Coronavirus (COVID-19) Infection Survey, UK: 18 March 2022

Estimates for England, Wales, Northern Ireland and Scotland. This survey is being delivered in partnership with University of Oxford, University of Manchester, UK Health Security Agency and Wellcome Trust. This study is jointly led by the Office for National Statistics (ONS) and the Department for Health and Social Care (DHSC) working with the University of Oxford and Lighthouse laboratory to collect and test samples. 

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Contact:
Email Rhiannon Yapp, Jasmin Roberts and Elizabeth Fuller

Release date:
18 March 2022

Next release:
25 March 2022

1. Main points

  • In England, the percentage of people testing positive for coronavirus (COVID-19) continued to increase in the week ending 12 March 2022; we estimate that 2,653,200 people in England had COVID-19 (95% credible interval: 2,571,500 to 2,739,700), equating to 4.87% of the population or around 1 in 20 people.

  • In Wales, the percentage of people testing positive for COVID-19 continued to increase in the week ending 12 March 2022; we estimate that 125,400 people in Wales had COVID-19 (95% credible interval: 108,100 to 144,900), equating to 4.13% of the population or around 1 in 25 people.

  • In Northern Ireland, the percentage of people testing positive for COVID-19 increased in the two weeks up to 12 March 2022, but the trend was uncertain in the most recent week; we estimate that 130,600 people in Northern Ireland had COVID-19 (95% credible interval: 113,100 to 149,100), equating to 7.12% of the population or around 1 in 14 people.

  • In Scotland, the percentage of people testing positive for COVID-19 continued to increase in the week ending 12 March 2022; we estimate that 376,300 people in Scotland had COVID-19 (95% credible interval: 345,400 to 409,900), equating to 7.15% of the population or around 1 in 14 people.

  • In the week ending 12 March 2022, the percentage of infections compatible with the Omicron BA.2 variant increased in England, Wales and Scotland and the trend was uncertain in Northern Ireland; the percentage of infections compatible with the Omicron BA.1 variant decreased in England, Northern Ireland and Scotland and the trend was uncertain in Wales.

Within this bulletin, we summarise some of the latest results from the Coronavirus (COVID-19) Infection Survey. For more detailed information on our methods see our Coronavirus (COVID-19) Infection Survey methodology article. You can also find out more about comparing methods used in the Coronavirus (COVID-19) Infection Survey and NHS Test and Trace in our article, to better understand comparisons in data sources.

About this bulletin

In this bulletin, we refer to the number of current COVID-19 infections within the population living in private residential households. We exclude those in hospitals, care homes and/or other communal establishments. In communal establishments, rates of COVID-19 infection are likely to be different. More information about the COVID-19 pandemic from the Office for National Statistics (ONS) and other sources can be found in our Coronavirus (COVID-19) latest insights.

The positivity rate is the percentage of people who have tested positive for COVID-19 on a polymerase chain reaction (PCR) test at a point in time. We use current COVID-19 infections to mean testing positive for SARS-CoV-2, with or without having symptoms, on a swab taken from the nose and throat. This is different to the incidence rate, which is a measure of only the new PCR positive cases in a given time period. All analysis was produced with our research partners at the University of Oxford.

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

More about coronavirus

Early management information from the Coronavirus (COVID-19) Infection Survey is made available to government decision-makers to inform their response to COVID-19. Occasionally we may publish figures early if it is considered in the public interest. We will ensure that we pre-announce any ad hoc or early publications as soon as we can. These will include supporting information where possible to aid user understanding. This is consistent with guidance from the Office for Statistics Regulation (OSR).

How the data in this bulletin can be used

The data can be used for:

  • estimating the number of positive cases among the population living in private households, including cases where people do not report having any symptoms
  • identifying differences in numbers of positive cases between UK countries and different regions in England
  • estimating the number of new cases and change 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 communal establishments
  • providing information about recovery time of those infected

The results in this bulletin are:

  • provisional and subject to revision
  • based on infections occurring in private households
  • subject to uncertainty, a credible or confidence interval gives an indication of the uncertainty of an estimate from data analysis
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2. Percentage of people who had COVID-19 in UK countries

In England, Wales and Scotland, the percentage of people testing positive for coronavirus (COVID-19) increased in the week ending 12 March 2022. In Northern Ireland, the percentage of people testing positive for COVID-19 increased in the two weeks up to 12 March 2022, but the trend was uncertain in the most recent week. Our estimates contain Omicron BA.1 and BA.2 variants and all other variants.

All estimates are based on statistical modelling of the trend in rates of positive nose and throat swab results. All estimates are subject to uncertainty given that a sample is only part of the wider population. Additionally, the estimates for the very latest days may change as more test results are received. Therefore, caution should be taken in over-interpreting small movements in the latest trends.

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Because of a relatively smaller number of tests in Wales, Northern Ireland and Scotland in the sample, credible intervals are wider, and results should be interpreted with caution. Wide credible intervals mean that differences between the central estimates within and between nations may appear smaller or more exaggerated than they really are.

Figure 1: The percentage of people testing positive for COVID-19 continued to increase in England, Wales and Scotland and the trend was uncertain in Northern Ireland in the most recent week

Estimated percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs, UK, 21 March 2021 to 12 March 2022

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Notes:

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

  2. Official estimates present the best estimate at that point in time. Modelled estimates are used to calculate the official reported estimate. The model smooths the series to understand the trend and is revised each week to incorporate new test results, providing the best indication of trend over time.

  3. Official estimates are displayed over a rolling year up to the most recent week. The full time series of our official estimates from 27 April 2020 onwards are available in the Coronavirus (COVID-19) Infection Survey datasets.

Download the data

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About our estimates

Our headline estimates of the percentage of people testing positive in England, Wales, Northern Ireland and Scotland are the latest official estimates. We include different measures to support our estimation and this section outlines the approaches used.

Official estimates should be used to understand the positivity rate for a single point in time. This is based on the modelled estimate for the latest week and is our best and most stable estimate, used in all previous outputs. The modelled estimate is more suited to understanding the recent trend. This is because the model is regularly updated to include new test results and smooths the trend over time. These modelled estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) and the unweighted sample counts are also included in the associated datasets. These estimates are produced using a different method of weighting to the model. For more information on our methods and quality surrounding the estimates please see our Coronavirus (COVID-19) Infection Survey methods article and Quality and Methodology Information report.

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.

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3. Sub-national analysis of the percentage of people who had COVID-19

In the week ending 12 March 2022, the percentage of people testing positive for coronavirus (COVID-19) increased across all regions of England.

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

Figure 2: The percentage of people testing positive for COVID-19 increased across all regions of England in the week ending 12 March 2022

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by region, England, 30 January to 12 March 2022

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Notes:

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

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

  3. The analysis is conducted over a six-week period, which means specific positive cases move in and out of the sample. This causes variability between estimates over time, which is expected given the lower number of positive tests in each region, compared with England as a whole.

  4. We describe trends by comparing the probability that the estimate for the reference day is higher or lower than the estimate for 7 and 14 days prior.

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Estimates for non-overlapping 14-day periods (which underpin our modelled estimates) by region are available in our Coronavirus (COVID-19) Infection Survey datasets.

Sub-regional analysis of the UK

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Sub-regional estimates are based on a different model to our headline national estimates and should not be compared. The number of people sampled in each sub-regional area who tested positive is lower compared with the number testing positive in their respective national samples. This means there is more uncertainty in sub-regional estimates and caution should be taken when interpreting or ranking them.

The percentage of people testing positive for COVID-19 varied across sub-regions of the UK. Figure 3 presents modelled estimates for sub-regions of all UK countries in the week ending 12 March 2022 for England, Wales, Northern Ireland and Scotland.

Figure 3: The percentage of people testing positive for COVID-19 by UK sub-regions

Modelled percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by sub-regional geography, UK, 6 March to 12 March 2022

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Notes:

  1. Sub-regional estimates are based on a different model to our headline estimates. Our sub-regional estimates are calculated as an average over a seven-day period and should not be compared with our headline positivity estimates, which are for a single reference date. Therefore, the subregional figures may differ from the headline estimates because they are averaged over a longer time period. If a trend is changing quickly, the figures shown in Figure 3 may not reflect the change we are seeing in our headline estimates.

  2. The colour scale has been adjusted from the 7 January 2022 publication onwards to accommodate for increased infection levels and is not comparable with sub-regional charts in previous bulletins.

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4. Age analysis of the percentage of people who had COVID-19

Age analysis by category for England

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

  • "aged 2 years to school Year 6" includes children in primary school and below
  • "school Year 7 to school Year 11" includes children in secondary school
  • "school Year 12 to those aged 24 years" includes young adults who may be in further or higher education

Those aged from 11 to 12 years and those aged 16 to 17 years have been split between different age categories depending on whether their birthday is before or after 1 September.

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Estimates are based on smaller sample sizes within each age group relative to England overall. There is a higher degree of uncertainty as indicated by larger credible intervals. These can be found in the Coronavirus (COVID-19) Infection Survey: England dataset.

In the week ending 12 March 2022, the percentage of people testing positive for coronavirus (COVID-19) in England increased in all age groups.

Figure 4: The percentage of people testing positive for COVID-19 increased in all age groups in the week ending 12 March 2022

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by age group, England, 30 January to 12 March 2022

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Notes:

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

.xlsx

Estimates for non-overlapping 14-day periods (which underpin our modelled estimates) by age are available in our Coronavirus (COVID-19) Infection Survey datasets.

We are unable to produce the same grouped analysis as presented in Figure 4 for the devolved administrations because of smaller sample sizes within each age group. However, estimates on positivity by single year of age for Wales, Northern Ireland and Scotland using a different model can be found in the following section and the accompanying datasets.

Age analysis by single year of age over time by country

In this section, we present modelled daily estimates of the percentage testing positive for COVID-19 by single year of age over time from 30 January to 12 March 2022 for England, Wales, Northern Ireland and Scotland. They are produced using a different method to the grouped age analysis for England presented previously and are therefore not comparable. Caution should be taken in over-interpreting small movements in positivity day to day.

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Estimates are based on smaller sample sizes within each age group in comparison with the total sample size for each country. There is a higher degree of uncertainty as indicated by larger confidence intervals. These can be found in the Coronavirus (COVID-19) Infection Survey datasets.

The data presented in Figure 5 for England suggests that the percentage of people testing positive has increased in all ages in the most recent week.

In Wales, the percentage of people testing positive increased in adults aged 20 years and over but the trend was uncertain for younger ages.

In Northern Ireland, the percentage of people testing positive increased in adults aged over 60 years. The percentage of school-aged children testing positive decreased in the most recent week and the trend was uncertain in young adults.

In Scotland, the trend in the percentage of nursery and primary school-aged children testing positive was uncertain in the most recent week. For all other ages, the percentage of people testing positive increased in the most recent week.

Further analysis on age for WalesNorthern Ireland and Scotland is published by their respective statistical agencies. Analysis for Wales is published in English and Welsh.

Figure 5: The percentage of people testing positive for COVID-19 by single year of age over time for England, Wales, Northern Ireland and Scotland

Modelled daily percentage of the population testing positive for coronavirus (COVID-19) on nose and throat swabs by single year of age, UK, 30 January to 12 March 2022

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Notes:

  1. These estimates use a different method to modelled daily estimates of the percentage testing positive by age group for England in the previous section and are therefore not comparable.
Download the data

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5. Number of new COVID-19 infections in UK countries

The incidence rate is a measure of new polymerase chain reaction (PCR)-positive cases per day per 10,000 people in a given time period. In this section, we look at an earlier time period to our analysis of the percentage testing positive. We include estimates of the incidence rate in our Coronavirus (COVID-19) Infection Survey datasets and in Table 2.

In the week ending 26 February 2022, the number of new PCR-positive COVID-19 cases per day increased in England and Scotland. In the same week, the trend in number of new PCR-positive COVID-19 cases per day was uncertain in Wales and Northern Ireland. Credible intervals are wider for Wales, Northern Ireland and Scotland because of relatively smaller sample sizes, and care should be taken in interpreting results.

The reference date used for our official estimates of incidence of PCR-positive cases is 14 days before the positivity reference day, meaning that there is a two-week lag between the incidence estimate and the positivity estimate. This is necessary as estimates later than this date are more likely to change as we receive additional data. While we believe that the incidence estimates are useful, they can be volatile and subject to change as more data become available. For more information on how we calculate estimates of incidence please see Coronavirus (COVID-19) Infection Survey: methods and further information.

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6. Analysis of viral load and variants of COVID-19

We publish weekly Cycle-threshold (Ct) values and a breakdown of infections by variant, based on gene positivity patterns from our swab tests. The "Cycle threshold", known as a Ct value, is a proxy for the quantity of virus (also known as viral load), where a lower Ct value indicates higher viral load. The Ct values of coronavirus (COVID-19) positive tests are provided in the Coronavirus (COVID-19) Infection Survey: technical dataset.

The Omicron variant BA.1 has changes in one of the three genes that the coronavirus survey swab test detects, which means the S-gene is no longer detected. When there is a high viral load (for example, when a person is most infectious), not detecting the S-gene in combination with detecting the other two genes (ORF1ab and N-genes) is a reliable indicator of this Omicron BA.1 variant. However, as the viral load decreases (for example, if someone is near the end of their recovery from the infection), not detecting the S-gene is a less reliable indicator of this Omicron variant.

The Omicron variant BA.2 does not have changes in the S-gene, and therefore all three genes, or the S-gene and either ORF1ab or N, will usually be detected in infections with this variant. Delta also does not have changes in the S-gene, and therefore the same sets of genes will usually be detected with the Delta and Omicron BA.2 variants. Our genome sequencing analysis shows that almost all infections where we detect the S-gene are now the Omicron BA.2 variant. For this reason, we now label cases with gene patterns ORF1ab + N + S, ORF1ab + S and N + S as "compatible with the Omicron BA.2 variant" in our main variant analysis.

Our latest complete sequenced data are for the week ending 13 March 2022 and show that the Omicron BA.2 variant is now the most common variant in England, Wales, Northern Ireland and Scotland. In this week, 76.1% of all sequenced COVID-19 infections from the survey were compatible with the Omicron BA.2 variant, and 23.9% were compatible with the Omicron BA.1 variant or its sub-variants.

Our main variant analysis is for a reference day, and therefore is not directly comparable with the sequencing data. The following analysis looks at the percentage of the population with a positive test compatible with the Omicron BA.1 or BA.2 variant in England, Wales, Northern Ireland and Scotland, and the regions of England.

During periods of change in COVID-19 variants we will include a breakdown of estimated infections by variant to illustrate how the estimated percentage of people infected in the population is changing by variant (Figure 6). When nearly all infections are compatible with a dominant variant, we will no longer include this breakdown.

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Data should be treated with caution. There could be small numbers of positive cases compatible with a particular variant in Wales, Scotland and Northern Ireland, leading to considerable uncertainty surrounding these estimates. Not all cases that are positive on the ORF1ab and N-genes will be the Omicron BA.1 variant, and not all cases that have a detectable S-gene will be the Omicron BA.2 variant.

The percentage of infections compatible with the Omicron BA.2 variant increased across England, Wales and Scotland in the week up to 12 March 2022. In Northern Ireland, the percentage of infections compatible with the Omicron BA.2 variant increased over the most recent two weeks up to 12 March 2022, but the trend was uncertain in the most recent week.

In the same week, the percentage of infections compatible with the Omicron BA.1 variant decreased in England, Northern Ireland and Scotland. In Wales, the percentage of infections compatible with the Omicron BA.1 variant decreased over the most recent two weeks up to 12 March 2022, but the trend was uncertain in the most recent week.

Figure 6: The percentage of infections compatible with the Omicron BA.2 variant increased across England, Wales and Scotland and the trend was uncertain in Northern Ireland in the most recent week

Modelled percentage of the population testing positive for infections compatible with the Omicron BA.1 variant and Omicron BA.2 variant, based on nose and throat swabs, daily, UK, 30 January to 12 March 2022

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Notes:

  1. Omicron BA.1 variant-compatible positives are defined as those that are positive on the ORF1ab-gene and N-gene, but not the S-gene. This group includes Omicron BA.1.1.
  2. Omicron BA.2 variant-compatible positives are defined as those that are positive on the ORF1ab-gene, N-gene and S-gene, or on the ORF1ab-gene and S-gene or on the N-gene and S-gene.
  3. Data should be treated with caution. Not all infections positive on the S-gene will be the Omicron BA.2 variant, and some infections with pattern ORF1ab+N will also be the Omicron BA.2 variant where the S-gene was not detected for other reasons, such as low viral load.
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In the week ending 12 March 2022, the percentage of infections compatible with the Omicron BA.2 variant increased in all regions of England. In the same week, the percentage of infections compatible with the Omicron BA.1 variant decreased in all regions of England except for the North East and East Midlands where the trend was uncertain. Caution should be taken in over-interpreting any small movements in the latest trend. These modelled estimates can be found in the Coronavirus (COVID-19) Infection Survey datasets.

The World Health Organization (WHO) have defined names for variants of concern. These are variants that the UK government has under surveillance. You can find out more in the latest SARS-CoV-2 variants of concern and variants under investigation in England briefing document.

Currently circulating variants of concern in the UK are:

  • Delta: B.1.617.2 and its genetic descendants
  • Omicron: B.1.1.529 (which includes sublineages BA.1, BA.1.1, BA.2 and BA.3)

Our Coronavirus (COVID-19) Infection Survey: technical dataset includes analysis of the genetic lineages of coronavirus seen in the samples we sequence. More information on how we measure variants from positive tests on the survey can be found in our Understanding COVID-19 variants blog. Our Coronavirus (COVID-19) Infection Survey methods article gives more detail about how we sequence the virus' genetic material.

The sequencing is produced by Northumbria University and analysis is produced by research partners at the University of Oxford. Of particular note are Dr Katrina Lythgoe, Dr Tanya Golubchik and Dr Helen Fryer. Genome sequencing is funded by the COVID-19 Genomics UK (COG-UK) consortium. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research and Innovation (UKRI), the National Institute of Health Research (NIHR), and Genome Research Limited operating as the Wellcome Sanger Institute.

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7. Test sensitivity and specificity

The estimates provided in Sections 2 to 6 are for the percentage of the private-residential population testing positive for coronavirus (COVID-19), otherwise known as the positivity rate. We do not report the prevalence rate. To calculate the prevalence rate, we would need an accurate understanding of the swab test's sensitivity (true-positive rate) and specificity (true-negative rate).

While we do not know the true sensitivity and specificity of the test, our data and related studies provide an indication of what these are likely to be. In particular, the data suggest that the false-positive rate is very low - under 0.005%. We do not know the sensitivity of the swab test. However, other studies suggest that sensitivity (the rate of true-positive test results) may be somewhere between 85% and 98%.

You can find more information on sensitivity and specificity in our Coronavirus (COVID-19) Infection Survey methods article and our blog that explains why we trust the data from the Coronavirus (COVID-19) Infection Survey. You can find more information on the data suggesting that our test's false-positive rate is very low in a paper written by academic partners at the University of Oxford.

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8. Coronavirus (COVID-19) Infection Survey data

Coronavirus (COVID-19) Infection Survey: England
Dataset | Released 18 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for England.

Coronavirus (COVID-19) Infection Survey: Northern Ireland
Dataset | Released 18 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Northern Ireland.

Coronavirus (COVID-19) Infection Survey: Scotland
Dataset | Released 18 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Scotland.

Coronavirus (COVID-19) Infection Survey: Wales
Dataset | Released 18 March 2022
Findings from the Coronavirus (COVID-19) Infection Survey for Wales.

Coronavirus (COVID-19) Infection Survey: technical data
Dataset | Released 18 March 2022
Technical and methodological data from the Coronavirus (COVID-19) Infection Survey, England, Wales, Northern Ireland and Scotland.

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9. Collaboration

Logos for London School of Hygiene and Tropical Medicine and Public Health England

The Coronavirus (COVID-19) Infection Survey analysis was produced by the Office for National Statistics (ONS) in collaboration with our research partners at the University of Oxford, the University of Manchester, UK Health Security Agency (UK HSA) and Wellcome Trust. Of particular note are:

  • Sarah Walker - University of Oxford, Nuffield Department for Medicine: Professor of Medical Statistics and Epidemiology and Study Chief Investigator
  • Koen Pouwels - University of Oxford, Health Economics Research Centre, Nuffield Department of Population Health: Senior Researcher in Biostatistics and Health Economics
  • Thomas House - University of Manchester, Department of Mathematics: Reader in Mathematical Statistics
  • Anna Seale - University of Warwick, Warwick Medical School: Professor of Public Health; UK Health Security Agency, Data, Analytics and Surveillance: Scientific Advisor
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10. Glossary

Confidence interval

A confidence interval gives an indication of the degree of uncertainty of an estimate, showing the precision of a sample estimate. The 95% confidence intervals are calculated so that if we repeated the study many times, 95% of the time the true unknown value would lie between the lower and upper confidence limits. A wider interval indicates more uncertainty in the estimate. Overlapping confidence intervals indicate that there may not be a true difference between two estimates. For more information, see our methodology page on statistical uncertainty.

Credible interval

A credible interval gives an indication of the uncertainty of an estimate from data analysis. The 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

Cycle threshold (Ct) values

The strength of a positive coronavirus (COVID-19) test is determined by how quickly the virus is detected, measured by a cycle threshold (Ct) value. The lower the Ct value, the higher the viral load and stronger the positive test. Positive results with a high Ct value can be seen in the early stages of infection when virus levels are rising, or late in the infection, when the risk of transmission is low.

False-positives and false-negatives

A false-positive result occurs when the tests suggest a person has COVID-19 when in fact they do not. By contrast, a false-negative result occurs when the tests suggest a person does not have COVID-19 when in fact they do. For more information on false-positives and false-negatives, see our methods article and our blog.

Incidence rate

The incidence rate is a measure of the estimated number of new polymerase chain reaction (PCR)-positive cases per day per 10,000 people at a given point in time. It is different to positivity, which is an estimate of all current PCR positive cases at a point in time, regardless of whether the infection is new or existing.

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11. Measuring the data

Reference dates

We aim to provide the estimates of positivity rate (the percentage of those who test positive) and incidence that are most timely and most representative of each week. We decide the most recent week we can report on based on the availability of test results for visits that have already happened, accounting for the fact that swabs have to be couriered to the labs, tested and results returned. On most occasions, the reference dates align perfectly, but sometimes this is not feasible. This week, the reference week for positivity is 6 March to 12 March 2022 for England, Wales, Northern Ireland and Scotland.

Within the most recent week, we provide an official estimate for positivity rate based on a reference point from the modelled trends. For positivity rates, we can include all swab test results, even from the most recent visits. Therefore, although we are still expecting further swab test results from the labs, there were sufficient data for the official estimate for infection to be based on a reference point after the start of the reference week. To improve stability in our modelling while maintaining relative timeliness of our estimates, we are reporting our official estimates based on the midpoint of the reference week. This week, the reference day for positivity rates is Wednesday 9 March 2022 for England, Wales, Northern Ireland and Scotland.

The reference date used for our official estimates of incidence of polymerase chain reaction (PCR)-positive cases is 14 days prior to the positivity reference day. This is necessary as estimates later than this date are more likely to change as we receive additional data. This week, the reference week for incidence is 20 to 26 February 2022 and the reference day is Wednesday 23 February 2022 for all UK countries.

Response rates

Enrolment for this wave of recruitment for the Coronavirus (COVID-19) Infection Survey ceased on 31 January 2022. Response rates for England, Wales, Northern Ireland and Scotland can be regarded as final response rates to the survey. Response rates for each nation are found in the Coronavirus (COVID-19) Infection Survey: technical dataset. We provide response rates separately for the different sampling phases of the study. Additional information on response rates can be found in our Coronavirus (COVID-19) Infection Survey methods article.

Survey fieldwork

Survey fieldwork for the pilot study began in England on 26 April 2020. In Wales, fieldwork began on 29 June 2020, in Northern Ireland fieldwork began on 26 July 2020 and in Scotland fieldwork began on 21 September 2020.

Sub-regional geographies

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

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

Other Coronavirus Infection Survey (CIS) analysis and studies

This study is one of a number of studies that look to provide information around the coronavirus pandemic within the UK. For information on other studies see Section 5: Quality characteristics of the Coronavirus (COVID-19) Infection Survey (coherence and comparability), revised 16 July 2021.

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12. Strengths and limitations

These statistics have been produced quickly in response to developing world events. The Office for Statistics Regulation (OSR), on behalf of the UK Statistics Authority, has reviewed them on 14 May 2020 and 17 March 2021 against several important aspects of the Code of Practice for Statistics and regards them as consistent with the Code's pillars of trustworthinessquality 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 Coronavirus (COVID-19) Infection Survey Quality and Methodology Information report, our methodology article, and our blog that explains why we trust the data from the Coronavirus (COVID-19) Infection Survey.

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Contact details for this Statistical bulletin

Rhiannon Yapp, Jasmin Roberts and Elizabeth Fuller
infection.survey.analysis@ons.gov.uk
Telephone: +44 1633 560499