Coronavirus (COVID-19) Infection Survey, UK: 13 November 2020

• Positivity rates in England have increased in recent weeks, but the rate of increase is slower than previous weeks; during the most recent week (31 October to 6 November 2020), we estimate 654,000 people (95% credible interval: 619,400 to 689,800) within the community population in England had the coronavirus (COVID-19), equating to around 1 in 85 people (95% credible interval: 1 in 90 to 1 in 80).
• Over the last week, positivity has increased in the South East, South West, East Midlands and the North East, whereas some other regions appear to have levelled off during this time period; the highest COVID-19 infection rates remain in the North West, and Yorkshire and The Humber.
• The highest positivity rates are seen in secondary school-aged children, older teenagers and young adults; rates continue to increase in those aged 35 years and above, and rates are now decreasing in older teenagers and young adults, with rates appearing to have levelled off among younger children, teenagers and those aged 25 to 34 years.
• During the most recent week (31 October to 6 November 2020), we estimate there were 8.75 new COVID-19 infections for every 10,000 people per day (95% credible interval: 7.25 to 10.93) in the community population in England, equating to around 47,700 new cases per day (95% credible interval: 39,500 to 59,600); the incidence rate has increased in recent weeks, and remains at about 50,000 new cases per day.
• Positivity rates in Wales have increased in recent weeks; during the most recent week (31 October to 6 November 2020), we estimate that 35,300 people in Wales had COVID-19 (95% credible interval: 25,500 to 46,600), equating to 1 in 85 people (95% credible interval: 1 in 120 to 1 in 65).
• Positivity rates in Northern Ireland had increased in recent weeks but now appear to have levelled off; during the most recent week (31 October to 6 November 2020), we estimate that 17,800 people in Northern Ireland had COVID-19 (95% credible interval: 11,500 to 25,800), equating to 1 in 105 people (95% credible interval: 1 in 160 to 1 in 70).
• Positivity rates in Scotland have increased over the last six weeks but it is too early to say that they have levelled off; during the most recent week (31 October to 6 November 2020), we estimate that 39,700 people in Scotland had COVID-19 (95% confidence interval: 28,300 to 52,800), equating to 1 in 135 people (95% confidence interval: 1 in 185 to 1 in 100).

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.

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.

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
• estimating the number of positive cases and new infections in smaller geographies, such as towns and cities
• providing information about recovery time of those infected

During the most recent week of the study, we estimate that 654,000 people in England had the coronavirus (COVID-19) (95% credible interval: 619,400 to 689,800)¹. This equates to 1.20% (95% credible interval: 1.14% to 1.27%) of the population in England or around 1 in 85 people (95% credible interval: 1 in 90 to 1 in 80). The ratios presented are rounded to the nearest 5. This is based on statistical modelling of the trend in rates of positive nose and throat swab results.

Official estimates of infection rates over time are presented in Figure 1. The most recent estimate shows the infection rate continues to increase, but the rate of increase is slower than previous weeks.

In the latest six-week period, there were 668,176 swab tests, and a total of 5,417 positive tests, in 4,098 people from 3,144 households. In the latest two-week period, there were 192,516 swab tests, and a total of 2,120 positive tests, in 1,898 people from 1,474 households.

To provide stability in estimates, we advise using estimates we published in previous bulletins as these are our official estimates of the rate and spread of COVID-19 infections in the community in England. Both these and the modelled estimates are presented in Figure 3, and official estimates are used to interpret change over time.

As this is a household survey, our figures do not include people staying in hospitals, care homes 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: The number of infections in England has increased in recent weeks, but the rate of increase is slower than previous weeks

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. 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.

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The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 2. 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 2 overlap with those presented in the datasets in our previous publication, so direct comparisons are not possible.

The percentage testing positive in the latest 14-day period (24 October to 6 November 2020) was 1.34% (95% confidence interval: 1.27% to 1.40%).

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

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 3: The most recent modelled estimate shows the number of infections in England has increased in recent weeks, but the rate of increase is slower than previous weeks

Estimated percentage of the population in England testing positive for the coronavirus (COVID-19) on nose and throat swabs based on modelled estimates from 26 September 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.

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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 (31 October to 6 November 2020), Tuesday 3 November 2020. More information on reference dates can be found in Section 13: 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 (31 October to 6 November 2020), the highest rates continue to be seen in the North West, and Yorkshire and The Humber where rates are now much closer together. The group of regions with the next highest rates are the North East, the East Midlands and the West Midlands, however, a large gap remains with the North West, and Yorkshire and The Humber.

Rates remain highest in the North West, and Yorkshire and The Humber. Over the last week, positivity has increased in the South East, South West, East Midlands and the North East, whereas some other regions appear to have levelled off during this time period. Caution should be taken in over-interpreting any small movements, particularly if they are already at a high level.

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 last week, positivity has increased in the South East, South West, East Midlands and the North East

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by region since 26 September 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.

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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.

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).

Positivity rates continue to increase in those aged 35 years and over and are now above 1% amongst those aged 35 to 49 and 50 to 69 years. The highest rates are seen among secondary school-aged children and older teenagers and young adults, although rates are now decreasing amongst older teenagers and young adults. Positivity rates appear to have levelled off among younger children and teenagers, as well as those aged 25 to 34 years. 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 6: Rates continue to increase in those aged 35 years and above, and rates are now decreasing in older teenagers and young adults

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by age group since 26 September 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.

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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.

Based on statistical modelling, we estimate that during the most recent week of the study¹ (31 October to 6 November 2020), there were 8.75 new coronavirus (COVID-19) infections per 10,000 people per day (95% credible interval: 7.25 to 10.93)¹. This equates to 47,700 new infections per day (95% credible interval: 39,500 to 59,600).

Credible intervals are wide and overlap with the previous week’s estimate. The incidence rate has increased in recent weeks, and the number of new infections per day remains around 50,000. The credible intervals are larger in the most recent periods because the model does not include people after their last swab result in the study to date, so the sample size for the most recent days is smaller, resulting in wider credible intervals. Because of instability in the data in the most recent week, we are no longer modelling data beyond the reference date.

The modelling used to calculate the incidence rate is a Bayesian model that is based on the same approach used for estimating the positivity rates in this bulletin. The model uses all swab test results to estimate the incidence rate of new infections for each different type of respondent (by age, sex and region) who tested negative when they first joined the study. It is made to be representative of the overall population using population data. More information on the methodology of this approach is available.

We are continually refining the way we estimate incidence and continue to present the absolute numbers for transparency in the dataset that accompanies this bulletin.

Figure 7: The incidence rate has increased in recent weeks

Estimated numbers of new infections with the coronavirus (COVID-19), England, based on nose and throat swabs with modelled estimates from 20 September 2020

Notes:

1. All results are provisional and subject to revision.
2. Credible intervals are large at the end of plot because there is less information available. At the end the model does not include people when their next swab result is not known, so the sample size for the most recent days is smaller, resulting in wider credible intervals.
3. This model does not control for household clustering, where multiple new cases derive from the same household.
4. Official reported estimates are plotted at a reference point believed to be most representative of the reference week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.
5. Modelled estimates include additional time at risk up to swab test results not available when the official reported estimates were produced.
6. Initial unweighted estimates covering the full study period to date are not included in the official reported estimates chart.
7. Because of instability in the modelled estimates in the most recent week, we are no longer modelling data beyond the reference date.

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The incidence rate measures the occurrence of new cases of COVID-19, and the calculation of this is defined in Section 12: Glossary. The incidence rate is not the same as the reproduction rate (R), which is the average number of secondary infections produced by one infected person.

To calculate the estimated average number of people becoming newly infected per day, we multiply the daily incidence rate by the community population (see Coverage in Section 13: Measuring the data). We use the unrounded incidence rate to do this, so results will differ if calculated using the rounded estimates from the dataset.

Notes for: Incidence rate in England

1. This is based on model estimates from the reference point of the most recent week (31 October to 6 November 2020), Saturday 31 October 2020. More information on reference dates can be found in Section 13: Measuring the data.  

During the most recent week of the study¹, we estimate that 35,300 people in Wales had the coronavirus (COVID-19) (95% credible interval: 25,500 to 46,600). This equates to 1.16% (95% credible interval: 0.84% to 1.53%) of the population in Wales or around 1 in 85 people (95% credible interval: 1 in 120 to 1 in 65). The ratios are rounded to the nearest 5.

Our modelling suggests that the number of COVID-19 cases in Wales has increased in recent weeks. 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 16,638 swab tests, and a total of 113 positive tests, in 86 people from 67 households. In the latest two-week period, there were 5,429 swab tests, and a total of 53 positive tests, in 49 people from 40 households.

Figure 8: Positivity rates in Wales have increased in recent weeks

Estimated percentage of the population in Wales testing positive for the coronavirus (COVID-19) on nose and throat swabs since 26 September 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 percentage testing positive in Wales in the latest 14-day period (24 October to 6 November 2020) was 1.27% (95% confidence interval: 0.92% to 1.72%).

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 (31 October to 6 November 2020), Tuesday 3 November 2020. More information on reference dates can be found in Section 13: Measuring the data.

During the most recent week of the study¹, we estimate that 17,800 people in Northern Ireland had the coronavirus (COVID-19) (95% credible interval: 11,500 to 25,800). This equates to 0.97% (95% credible interval: 0.62% to 1.41%) of the population in Northern Ireland or around 1 in 105 people (95% credible interval: 1 in 160 to 1 in 70). The ratios in this bulletin are rounded to the nearest 5.

Our modelling suggests that positivity rates in Northern Ireland had increased in recent weeks but now appear to have levelled off. 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 12,002 swab tests, and a total of 103 positive tests, in 72 people from 52 households. In the latest two-week period, there were 3,495 swab tests, and a total of 36 positive tests, in 30 people from 24 households.

Figure 10: Positivity rates in Northern Ireland had increased in recent weeks but now appear to have levelled off

Estimated percentage of the population in Northern Ireland testing positive for the coronavirus (COVID-19) on nose and throat swabs since 26 September 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 (24 October to 6 November 2020) was 1.19% (95% confidence interval: 0.77% to 1.75%).

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 (31 October to 6 November 2020), Tuesday 3 November 2020. More information on reference dates can be found in Section 13: Measuring the data.

This week we have introduced modelled daily estimates for Scotland, please note that these are not directly comparable with the 14-day weighted estimates.

During the most recent week of the study¹, we estimate that 39,700 people in Scotland had the coronavirus (COVID-19) (95% credible interval: 28,300 to 52,800). This equates to 0.75% (95% credible interval: 0.54% to 1.00%) of the population in Scotland or around 1 in 135 people (95% credible interval: 1 in 185 to 1 in 100). The ratios in this bulletin are rounded to the nearest 5.

Our modelling suggests that positivity rates in Scotland have increased over the last six weeks but it is too early to say whether rates are levelling off. 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 19,796 swab tests, and a total of 112 positive tests, in 77 people from 59 households. In the latest two-week period, there were 7,714 swab tests, and a total of 57 positive tests, in 52 people from 39 households.

Figure 12: Positivity rates in Scotland have increased over the last six weeks, it is too early to say whether rates are levelling off

Estimated percentage of the population in Scotland testing positive for the coronavirus (COVID-19) on nose and throat swabs since 26 September 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 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 (24 October to 6 November 2020) was 1.06% (95% confidence interval: 0.77% to 1.42%).

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 (31 October to 6 November 2020), Tuesday 3 November 2020. More information on reference dates can be found in Section 13: Measuring the data.

The estimates provided in Section 2, Section 6, Section 7 and Section 8 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, as COVID-19 is a new virus, 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%. To understand the potential impact of false-positives and false-negatives, we have estimated what the prevalence would be in two scenarios using different test sensitivity and the same specificity rates. We do not know the sensitivity of the swab test. However, other studies suggest that sensitivity may be somewhere between 85% and 98%.

Under a scenario where test sensitivity is between 85% and 95%, and test specificity is between 98.5% and 100%, the most recent weighted fortnightly estimate for England would be 1.46% (95% credible interval: 1.34% to 1.61%). In the unlikely situation where test sensitivity was lower, between 45% and 75%, the weighted fortnightly estimate for England would be 2.22% (95% credible interval: 1.80% to 2.93%).

For this reason, we do not produce prevalence estimates for every analysis, but we will continue to monitor the impacts of sensitivity and specificity in future.

You can find more information on sensitivity and specificity in our methods article. You can find more information on cycle thresholds 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, it is calculated 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 include 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.

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 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 data align perfectly, but sometimes this is not feasible. This week, the reference week falls between 31 October to 6 November 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 positivity 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 Tuesday 3 November 2020.

The calculation of incidence uses time between two tests; so, for example, a participant who was last seen two weeks ago and is not due their next visit for another two weeks only contributes to the model up to two weeks ago. Our official estimates of incidence are therefore based on the first day of the reference week. This week, the reference day for incidence is Saturday 31 October 2020. The model includes all information up to 31 October (the start of the reference week); we now model data up until the reference day only, as the data up until this point are more complete.

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, 40% 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 6 November, was 908,124, of which 11% of households have provided a swab so far, increasing the number of households taking part to 142,462 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 10,844, 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 6 November, a further 15,678 households have been invited, of which 5% of household have provided at least one swab so far.

Fieldwork began in Northern Ireland on 26 July, and as of 6 November, 7,040 households in Northern Ireland have been invited to participate, of which 34% 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 6 November, the number of households invited to participate in the survey in Scotland, was 74,312, of which 5% 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 over 1.4 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.

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, October 2020, offers more detailed analysis, including further exploration of the characteristics and behaviours of those with COVID-19, such as symptoms among those testing positive, region by age, and travel abroad by time.

Laboratory confirmed cases in the UK

Public Health England (PHE) present 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: for 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.