Coronavirus (COVID-19) Infection Survey, UK: 15 July 2022

The following points are for the week ending 6 July 2022 for England, Wales, and Northern Ireland, and 7 July 2022 for Scotland.

• The percentage of people testing positive for coronavirus (COVID-19) continued to increase across the UK.
• In England, the estimated number of people testing positive for COVID-19 was 2,873,600 (95% credible interval: 2,754,900 to 2,991,100), equating to 5.27% of the population, or around 1 in 19 people.
• In Wales, the estimated number of people testing positive for COVID-19 was 183,500 (95% credible interval: 155,800 to 215,300), equating to 6.04% of the population, or around 1 in 17 people.
• In Northern Ireland, the estimated number of people testing positive for COVID-19 was 107,600 (95% credible interval: 86,900 to 129,700), equating to 5.86% of the population, or around 1 in 17 people.
• In Scotland, the estimated number of people testing positive for COVID-19 was 334,000 (95% credible interval: 287,400 to 382,300), equating to 6.34% of the population, or around 1 in 16 people.

About this bulletin

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.

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).

The Office for National Statistics (ONS) Coronavirus (COVID-19) Infection Survey is moving from a survey worker data collection method to a more flexible approach for participants. We will introduce a digital questionnaire and send swab and blood sample kits through the post. Further information on what these changes mean and how the survey will continue to be valuable can be found in our recent blog post.

During this period of transition, we are temporarily pausing our estimates of incidence and sub-regional analysis. Most recent updates for these outputs are available in our Coronavirus (COVID-19) Infection Survey datasets.

We have also not updated our variant analysis in this release because the majority of cases are compatible with Omicron BA.4 or BA.5 variants.

The percentage of people testing positive for coronavirus (COVID-19) continued to increase in England, Wales, and Northern Ireland in the week ending 6 July 2022, and in Scotland in the week ending 7 June 2022. These increases were likely caused by increases in infections compatible with Omicron variants BA.4 and BA.5.

Our estimates contain all variants of COVID-19 that were circulating at the time the data was collected.

Figure 1: The percentage of people testing positive for coronavirus (COVID-19) continued to increase across the UK in the most recent week

Estimated percentage of the population testing positive for COVID-19 on nose and throat swabs, UK, 11 July 2021 to 7 July 2022

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 our Coronavirus (COVID-19) Infection Survey datasets.
4. The reference week is 30 June to 6 July 2022 for England, Wales and Northern Ireland, and 1 to 7 July 2022 for Scotland.

Download the data

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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.

Official estimates should be used to understand the positivity rate for a single point in time and are our best and most stable estimates, used in all previous outputs. They are based on a reference day from the statistical model of the trend in rates of positive nose and throat swab results for the latest week. All estimates are subject to uncertainty given that a sample is only part of the wider population.

The modelled estimates are 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. 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. Therefore, caution should be taken in over-interpreting small movements in the very latest trends. These modelled estimates can be found in our Coronavirus (COVID-19) Infection Survey datasets.

In the week ending 6 July 2022, the percentage of people testing positive for coronavirus (COVID-19) continued to increase across all English regions.

Figure 2: The percentage of people testing positive for coronavirus (COVID-19) continued to increase across all English regions in the week ending 6 July 2022

Modelled daily percentage of the population testing positive for COVID-19 on nose and throat swabs by region, England, 26 May to 6 July 2022

Notes:

1. Credible intervals widen slightly at the end as there is a delay between the swab being taken and reporting of results. We report latest figures based on the reference day for that week because of this greater uncertainty in the most recent days.
2. The percentage of people testing positive by region was calculated using a similar modelling approach to the national daily estimates in Section 2: COVID-19 by UK countries.
3. The analysis is conducted over a six-week period, which means some 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.

Download the data

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Sub-regional analysis of the UK

We are temporarily pausing our sub-regional analysis while we transition to our new digital data collection method. The most recent updates for these outputs are available in our Coronavirus (COVID-19) Infection Survey datasets.

Age group analysis for England

Our age groups separate children and young people by school age.

In the week ending 6 July 2022, the percentage of people testing positive for coronavirus (COVID-19) in England continued to increase in all age groups. Caution should be taken in over-interpreting any small movements in the latest trend.

Figure 3: In England, the percentage testing positive for coronavirus (COVID-19) continued to increase in all age groups in the week ending 6 July 2022

Modelled daily percentage of the population testing positive for COVID-19 on nose and throat swabs by age group, England, 26 May to 6 July 2022

Notes:

1. Credible intervals widen slightly at the end as there can be a delay between the swab being taken and reporting of results. We report latest figures based on the reference day for that week because of this greater uncertainty in the most recent days.

Download the data

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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. However, estimates of positivity by single year of age for Wales, Northern Ireland and Scotland using a different model are in the following section and in our accompanying 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 by single year of age over time from 26 May to 6 July 2022 for England, Wales, and Northern Ireland, and 27 May to 7 July 2022 for Scotland. They are produced using a different method to the grouped age analysis for England presented previously and are therefore not directly comparable.

The data in Figure 4 suggest that the percentage of people testing positive continued to increase for most ages in England, Wales, and Northern Ireland in the most recent two weeks up to 6 July 2022. In Scotland, the trend was uncertain for most ages in the latest two weeks up to 7 July 2022.

Figure 4: The percentage testing positive for coronavirus (COVID-19) over time by single year of age

Modelled daily percentage of the population testing positive for COVID-19 on nose and throat swabs by single year of age, UK, 26 May to 7 July 2022

Notes:

1. Estimates use a different method to the modelled daily estimates of the percentage testing positive by age group for England and are not directly comparable.
2. There are no estimates for those aged two years in Wales and Northern Ireland on account of limited data for that age in the time period.
3. The reference period is 26 May to 6 July 2022 for England, Wales and Northern Ireland, and 27 May to 7 July 2022 for Scotland.

Download the data

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Further information on age for Wales, Northern Ireland and Scotland is published by their respective statistical agencies.

Please see:

• Welsh Government's Coronavirus (COVID-19) Infection Survey findings published in English
• Welsh Government's Coronavirus (COVID-19) Infection Survey findings published in Welsh
• Northern Ireland Department for Health's Coronavirus (COVID-19) Infection Survey findings
• Scottish Government's Coronavirus (COVID-19) Infection Survey findings

We are temporarily pausing our incidence analysis while we transition to our new digital data collection method. The most recent updates for these outputs are available in our Coronavirus (COVID-19) Infection Survey datasets.

The World Health Organization (WHO) have defined names for variants of concern.

Currently, the variants under surveillance in the UK are:

• Omicron, including sub-lineages BA.1, BA.2, BA.3, BA.4 and BA.5

We publish weekly breakdowns of infections by variant as determined by whole genome sequencing and cycle-threshold (Ct) values.

The Ct value reflects the quantity of virus (also known as viral load) found in a swab test. A lower Ct value indicates a higher viral load. The latest Ct values of coronavirus (COVID-19) positive tests are provided in our Coronavirus (COVID-19) Infection Survey: technical dataset.

Our technical dataset includes weekly analysis of the genetic lineages of coronavirus seen in the samples we sequence. Of the COVID-19 positives successfully sequenced, in the latest week available (week ending 3 July 2022) 68.9% were Omicron BA.5, 20.3% were Omicron BA.4, 10.8% were Omicron BA.2 and there were no Omicron BA.1 (or its sub-lineages) sequences identified.

We last published our main variant analysis in our Coronavirus (COVID-19) Infection Survey, UK: 8 July 2022 bulletin. This showed a very high proportion of infections compatible with the BA.4 and BA.5 variants, so we have not included a breakdown of infections by variant in this release. We will continue to monitor infections by variant and will reintroduce the charts and analysis by gene pattern when considered helpful. More information on how we measure variants from positive tests on the survey can be found in our Understanding COVID-19 variants blog and in our Coronavirus (COVID-19) Infection Survey methods article. 

The sequencing is produced by the Wellcome Trust Sanger Institute 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.

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.

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

Age groups for children and young people

• "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 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.

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. A wider interval indicates more uncertainty in the estimate. Overlapping credible intervals indicate that there may not be a true difference between two estimates. For more information, see our methodology page on statistical uncertainty.

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 Section 12: Strengths and limitations.

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.

Modelled estimates

In earlier publications we published weighted estimates for non-overlapping 14-day periods. These were additional to our modelled estimates, which are updated more regularly as test results are received and provide the best measure of trends. The weighted estimates were last updated in our publication on 13 May 2022. For more information on our methods and quality surrounding the estimates please see our Coronavirus (COVID-19) Infection Survey methods article and our Quality and Methodology Information (QMI) report.

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 June to 6 July 2022 for England, Wales, and Northern Ireland, and 1 to 7 July 2022 for 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 Sunday 3 July 2022 for England, Wales, and Northern Ireland, and Monday 4 July 2022 for Scotland.

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. Where we have multiple positivity reference days the earliest date is used. This is necessary as estimates later than this date are more likely to change as we receive additional data. We have paused publication of updates to incidence as of the current release (15 July 2022). The last published update to reporting for incidence is 9 to 15 June 2022 and the reference day is 12 June 2022, and this is included in our Coronavirus (COVID-19) Infection Survey datasets.

Gene patterns for variant analysis

The Omicron variants BA.4 and BA.5 have changes in one of the three genes that the coronavirus survey swab test detects, which means the S-gene is no longer detected. 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 the Omicron variants BA.4 and BA.5. 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 these Omicron variants.

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.

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 our 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.

Inconclusive and failed tests

Our estimates are based on confirmed positive test results. The remaining swabs are either negative and included in analysis, or inconclusive and not included in analysis. Some swabs are test failures, which also are not included in analysis. The impact of excluding inconclusive results from our estimates of positive infections is likely to be very small and unlikely to affect the trend.

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 Coronavirus (COVID-19) Infection Survey sub-regions. The geographies are a rules-based composition of local authorities. Local authorities with a population over 200,000 have been retained where possible.

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

Other Coronavirus Infection Survey (CIS) analysis and studies

This study provides the main measure of coronavirus infection in the UK. Other sources have provided data during previous stages of the pandemic. For information on other studies see Section 5: Quality characteristics of the Coronavirus (COVID-19) Infection Survey (coherence and comparability) of the Coronavirus (COVID-19) Infection Survey QMI, revised 16 July 2021.

The data in this bulletin 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 in positive cases over time

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

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 is 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.