
• providing information about recovery time of those infected

Infection rates remain low across the UK compared with earlier months in the year. In England, the percentage of people testing positive has continued to increase in the week ending 5 June 2021. In Wales and Scotland, the percentage testing positive increased in the two weeks up to 5 June 2021, however, the trend is uncertain in the week ending 5 June 2021. In Northern Ireland in the same week, the trend in the percentage of people testing positive is uncertain.

These estimates are based on statistical modelling of the trend in rates of positive nose and throat swab results. The ratios presented are rounded to the nearest 10. Because of lower positivity rates caution should be taken in over-interpreting any small movements in the latest trends.

Figure 1: The percentage of people testing positive increased in England, and the trends are uncertain in Wales, Northern Ireland and Scotland, in the week ending 5 June 2021

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs from 3 May 2020

Notes:

1. 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. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.
2. Official reported estimates are plotted at a reference point believed to be most representative of the given week.
3. 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.
4. 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.

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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 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 understand 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 accompanying datasets.

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) and the unweighted sample counts are included in the accompanying 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. Information about how the modelled and 14-day non-overlapping estimates are calculated can be found in our methods article.

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.

The overall national picture for England is a result of the trends across regions. During the week ending 5 June 2021, the highest percentage of people testing positive was observed in the North West.

In the week ending 5 June 2021, the percentage of people testing positive has increased in the North West, West Midlands, London and the South East. There were also early signs of a decrease in the percentage of people testing positive in the East of England in the week ending 5 June 2021. The trend is uncertain for all other regions in the same week. In many regions positivity rates are very low, so trends will be difficult to identify since they are affected by small changes in the number of people testing positive from week to week.

Figure 2: The percentage of people testing positive increased in the North West, West Midlands, London and the South East in the week ending 5 June 2021

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by region since 25 April 2021, England

Notes:

1. All results are provisional and subject to revision.
2. These statistics refer to infections reported in the community, by which we mean private households. These figures exclude infections reported in hospitals, care homes and/or other institutional settings.
3. 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.
4. 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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Age analysis by category for England

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

• "age two years to school Year 6" includes those children in primary school and below
• "school Year 7 to school Year 11" includes those children in secondary school
• "school Year 12 to age 24 years" includes those 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.

In the week ending 5 June 2021, the percentage of people testing positive has increased in those in school Year 12 to age 34 years and in those aged 50- to 69-years-old. In the two weeks up to 5 June 2021, the percentage testing positive increased in school Years 7 to 11 and those aged 35 to 49 years, however, the trend is uncertain in the week ending 5 June 2021. In the week ending 5 June 2021, the trend is uncertain for those aged two years to school Year 6 and for those aged 70 years and above. Because of lower positivity rates, caution should be taken in over-interpreting small movements in the latest trends.

Figure 3: The percentage of people testing positive has increased in those in school Year 12 to age 34 years and those aged 50 to 69 years in the week ending 5 June 2021

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by age group since 25 April 2021, England

Notes:

1. All results are provisional and subject to revision.
2. These statistics refer to infections reported in the community, by which we mean private households. These figures exclude infections reported in hospitals, care homes and/or other institutional settings.

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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.

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

The incidence rate is a measure of new polymerase chain reaction (PCR)-positive cases in a given time period.

We regularly review our methods and survey design as part of our ongoing quality assurance process. Our incidence method uses several weeks' data to provide the latest estimate of new infections. Because of lower numbers of people testing positive over the last several weeks compared with earlier in the year, we are reviewing our estimates of incidence (last published 7 May 2021). This review ensures that the estimates we provide continue to be of high quality. Therefore, we will not be updating our incidence estimates in this publication. For more information on how we calculate estimates of incidence please see COVID-19 Infection Survey: methods and further information.

The World Health Organisation (WHO) have suggested new names for Variants of Concern and Variants of Interest which are shown in Table 2.

The variant B.1.1.7 (WHO 'Alpha', known as the "UK variant") of COVID-19 identified in the UK in mid-November 2020 has changes in one of the three genes that COVID-19 swab tests detect, known as the S-gene. This means in cases compatible with this variant, the S-gene is not detected by the current test. Therefore B.1.1.7 (WHO 'Alpha') has the pattern ORF1ab+N (S gene negative) in our main variant analysis.

Other variants – including both B.1.617.2 (WHO 'Delta', first identified in India) and B.1.351 (WHO 'Beta', first identified in South Africa) – are positive on all three genes, with the pattern ORF1ab+S+N. If there is an increase in the prevalence of any of these strains, this will show up in our analysis as an increase in our category "Not compatible with the Alpha (UK) variant". Our main variant analysis can therefore differentiate between these two groups of variants (ORF1ab+N positive or ORF1ab+S+N positive), but cannot differentiate between variants that have the same gene pattern for the three genes that COVID-19 swab tests detect. More information on individual variants and where they were first detected is available on the government variant dashboard.

Other variants, including B.1.525 (WHO 'Eta', first identified in Nigeria), also have the same pattern of gene positivity as B.1.1.7 (WHO 'Alpha', the UK variant). At present these are rare in the UK so we continue to describe this group as compatible with the Alpha (UK) variant, but we will continue to keep this under review. The percentage of people testing positive by different variants are provided in the accompanying technical dataset.

In the week ending 5 June 2021, the percentage of people testing positive whose results are compatible with B.1.1.7 (WHO "Alpha", the UK variant) continued to increase in Wales whilst the trend is uncertain in England, Northern Ireland and Scotland.

In the week ending 5 June 2021, the percentage of people testing positive whose results are not compatible with B.1.1.7 (WHO "Alpha", the UK variant) continued to increase in England whilst the trend is uncertain in Wales, Northern Ireland and Scotland. These cases are likely to be compatible with the variant B.1.617.2 (WHO "Delta", first identified in India), which is now the most common variant group in England.

The percentage of people testing positive by variant category in England is shown in Figure 4. Because of the low number of positive results there is a greater degree of uncertainty in the percentage of people testing positive by variant category for Wales, Northern Ireland and Scotland. Therefore, we are not presenting this data in Figure 4 in this publication.

Figure 4: In the week ending 5 June 2021, the percentage testing positive whose results are not compatible with the Alpha (UK) variant and whose results were too low for the variant to be identifiable increased in England

Modelled percentage of cases compatible with the Alpha (UK) variant, not compatible with the Alpha (UK) variant and where the virus was too low for the variant to be identifiable based on nose and throat swabs, daily, since 25 April 2021, England

Notes:

1. All results are provisional and subject to revision.
2. These statistics refer to infections reported in the community, by which we mean private households. These figures exclude infections reported in hospitals, care homes and/or other institutional settings.
3. Data should be treated with caution. There are uncertainties given that not all cases that are positive on the ORF1ab and N-genes will be the Alpha (UK) variant.
4. Alpha (UK) variant compatible positives are defined as those that are positive on the N-gene and ORF1ab-gene, but not the S-gene. Positives that are not compatible with the Alpha variant are defined as those that are positive on the S-gene, N-gene and ORF1ab-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.
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.

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Each test goes through a number of cycles before a positive result is detectable. If there is a high quantity of the virus present, a positive result will be identified after a low number of cycles. However, if there is only a small amount of the virus present, then it will take more cycles to detect it.

The number of cycles is measured as a "cycle threshold", known as a Ct value. These values 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 COVID-19 positive tests are provided in the technical dataset that accompanies this bulletin.

We try to read all letters of the virus's genetic material for every positive nose and throat swab with sufficient virus to do so (Ct less than 30) – this is called whole genome sequencing. Positive samples are hand-picked at the testing centre and shipped to a sequencing lab, after which they are sequenced and the genetic data processed. Sequencing is not successful on all these samples, or only part of the genome is sequenced. This is especially so for the higher Ct values, which are common in our data as we often catch people early or late in infection when viral loads tend to be lower (and hence Ct values are higher). Where we successfully sequence over half of the genome, we use the sequence data to work out which virus is which type of variant. This method can tell us which variant might be responsible for any potential increase in either cases "Not compatible with the Alpha (UK) variant" or "compatible with the Alpha (UK) variant". However, because we cannot get a sequence from every positive result, there is more uncertainty in these estimates.

These data are provided in the accompanying technical dataset using the international standard labels.

Because of the bank holiday last week, we have been unable to update our genetic lineages data this week.

More information on how we measure variants from positive tests on the survey can be found in our blog.

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 methods article and our recent blog. 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.

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, Public Health England (PHE) 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

Community

In this bulletin, we refer to the number of coronavirus (COVID-19) infections within the community. Community in this instance refers to private households, and it excludes those in hospitals, care homes and/or other institutional settings.

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. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

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 recent blog.

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 is 30 May to 5 June 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 2 June 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 accompanying 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 methods article.

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.

These statistics have been produced quickly in response to developing world events. The Office for Statistics Regulation, on behalf of the UK Statistics Authority, has reviewed them 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 methodology article and our blog.