Coronavirus (COVID-19) Infection Survey, UK: 18 December 2020

• The percentage of people testing positive for the coronavirus (COVID-19) in England has increased; during the most recent week (6 to 12 December 2020), we estimate 567,300 people (95% credible interval: 533,600 to 602,300) within the community population in England had the COVID-19, equating to around 1 in 95 people (95% credible interval: 1 in 100 to 1 in 90).

• Over the most recent week, the percentage of people testing positive has increased sharply in London, with other increases in the East of England, the East Midlands, and the South East; the percentage of people testing positive in the North West and Yorkshire and The Humber has continued to decrease in the most recent week.

• In the most recent week, the percentage of people testing positive has increased in most age groups, other than those in school Year 12 to 24 years old, and those aged 50 to 69 years; there are now early signs the percentage testing positive is levelling out among older teenagers and young adults.

• The percentage of those testing positive has increased over recent weeks in Wales; during the most recent week (6 to 12 December 2020), we estimate that 33,400 people in Wales had COVID-19 (95% credible interval: 23,800 to 44,300), equating to 1 in 90 people (95% credible interval: 1 in 130 to 1 in 70).

• The percentage testing positive in Northern Ireland appears to no longer be decreasing; during the most recent week (6 to 12 December 2020), we estimate that 8,500 people in Northern Ireland had COVID-19 (95% credible interval: 5,100 to 13,000), equating to 1 in 215 people (95% credible interval: 1 in 360 to 1 in 140).

• The percentage testing positive in Scotland has increased; during the most recent week (6 to 12 December 2020), we estimate that 52,500 people in Scotland had COVID-19 (95% credible interval: 41,600 to 64,600), equating to 1 in 100 people (95% credible interval: 1 in 125 to 1 in 80).

Incidence (the number of new infections in a set period of time) helps us understand the rate at which infection is growing within the population and supports our main measure of prevalence to provide a fuller understanding of the coronavirus. We estimate incidence by directly measuring when a participant in our study who has previously tested negative subsequently tests positive, and comparing this with the number of participants who remain negative. When enrolled on the survey, participants are swabbed weekly for five weeks and then move to monthly swabbing.

Increasing the CIS sample size to 150,000 participants per fortnight enabled the majority of participants to be swabbed weekly, providing us with regular and timely updates on the number of new infections and the "time at risk". The proportion swabbed monthly has now increased and we have reviewed our estimation of incidence, determining options that will adapt our approach to reflect changes in data capture and survey design. We are committed to regular reviews of our methods and survey design as part of our ongoing quality assurance process to ensure our estimates remain of the highest quality possible and continue to meet user needs.

This review ensures we will continue to provide an accurate estimate of incidence and to make sure our statistics continue to be of high quality. Our aim is to re-introduce our estimate of incidence in January 2021. We will confirm a date nearer the time.

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.

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 infections in a given time period. All analysis was produced with our research partners at the University of Oxford.

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

During the most recent week of the study, we estimate that 567,300 people in England had the coronavirus (COVID-19) (95% credible interval: 533,600 to 602,300)¹. This equates to 1.04% (95% credible interval: 0.98% to 1.10%) of the population in England or around 1 in 95 people (95% credible interval: 1 in 100 to 1 in 90). The ratios presented are rounded to the nearest five. This is based on statistical modelling of the trend in rates of positive nose and throat swab results.

Official estimates of the percentage of people testing positive over time are presented in Figure 1. In the most recent week, the percentage of people testing positive in England has increased.

In the latest six-week period, there were 612,638 swab tests, and a total of 6,242 positive tests, in 5,138 people from 3,973 households. In the latest two-week period, there were 187,158 swab tests, and a total of 1,750 positive tests, in 1,672 people from 1,395 households.

Our headline estimate of percentage testing positive in England is the official estimate. We include different measures to support our estimation and the below outlines the appropriate uses of all of the approaches.

Official estimates should be used to understand the positivity rate for a single point in time. This estimate, based on the modelled estimate for the latest week, is our best and most stable estimate and is used in all previous outputs. The modelled estimate can be used to understand the recent trend. The modelling includes a set period of data and smooths the estimate over time.

As this is a household survey, our figures do not include people staying in hospitals, care homes and/or other institutional settings. In these settings, rates of COVID-19 infection are likely to be different. More information about rates of COVID-19 in care homes can be found in Impact of coronavirus in care homes in England: 26 May to 19 June 2020.

Figure 1: In the most recent week, the percentage of people testing positive in England has increased

Official estimates of the percentage of the population in England 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. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

Download the data

.xlsx

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.

Figure 2: The most recent modelled estimate shows signs that the percentage testing positive has increased

Estimated percentage of the population in England testing positive for the coronavirus (COVID-19) on nose and throat swabs based on modelled estimates from 1 November 2020

Notes:

1. These results are provisional and subject to revision.

2. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

4. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data are included.

Download the data

.xlsx

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 3. These estimates are provided for context. The dataset that accompanies this bulletin includes the 14-day estimates and the unweighted sample counts. The 14-day time periods presented in Figure 3 overlap with those presented in the data tables in our previous publication, so direct comparisons are not possible.

The percentage testing positive in the latest 14-day period (29 November to 12 December 2020) was 1.15% (95% confidence interval: 1.09% to 1.21%). Averaging the percentage testing positive over the past 14-day period can mask changes in the percentage testing positive that have occurred over the most recent two weeks.

Information about how the modelled and 14-day non-overlapping estimates are calculated can be found in our methods article.

We are continuously refining and looking to improve our modelling and presentations. We would welcome any feedback via email: infection.survey.analysis@ons.gov.uk.

For information about the potential impact of false-positive and false-negative test results, see our methods article.

Notes for: Number of people in England who had COVID-19

1. This is based on model estimates from the reference point of the most recent week (6 to 12 December 2020), Wednesday 9 December 2020. More information on reference dates can be found in Section 14: Measuring the data.

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

During the most recent week of the study (6 to 12 December 2020), the percentage of people testing positive varies substantially by region; the East Midlands and London now have the highest proportion of people testing positive in the most recent week. The South West has a much lower proportion of people testing positive compared with all other regions.

Trends over time vary substantially between regions and can be seen in Figure 5. Over the most recent week, the percentage of people testing positive has sharply increased in London, with other increases in the East of England, East Midlands and South East. However, the credible intervals for the East Midlands are relatively wide. The percentage of people testing positive in the North West and Yorkshire and The Humber has continued to decrease in the most recent week. Caution should be taken in over-interpreting any small movements in the latest trend, particularly if they are already at a high level. Our 14-day estimates can be found in the dataset that accompanies this bulletin.

The percentage of people testing positive by region was calculated using a similar modelling approach to the national daily estimates in Section 2: Number of people in England who had COVID-19.

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.

Figure 5: Over the most recent week, the percentage of people testing positive has increased sharply in London, with other increases in the East of England, East Midlands and South East

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by region since 1 November 2020, 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.

Download the data

.xlsx

Estimates for non-overlapping 14-day periods (which underpin our modelled estimates) for regions in England are available in our dataset, and are provided for context.

The analysis in this section presents modelled estimates for the most recent week of data at the sub-regional level. In the data used to produce these estimates, the number of people sampled in each area who tested positive for the coronavirus (COVID-19) is lower relative to the England overall sample. This means there is a higher degree of uncertainty in the sub-regional estimates for this period and caution should be taken when interpreting or ranking these estimates, and the uncertainty of the estimates and wide credible intervals should be taken into account.

During the most recent week of the study (6 to 12 December 2020), the highest rates can be seen in areas in London, the East Midlands, and North East. The lowest rates can be seen in the South West.

Figure 6: Over the last week, the highest percentage testing positive can be seen in areas in the East Midlands and London

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, by sub-regional geography, England, from modelling the most recent week of data 6 to 12 December 2020

Notes:

1. These results are provisional and subject to revision.

2. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

Download the data

.xlsx

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 have been split between the youngest age categories depending on whether they are in school Year 6 or 7 (birthday before or after 1 September).

Similarly, 16- to 17-year-olds are split depending on whether they are in school Years 11 or 12 (birthday before or after 1 September).

In the most recent week, the percentage of those testing positive has increased in most age groups, excluding those in school Year 12 to 24 years old, and those aged 50 to 69 years. Previously, the percentage of people testing positive was decreasing in older teenagers and young adults, but this now appears to have levelled. Rates in this group are now similar to those aged 25 to 49 years. Rates continue to be highest in secondary school-age children.

Caution should be taken in over-interpreting small movements in the narrower age groups, which have wider credible intervals. This is based on statistical modelling of nose and throat swab test results.

In the data used to produce these estimates, the number of people sampled in the different age groups who tested positive for COVID-19 is lower relative to England overall. This means there is a higher degree of uncertainty in estimates for individual age groups over this period, as indicated by larger credible intervals.

Figure 7: In the most recent week, the percentage testing positive has increased in most age groups, excluding those in school Year 12 to 24 years old, and those aged 50 to 69 years

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by age group since 1 November 2020, 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 modelled estimates are presented at the reference value for a region which is the East Midlands. This does not affect the overall trend over time, but estimated probabilities for other regions would vary in level.

Download the data

.xlsx

Estimates for non-overlapping 14-day periods (which underpin our modelled estimates) by age group are available in our dataset, and are provided for context.

Currently in our main analysis, individuals in school Year 12 and 13 have been grouped with young adults up to age 24 years. We are considering the most appropriate category for these individuals to be grouped with for future bulletins.

Incidence (the number of new infections in a set period of time) helps us understand the rate at which infection is growing within the population and supports our main measure of prevalence to provide a fuller understanding of the coronavirus. We estimate incidence by directly measuring when a participant in our study who has previously tested negative subsequently tests positive, and comparing this with the number of participants who remain negative. When enrolled on the survey, participants are swabbed weekly for five weeks and then move to monthly swabbing.

Increasing the CIS sample size to 150,000 participants per fortnight enabled the majority of participants to be swabbed weekly, providing us with regular and timely updates on the number of new infections and the "time at risk". The proportion swabbed monthly has now increased and we have reviewed our estimation of incidence, determining options that will adapt our approach to reflect changes in data capture and survey design. We are committed to regular reviews of our methods and survey design as part of our ongoing quality assurance process to ensure our estimates remain of the highest quality possible and continue to meet user needs.

This review ensures we will continue to provide an accurate estimate of incidence and to make sure our statistics continue to be of high quality. Our aim is to re-introduce our estimate of incidence in January 2021. We will confirm a date nearer the time.

During the most recent week of the study¹, we estimate that 33,400 people in Wales had the coronavirus (COVID-19) (95% credible interval: 23,800 to 44,300). This equates to 1.10% (95% credible interval: 0.78% to 1.46%) of the population in Wales or around 1 in 90 people (95% credible interval: 1 in 130 to 1 in 70). The ratios are rounded to the nearest five. Our modelling suggests that the percentage of those testing positive has increased over recent weeks in Wales. This is based on exploratory modelling of throat and nose swab results.

Because of the relatively small number of tests and a low number of positives in our sample, credible intervals are wide and therefore results should be interpreted with caution.

In the latest six-week period, there were 19,847 swab tests, and a total of 160 positive tests, in 143 people from 119 households. In the latest two-week period, there were 6,088 swab tests, and a total of 65 positive tests, in 62 people from 55 households.

Our headline estimate of percentage testing positive in Wales is the official estimate. We include different measures to support our estimation and the below outlines the appropriate uses of all of the approaches.

Official estimates should be used to understand the positivity rate for a single point in time. This estimate, based on the modelled estimate for the latest week, is our best and most stable estimate and is used in all previous outputs. The modelled estimate can be used to understand the recent trend. The modelling includes a set period of data and smooths the estimate over time.

Figure 8: The percentage of those testing positive has increased over recent weeks in Wales

Estimated percentage of the population in Wales testing positive for the coronavirus (COVID-19) on nose and throat swabs since 1 November 2020

Notes:

1. These results are provisional and subject to revision.

2. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

4. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data are included.

Download the data

.xlsx

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 9. These 14-day estimates are provided for context. The dataset that accompanies this bulletin includes the 14-day estimates and the unweighted sample counts. The 14-day time periods presented in Figure 9 overlap with those presented in the data tables in our previous publication, so direct comparisons are not possible.

The percentage testing positive in Wales in the latest 14-day period (29 November to 12 December 2020) was 1.20% (95% confidence interval: 0.88% to 1.60%). Caution should be taken around using the 14-day estimate, as averaging the percentage testing positive over the past 14-day period can mask changes in the percentage testing positive that have occurred over the most recent two weeks.

The Welsh Government also publishes results from this survey that describe COVID-19 infections in Wales in English and in Welsh.

Notes for: Number of people in Wales who had COVID-19

1. This is based on model estimates from the reference point of the most recent week (6 to 12 December 2020), Wednesday 9 December 2020. More information on reference dates can be found in Section 14: Measuring the data.

During the most recent week of the study¹, we estimate that 8,500 people in Northern Ireland had the coronavirus (COVID-19) (95% credible interval: 5,100 to 13,000). This equates to 0.47% (95% credible interval: 0.28% to 0.71%) of the population in Northern Ireland or around 1 in 215 people (95% credible interval: 1 in 360 to 1 in 140). The ratios in this bulletin are rounded to the nearest five. Our modelling suggests that in the most recent week, the percentage of people testing positive in Northern Ireland appears to no longer be decreasing. This is based on exploratory modelling of throat and nose swab results.

Because of the relatively small number of tests and a low number of positives in our sample, credible intervals are wide and therefore results should be interpreted with caution.

In the latest six-week period, there were 16,164 swab tests, and a total of 101 positive tests, in 84 people from 65 households. In the latest two-week period, there were 5,482 swab tests, and a total of 23 positive tests, in 20 people from 18 households.

Our headline estimate of percentage testing positive in Northern Ireland is the official estimate. We include different measures to support our estimation and the below outlines the appropriate uses of all of the approaches.

Official estimates should be used to understand the positivity rate for a single point in time. This estimate, based on the modelled estimate for the latest week, is our best and most stable estimate and is used in all previous outputs. The modelled estimate can be used to understand the recent trend. The modelling includes a set period of data and smooths the estimate over time.

Figure 10: In the most recent week, the percentage of people testing positive in Northern Ireland no longer appears to be decreasing

Estimated percentage of the population in Northern Ireland testing positive for the coronavirus (COVID-19) on nose and throat swabs since 1 November 2020

Notes:

1. These results are provisional and subject to revision.

2. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

4. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data are included.

Download the data

.xlsx

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 11. These 14-day estimates are provided for context. The data are also included in the accompanying dataset.

The percentage testing positive in Northern Ireland in the latest 14-day period (29 November to 12 December 2020) was 0.50% (95% confidence interval: 0.29% to 0.80%). Caution should be taken around using the 14-day estimate, as averaging the percentage testing positive over the past 14-day period can mask changes in the percentage testing positive that have occurred over the most recent two weeks.

Notes for: Number of people in Northern Ireland who had COVID-19

1. This is based on model estimates from the reference point of the most recent week (6 to 12 December 2020), Wednesday 9 December 2020. More information on reference dates can be found in Section 14: Measuring the data.

During the most recent week of the study¹, we estimate that 52,500 people in Scotland had the coronavirus (COVID-19) (95% credible interval: 41,600 to 64,600). This equates to 1.00% (95% credible interval: 0.79% to 1.23%) of the population in Scotland or around 1 in 100 people (95% credible interval: 1 in 125 to 1 in 80). The ratios in this bulletin are rounded to the nearest five. Our modelling suggests that the percentage testing positive in Scotland has increased over the most recent week. This is based on exploratory modelling of throat and nose swab results.

Because of the relatively small number of tests and a low number of positives in our sample, credible intervals are wide and therefore results should be interpreted with caution.

In the latest six-week period, there were 39,491 swab tests, and a total of 317 positive tests, in 239 people from 191 households. In the latest two-week period, there were 12,800 swab tests, and a total of 116 positive tests, in 108 people from 93 households.

Our headline estimate of percentage testing positive in Scotland is the official estimate. We include different measures to support our estimation and the below outlines the appropriate uses of all of the approaches.

Official estimates should be used to understand the positivity rate for a single point in time. This estimate, based on the modelled estimate for the latest week, is our best and most stable estimate and is used in all previous outputs. The modelled estimate can be used to understand the recent trend. The modelling includes a set period of data and smooths the estimate over time.

Figure 12: The percentage testing positive in Scotland has increased over the most recent week

Estimated percentage of the population in Scotland testing positive for the coronavirus (COVID-19) on nose and throat swabs since 1 November 2020

Notes:

1. These results are provisional and subject to revision.

2. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

4. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data are included.

5. Estimates for Scotland do not include data for Orkney, Shetlands and the Western Isles.

Download the data

.xlsx

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 13. These 14-day estimates are provided for context. The data are also included in the accompanying dataset.

The percentage testing positive in Scotland in the latest 14-day period (29 November to 12 December 2020) was 1.01% (95% confidence interval: 0.81% to 1.24%). Caution should be taken around using the 14-day estimate, as averaging the percentage testing positive over the past 14-day period can mask changes in the percentage testing positive that have occurred over the most recent two weeks.

Notes for: Number of people in Scotland who had COVID-19

1. This is based on model estimates from the reference point of the most recent week (6 to 12 December 2020), Wednesday 9 December 2020. More information on reference dates can be found in Section 14: Measuring the data.

The estimates provided in Section 2, Section 7, Section 8 and Section 9 are for the percentage of the private-residential population testing positive for the 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 may be somewhere between 85% and 98%.

To understand the potential impact of false-positives and false-negatives, we can estimate what the prevalence would be for various different observed positivity rates under different assumptions about the test sensitivity and specificity. We do this using Bayesian analysis to calculate what prevalence would be in two different scenarios, one with medium sensitivity and the other with low sensitivity, and both with the same specificity. We can do this for any observed positivity rate.

As an example, the weighted fortnightly estimate for England between 1 and 14 November was 1.27% (95% credible interval: 1.21% to 1.33%). Under a scenario where test sensitivity is between 85% and 95%, and test specificity is between 98.5% and 100%, the weighted fortnightly estimate for England between 1 to 14 November would be 1.39% (95% credible interval: 1.27% to 1.53%). In the unlikely situation where test sensitivity was lower, between 45% and 75%, the weighted fortnightly estimate for England between 1 to 14 November would be 2.11% (95% credible interval: 1.71% to 2.80%).

You can find more information on sensitivity and specificity in our methods article. 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.

Incidence rate

The incidence rate is an estimate of how often new cases of COVID-19 occur over a given period of time. In our study, we have previously calculated this by dividing the number of times a person has a positive test for the first time in the study, having first tested negative, by the total time everyone is in the study.

We included the time people are in the study between successive negative tests for those who never have a positive test and the time up to halfway (or maximum of seven days, whichever is later) between their last negative and first positive test for those who have a positive test. This reflects the fact that we do not actually know when a person first becomes positive, only when we tested them. People who are positive when they join the study are not included in this calculation. We are currently reviewing our methods for calculating incidence as part of our ongoing quality assurance process.

Data presented in this bulletin come from the Coronavirus (COVID-19) Infection Survey, which looks to identify the percentage of the population testing positive for COVID-19 and whether they have symptoms or not. The survey helps track the current extent of infection and transmission of COVID-19 among the population as a whole. This section of the bulletin provides a short summary of the study data and data collection methods. Our methodology article provides further information around the survey design, how we process data and how data are analysed. The study protocol specifies the research for the study.

Reference dates

We aim to provide the estimates of positivity rate (the percentage of those who test positive) 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 data align perfectly, but sometimes this is not feasible. This week, the reference week is 6 to 12 December 2020.

Within the most recent week, we provide an official estimate for positivity rate and incidence 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 are 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 9 December 2020.

Response rates

At the beginning of the survey, our sample was largely made up of people in England who have taken part in previous Office for National Statistics (ONS) surveys and had agreed to future contact regarding research. We initially invited 20,276 households, and then a further 91,143 in extension weeks. Of those households invited, 42% have provided at least one swab. The likelihood of enrolment decreases over time and response rate information for those initially asked to take part in these first two phases can be considered as relatively final.

In England, we expanded our sampling at the end of July to invite a random sample of households from a list of addresses. As we have expanded, we reached out across the country to enrol new households, this different approach will affect response rates. The number of households invited to participate in the survey in this expansion in England, as of 12 December, was 908,124, of which 13% of households have provided a swab so far, increasing the number of households taking part to 183,405 to date.

Response rates for these expansion weeks 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 should not be compared with response rates for those that have taken part in a previous survey, as this is a different mode of sampling. The total number of households invited will contain households for which the mail was undeliverable and therefore could not respond.

Fieldwork began in Wales on 29 June, and the number of households initially invited to participate was 13,342, of which 29% have provided at least one swab so far. The initial sample was made up of people who had taken part in previous ONS surveys and had agreed to future contact regarding research. At the beginning of October, the survey in Wales was expanded to invite a random sample of households from a list of addresses, and as of 12 December, a further 29,122 households have been invited, of which 7% of household have provided at least one swab so far.

Fieldwork began in Northern Ireland on 26 July, and as of 12 December, 9,523 households in Northern Ireland have been invited to participate, of which 42% of households have provided at least one swab so far. The initial sample was made up of people who had taken part in previous ONS and NISRA surveys and had agreed to future contact regarding research.

Fieldwork began in Scotland on 21 September, and as of 12 December, the number of households invited to participate in the survey in Scotland, was 119,938, of which 8% have provided at least one swab. This initial sample is taken from a random sample of households from a list of addresses.

Response rates for 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. Since the survey began, we have taken just over 2 million swabs from participants across the UK.

Response rates for each nation are found in the dataset that accompanies this bulletin. We provide response rates separately for the different sampling phases of the study.

Coverage

Survey fieldwork for the pilot study began in England on 26 April 2020. Survey fieldwork in Wales began on 29 June, and since 7 August, we have reported headline figures for Wales. Survey fieldwork began in Northern Ireland on 26 July and since 25 September we have reported headline figures for Northern Ireland. Survey fieldwork in Scotland began on 21 September, and we have reported headline figures for Scotland since 23 October.

Only private residential households, otherwise known as the target population in this bulletin, are included in the sample. People in hospitals, care homes and/or other institutional settings are not included.

The overall target population for England used in this study is 54,524,766. The overall target population for Wales used in the study is 3,039,465. The overall target population for Northern Ireland used in the study is 1,834,846. The overall target population for Scotland used in the study is 5,264,705.

Sub-regional geographies

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

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

Analysing the data

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.

We continue to develop our analysis methods, and these quality enhancements may lead to minor changes in estimates, for example, the positive test counts across the study period.

We are giving increasing prominence to the weighted estimates to ensure we are giving appropriate visibility to all available indicators.

Other CIS analysis

Our recent release, Coronavirus (COVID-19) Infection Survey: characteristics of people testing positive for COVID-19 in England and antibody data for the UK: November 2020, offers more detailed analysis, including further exploration of the characteristics and behaviours of those with COVID-19, including symptoms among those testing positive by age, and patient-facing role by age. This characteristics article also includes analysis on the likelihood of testing positive for COVID-19 antibodies in England, Wales, Northern Ireland and Scotland.

Laboratory confirmed cases in the UK

Public Health England (PHE) presents data on the total number of laboratory-confirmed cases in the UK, which capture the cumulative number of people in the UK who have tested positive for COVID-19. These statistics present all known cases of COVID-19, both current and historical, for the UK, and by nation, by regions of England, and because of the large sample size, by local authority.

Further information can be found on the Coronavirus dashboard. A summary for each nation: England, Wales, Scotland and Northern Ireland is also available.

Testing and tracing systems

Each nation of the UK has a testing and tracing system: England, Wales, Northern Ireland and Scotland. These ensure that anyone who develops symptoms of COVID-19 can quickly be tested to find out if they have the virus. Some nations also include targeted asymptomatic testing of NHS and social care staff and care home residents. Additionally, it helps trace close recent contacts of anyone who tests positive for COVID-19 and, if necessary, notify them that they must self-isolate. We have recently published an article that compares the methods used in the COVID-19 Infection Survey and NHS Test and Trace in England.

In comparison with Public Health data and Testing and Tracing data, the statistics presented in this bulletin take a representative sample of the community population (those in private residential households), including people who are not otherwise prioritised for testing. This means that we can estimate the number of people in the community population with COVID-19 who do not report any evidence of symptoms.

Other studies

This study is one of a number of studies that look to provide information around the coronavirus pandemic within the UK.

COVID Symptom Study (ZOE app and King's College London), UK

The COVID Symptom Study app allows users to log their health each day, including whether or not they have symptoms of COVID-19. The study aims to predict which combination of symptoms indicate that someone is likely to test positive for COVID-19. The app was developed by the health science company ZOE with data analysis conducted by King’s College London. Anyone over the age of 18 years can download the app and take part in the study. Respondents can report symptoms of children.

The study estimates the total number of people with symptomatic COVID-19 and the daily number of new cases of COVID-19 based on app data and swab tests taken in conjunction with the Department of Health and Social Care (DHSC). The study investigates the “predictive power of symptoms”, and so the data do not capture people who are infected with COVID-19 but who do not display symptoms.

Unlike the data presented in this bulletin, the COVID Symptom Study is not a representative sample of the population. It is reliant on app users and so captures only some cases in hospitals, care homes and other communities where few people use the app. To account for this, the model adjusts for age and deprivation when producing UK estimates. The larger sample size allows for detailed geographic breakdown.

Real-time Assessment of Community Transmission-1 and -2 (REACT-1 and -2), England

Like our study, the Real-time Assessment of Community Transmission-1 REACT-1 survey, led by Imperial College London, involves taking swab samples to test for COVID-19 antigens to estimate the prevalence and transmission of the virus that causes COVID-19 in the community. Each round of the study currently involves around 160,000 participants aged five years and over, selected from a random cross-section sample of the general public from GP registration data. Trends in infection by characteristics, such as age, sex, ethnicity, symptoms and key worker status, are also possible through the study.

One of the main differences from our COVID-19 Infection Survey is that the REACT surveys do not require follow-up visits, as the study is interested primarily in prevalence at a given time point. Consequently, the incidence rate cannot be calculated from the REACT studies.

In addition, the REACT-2 study uses antibody finger-prick tests to track past infections and monitor the progress of the pandemic. Estimates in this bulletin and the REACT study use different tests and different methods, for example, the REACT estimates are based on self-administered and self-read finger prick tests, whereas tests in this survey are carried out by a trained nurse, phlebotomist or healthcare assistant.

PHE surveillance

PHE also publish an estimate of the prevalence of antibodies in the blood in England using blood samples from healthy adult blood donors. PHE provide estimates by region and currently do not scale up to England. Estimates in this bulletin and those published by PHE are based on different tests; PHE estimates are based on testing using the Euroimmun assay method, while blood samples in our survey are tested for antibodies by research staff at the University of Oxford using a novel ELISA. For more information about the antibody test used in this bulletin, see the COVID-19 Infection Survey protocol.

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.