Coronavirus (COVID-19) Infection Survey, UK: 20 January 2023

The following points are for the week ending 10 January 2023.

• The percentage of people testing positive for coronavirus (COVID-19) continued to decrease in England and Wales, and decreased in Northern Ireland and Scotland.

• In England, the estimated number of people testing positive for COVID-19 was 1,461,900 (95% credible interval: 1,394,000 to 1,529,700), equating to 2.61% of the population (a decrease from 4.02% in the previous reference week), or around 1 in 40 people.

• In Wales, the estimated number of people testing positive for COVID-19 was 121,600 (95% credible interval: 103,200 to 140,900), equating to 3.94% of the population (a decrease from 5.16% in the previous reference week), or around 1 in 25 people.

• In Northern Ireland, the estimated number of people testing positive for COVID-19 was 77,300 (95% credible interval: 63,400 to 92,300), equating to 4.22% of the population (a decrease from 7.04% in the previous reference week), or around 1 in 25 people.

• In Scotland, the estimated number of people testing positive for COVID-19 was 171,500 (95% credible interval: 147,700 to 197,000), equating to 3.26% of the population (a decrease from 4.17% in the previous reference week), or around 1 in 30 people.

About this bulletin

The positivity rate is the percentage of people who would 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. Data are based on confirmed positive COVID-19 test results from those living in private households, excluding those living in care homes or other communal establishments.

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 available supporting information to aid user understanding. This is consistent with guidance from the Office for Statistics Regulation (OSR).

The Office for National Statistics (ONS) is running a small pilot to find out whether the Coronavirus (COVID-19) Infection Survey could be used as an early warning system for Influenza (flu) and another respiratory virus called respiratory syncytial virus (RSV) in the community. More information and findings can be found in our recent blog post, The Bigger Picture: Using the COVID-19 Infection Survey to track other infections and accompanying dataset.

In the week ending 10 January 2023, the percentage of people testing positive for coronavirus (COVID-19) continued to decrease in England and Wales, and decreased in Northern Ireland and Scotland.

Figure 1: The percentage of people testing positive for coronavirus (COVID-19) continued to decrease in England and Wales, and decreased in Northern Ireland and Scotland, in the week ending 10 January 2023

Estimated percentage of the population testing positive for COVID-19 on nose and throat swabs, UK, 25 December 2021 to 10 January 2023

Notes:

1. Official reported estimates are plotted at a reference point believed to be most representative of the given week.
2. 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.

3. There is a higher degree of uncertainty in our estimates for Wales, Northern Ireland and Scotland, compared with England. This is shown by wider credible intervals.

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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.

On 12 January 2023, we published our Regional and sub-regional estimates of coronavirus (COVID-19) positivity over time, UK article. This reports the percentage of people testing positive for coronavirus (COVID-19) in private residential households by region and sub-region over time, exploring periods when Alpha, Delta and Omicron variants were dominant and how infections varied across parts of the UK.

In the week ending 10 January 2023, the percentage of people testing positive for COVID-19 decreased in all regions of England.

Figure 2: The percentage of people testing positive for coronavirus (COVID-19) decreased in all regions of England in the week ending 10 January 2023

Modelled daily percentage of the population testing positive for COVID-19 on nose and throat swabs by region, England, 30 November 2022 to 10 January 2023

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. There is a higher degree of uncertainty in our estimates for English regions compared with England overall, shown by wider credible intervals.
3. 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.
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 update our sub-regional analysis monthly. Our most recent estimates for the percentage of people testing positive for COVID-19 in sub-regions of the UK can be found in our Coronavirus (COVID-19) Infection Survey, UK: 13 January 2023 bulletin.

Our age group analysis separates children and young people by school age.

In the week ending 10 January 2023, the percentage of people testing positive for coronavirus (COVID-19) in England decreased in all age groups.

Figure 3: The percentage of people testing positive for coronavirus (COVID-19) decreased in all age groups in the week ending 10 January 2023

Modelled daily percentage of the population testing positive for COVID-19 on nose and throat swabs by age group, England, 30 November 2022 to 10 January 2023

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.
2. There is a higher degree of uncertainty in our estimates for each age group in England compared with England overall. This is shown by wider credible intervals.

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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 available in our Coronavirus (COVID-19) Infection Survey datasets.

Single year of age analysis by UK countries

We now update our single year of age analysis monthly. Our most recent estimates for the percentage of people testing positive for COVID-19 by single year of age, by UK country can be found in our Coronavirus (COVID-19) Infection Survey, UK: 13 January 2023 bulletin.

The incidence rate is a measure of new polymerase chain reaction (PCR)-positive cases per day per 10,000 people in a given time period. In this section, we look at an earlier time period to our analysis of the percentage testing positive. We include official estimates of the incidence rate for the latest week in Table 2. These estimates, along with daily modelled estimates over the most recent six-week period, can also be found in our Coronavirus (COVID-19) Infection Survey datasets.

We have updated our incidence estimates for the first time since moving to remote data collection. This analysis uses our updated reinfections definition, therefore these estimates are not directly comparable with previous incidence estimates last presented in our Coronavirus (COVID-19) Infection Survey, UK: 8 July 2022 bulletin.

Credible intervals are wider for Wales, Northern Ireland and Scotland because of relatively smaller sample sizes, and care should be taken in interpreting results.

Currently, the variants under surveillance in the UK are Omicron, including sub-lineages BA.2, BA.4, and BA.5 and their sub-lineages.

The cycle threshold (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, as well as latest analysis of the genetic lineages of COVID-19 seen in the samples we sequence, are provided in our Coronavirus (COVID-19) Infection Survey: technical dataset.

Since the end of June 2022, most COVID-19 infections in the UK have been Omicron variant BA.5 or its sub-lineages, the majority of which are now the sub-lineage BQ.1. In the week ending 8 January 2023, BQ.1 comprised 44.2%, and other BA.5 variants (and sub-lineages, excluding BQ.1) comprised 6.0%, of all sequenced COVID-19 infections. The variant BA.2.75 and its sub-lineages (that includes XBB and its sub-lineages, and CH.1.1 and its sub-lineages) comprised 46.6%, with the sub-lineage CH.1.1 and its sub-lineages comprising 25.2%, and the sub-lineage XBB and its sub-lineages comprising 10.7%, of sequenced infections in the week ending 8 January 2023. In the same week, BA.4 and its sub-lineages comprised 1.1% of sequenced infections.

We last published our variant analysis by gene pattern in our Coronavirus (COVID-19) Infection Survey, UK: 8 July 2022 bulletin. We will continue to monitor infections by variant and will reintroduce 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 whole genome 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 4 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 (UKHSA) 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

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 a test suggests a person has COVID-19 when in fact they do not. By contrast, a false-negative result occurs when a test suggests 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.

Variant analysis by gene pattern

Different variants have various changes in their genetic code (mutations), and sometimes these affect the ability of the PCR test to detect one or more of the genes (or regions) of the virus they target. As a result, the pattern of genes identified in a positive PCR test can be used alongside knowledge of the currently circulating variants to describe a sample as "compatible with" a variant (or variants). The same pattern of genes detected can be found in different variants at different time points (waves) of the coronavirus pandemic. This analysis differs from whole genome sequencing because it does not identify the actual variant present in the swab, but instead assesses whether the positive test is "compatible with" a variant or variants known to be circulating in the UK at the time of analysis. We are able to do this because the PCR test for COVID-19 uses chemical reactions at three different locations in the COVID-19 viral genome, and one of them (the Spike gene) has characteristic deletions in its genetic code in several of the major variants, specifically: Alpha, Omicron BA.1, BA.4 and BA.5.

Whole genome sequencing

Swabs that are positive on a PCR test for COVID-19 with a Ct value less than 30 are additionally sent for genomic sequencing. A detailed investigation is undertaken to work out the specific order of the letters that make up the genetic material of the virus in the sample. Where we can identify at least 50% of the genetic code, we can identify the COVID-19 variant present through comparisons with the genetic sequences of known variants. Currently, the variants under surveillance in the UK are Omicron, including sub-lineages BA.2, BA.4, and BA.5 and their sub-lineages.

Remote data collection

The Office for National Statistics (ONS) Coronavirus (COVID-19) Infection Survey has moved from collecting data and samples through home visits by a study worker to a more flexible approach for participants. We have introduced an online questionnaire and swab and blood samples are returned through the post (or by courier for some participants). Further information on what these changes mean and how the survey will continue to be valuable can be found in our recent blog post: The COVID-19 Infection Survey is changing.

There were minimal differences between estimates of swab positivity produced from remote data collection methods, compared with data collected by study worker home visits. New data presented in the 19 August 2022 publication were based on a combination of data collected remotely and by study worker home visits. New data presented from the 26 August 2022 publication onwards were collected by remote data collection only. Further information on the effects of the change in data collection method can be found in our Quality Report: August 2022 and Quality Report: December 2022.

Laboratories

The nose and throat swabs taken from participants of the Coronavirus (COVID-19) Infection Survey are sent to the Lighthouse Laboratory in Glasgow for processing. Recently, some of our swabs have been sent to the Rosalind Franklin as well as Berkshire and Surrey Pathology Services laboratories for testing. This is to ensure resilience for testing capacity and to enable a small pilot community respiratory surveillance study. We have investigated potential effects of using multiple laboratories on our positivity results and, where necessary, have made minor statistical adjustments within our existing models to ensure consistency.

Weighted 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.

Study reference dates

We aim to provide the estimates of positivity rate (the percentage of people who test positive) and incidence that are most timely and most representative of each week. In addition, to improve stability in our modelling while maintaining relative timeliness of our estimates, we report our official estimates based on the midpoint of the reference week. This week, the reference week is 4 to 10 January 2023, and the reference day is 7 January 2023 for all UK nations.

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. This week, the reference week for incidence is 21 to 27 December 2022, and the reference day is 24 December 2022.

For more information on our methods surrounding the reference dates, please see our Coronavirus (COVID-19) Infection Survey methods article.

Response rates

Enrolment for this wave of recruitment for the Coronavirus (COVID-19) Infection Survey largely ceased on 31 January 2022. Response rates for England, Wales, Northern Ireland and Scotland can generally 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.

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 4: Quality characteristics of the Coronavirus (COVID-19) Infection Survey (coherence and comparability) of the Coronavirus (COVID-19) Infection Survey QMI, revised 8 August 2022.

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:

• 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

• for daily modelled estimates, provisional and subject to revision

The Office for Statistics Regulation (OSR), on behalf of the UK Statistics Authority, has reviewed these statistics 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.