Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: 19 October 2022

Characteristics of people testing positive for COVID-19 from the Coronavirus (COVID-19) Infection Survey.

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Contact:
Email Eleanor Fordham, Zoë Charnock and Rhian Carbury

Release date:
19 October 2022

Next release:
16 November 2022

1. Main points

  • The latest estimated rate of coronavirus (COVID-19) reinfections on 29 September 2022 was 41.6 per 100,000 participant days at risk (95% confidence interval: 40.8 to 42.5).

  • Of all identified reinfections, 92.3% occurred during the period when the Omicron variants were dominant.

  • People living in larger households or living with a long-term health condition were more likely to be reinfected.

About this bulletin

In this bulletin, we present the latest analysis on COVID-19 reinfections and risk factors associated with COVID-19 reinfection. This is part of our series of analysis on the characteristics of people testing positive for COVID-19.

Survey data up to July 2022 were collected via study worker home visits. In July 2022, we collected data both from study worker home visits and remotely, and data have been collected fully remotely since 1 August 2022. We have previously found no evidence of a difference in swab positivity between study worker home visit and remote data collection, and therefore our assessment of reinfections (which rely on positive and negative swab tests) will not be affected by the change in approach. Additionally, there have been some changes to laboratory testing whose impact we are investigating.

In this bulletin, we refer to the number of COVID-19 infections within the population living in private residential households. We exclude those in hospitals, care homes and/or other communal establishments. We include COVID-19 infections, which we define as testing positive for SARS-CoV-2, with or without having symptoms, on a swab taken from the nose and throat.

More about coronavirus

More information on our headline estimates of the overall number of positive cases in England, Wales, Northern Ireland and Scotland are available in our latest weekly bulletin. Our methodology article provides more information on the methods used for our models.

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2. COVID-19 reinfections, UK

This section estimates the rate of coronavirus (COVID-19) reinfections in the UK, from 6 December 2021 to 29 September 2022. Table 1a in our Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: dataset contains a longer series of these reinfection rate estimates from 22 March 2021 to 29 September 2022.

This analysis includes individuals who have had at least one positive swab test recorded in the survey and meet our criteria for being "at risk" of reinfection. An individual is classified as "at risk" if it is possible for a test of theirs to be considered a reinfection if it turns out to be positive. The "at-risk period" refers to the period following the first time we could have defined a reinfection based on a combination of the number of days between initial and subsequent positive tests and the number of immediately preceding negative tests, and the viral load and variant type of initial and subsequent positive tests. A reinfection is therefore only identified when an "at risk" individual has a positive test.

The technical article on reinfections provides a more detailed explanation of the methods used, however, the definition of reinfections used in this technical article has since been updated. Full details of the up-to-date definition used to identify a reinfection in this analysis can be found in Section 7: Measuring the data.

Our reinfections analysis includes first reinfections only, that is, individuals who have had a positive test for a second COVID-19 infection. For people who have had three or more COVID-19 infections, only their first and second infections are included, and their third infection (or any infections after that) are excluded.

Figure 1 presents a weekly cumulative rate of reinfections per 100,000 participant days at risk from 6 December 2021 to 29 September 2022.

The estimated rate for COVID-19 reinfections has remained high since the Omicron variants became dominant 

There has been a large increase in the rates of reinfections since the Omicron variants became dominant. The rate was 12.6 per 100,000 participant days at risk (95% confidence interval: 11.7 to 13.6) on 20 December 2021 and has since risen, remaining consistently higher than 40 per 100,000 participant days at risk over several months. There was a slight decrease since April 2022, likely because of varying levels of protection provided by past infections, including with Omicron BA.1 and BA.2, and changing background infection levels among the population.

Figure 1: The rates of reinfection have remained high since the Omicron variants became dominant

Estimated rate of coronavirus reinfections per 100,000 participant days at risk, UK, 6 December 2021 to 29 September 2022

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Notes:
  1. These estimates include first reinfections only (that is, second infections).

  2. Estimates are shown over the period when the Omicron variants were dominant up to the most recent date. A longer time series of our estimates of the rate of COVID-19 reinfection from 22 March 2021 onwards are available in our Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: dataset.

  3. We define the period when the Omicron BA.1 variant was dominant as 20 December 2021 to 1 March 2022, the period when the Omicron BA.2 variant was dominant as 2 March to 15 June 2022, and the period when the Omicron BA.4 and BA.5 variants were dominant as 16 June 2022 onwards.

Download the data

.xlsx

Figure 2 presents the percentage of first and second COVID-19 infections by the period in which different variants were dominant for participants who have experienced a reinfection in the survey.

Of all identified COVID-19 reinfections, most continued to be in the period when the Omicron variants were dominant

Of all identified reinfections, most have continued to be in the period when the Omicron variants were dominant (92.3%). A large proportion of these reinfections had first infections in the periods when the Alpha (33.8%) and Delta (34.8%) variants were dominant. A small proportion of people have had a first and second infection during the period when the same variant was dominant, but the rate is highest for those in the period when the Omicron variants were dominant (23.7%) because this period includes BA.1, BA.2, BA.4 and BA.5.

Figure 2: Of all identified reinfections, most have continued to be in the period when the Omicron variants were dominant

Percentage of first and second coronavirus infections by period in which different variants were dominant, UK, 2 July 2020 to 29 September 2022

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Notes:
  1. These estimates include first reinfections only (that is, second infections).

  2. We define the Alpha period as prior to 17 May 2021, the Delta period as 17 May to 19 December 2021, and the Omicron period as 20 December 2021 onwards. These are the periods during which these respective variants were dominant. Other variants were in circulation at the time.

Download the data

.xlsx

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3. Risk factors associated with COVID-19 reinfections, UK

This section presents analysis of the risk factors associated with a coronavirus (COVID-19) reinfection identified among participants across the UK who had previously tested positive in the survey. This analysis continues to include data from 2 July 2020 as in our previous bulletins, but now focuses on the risk of COVID-19 reinfection during the period when the Omicron BA.4 and BA.5 variants were dominant, from 16 June 2022 onwards.

Our reinfections technical article outlines the model used to investigate how the rate of reinfection varies over time and between individuals. This model explores multiple factors including:

  • age

  • sex

  • ethnicity

  • reported symptoms and cycle threshold (Ct) value observed in the initial infection

  • deprivation

  • household size

  • working in patient-facing healthcare

  • long-term health conditions

  • vaccination status

People who had their second or third vaccination 90 days or more previously were more likely to be reinfected than people who had their third vaccination 14 to 89 days previously

The risk of COVID-19 reinfection by characteristic is measured in terms of hazard ratios and presented in Table 2a of our Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: dataset.

The data show:

  • people who reported symptoms within 35 days of their first infection were less likely to be reinfected than those who did not

  • people of ethnic minorities were more likely to be reinfected than those of White ethnicities

  • those living with more people in their household were more likely to be reinfected

  • those living with long-term health conditions were more likely to be reinfected than those not living with long-term health conditions

  • people who had their second or third vaccination 90 days or more previously were more likely to be reinfected than people who had their third vaccination 14 to 89 days previously

Figure 3: People who had their second or third vaccine 90 days or more previously were more likely to be reinfected than people who had their third vaccine 14 to 89 days previously

Coronavirus reinfection hazard ratios for characteristics included in the model, UK, 16 June to 29 September 2022

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Notes:
  1. These estimates include first reinfections only (that is, second infections).

  2. A hazard ratio of greater than 1 indicates more risk in the specified group compared with the reference group, and a hazard ratio of less than 1 indicates less risk.

  3. The hazard ratio for deprivation shows how a 10-unit increase in deprivation score, where 1 represents most deprived and 100 represents least deprived, affects the likelihood of testing positive for COVID-19.

  4. Although included in the model, the effect of Ct values and age are not presented in this figure but are included in Tables 2b and 2c of our Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: dataset, respectively.

  5. This analysis continues to include data from 2 July 2020 as in our previous bulletins, but now focuses on the risk of COVID-19 reinfection during the period when the Omicron BA.4 and BA.5 variants were dominant, from 16 June 2022 onwards.

Download the data

.xlsx

In addition to these data, we also looked at the effect of Ct values at the first infection and the rate of reinfection over time by age, during the period when the Omicron BA.4 and BA.5 variants were dominant. These data can be found in Tables 2b and 2c of our Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: dataset.

Those with a lower viral load (high Ct value) at their first infection were more likely to be reinfected with COVID-19. There was a much higher initial risk of reinfection in younger children [note 1], but effects were modest overall.

Notes for: Risk factors associated with COVID-19 reinfections, UK

  1. These rates were calculated for a reference category, which was those who were male, not working in a patient-facing healthcare role, median deprivation, household size of three persons, no long-term health condition, first infection Ct value equals 20, 14 to 89 days after their third vaccine.
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4. Characteristics of people testing positive for COVID-19 data

Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK
Dataset | Released 19 October 2022
Characteristics of people testing positive for coronavirus (COVID-19) taken from the Coronavirus (COVID-19) Infection Survey

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5. 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
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6. 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.

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.

Deprivation

Deprivation is based on an index of multiple deprivation (IMD) (PDF, 2.18MB) score or equivalent scoring method for the devolved administrations, from 1, which represents most deprived up to 100, which represents least deprived. The hazard or odds ratio shows how a 10-unit increase in deprivation score, which is equivalent to 10 percentiles or 1 decile, affects the likelihood of testing positive for COVID-19.

Hazard ratio

A measure of how often a particular event happens in one group compared with how often it happens in another group, over time. When a characteristic (for example, being male) has a hazard ratio of one, this means that there is neither an increase nor a decrease in the risk of reinfection compared with a reference category (for example, being female).

Participant days at risk

The risk of reinfection varies from person to person, depending on when they were first infected. People who were first infected in the early part of the survey have had more opportunity to become reinfected compared with someone who has experienced their first infection more recently. Therefore, this analysis uses "participant days at risk" to determine the number of reinfections.

For more information, see our methodology page on statistical uncertainty.

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7. Measuring the data

More information on measuring the data is available in the Coronavirus (COVID-19) Infection Survey statistical bulletin.

Our methodology article provides further information around the survey design, how we process data and how data are analysed.

COVID-19 reinfections analysis 

All estimates of COVID-19 reinfections in Sections 2 and 3 are unweighted. The sample for this analysis includes only those who have tested positive for COVID-19 on a swab test, and so there is no known population of which weighted estimates could be representative.

Since the bulletin published 30 March 2022, we have updated our definition of a reinfection to reflect the shorter time between reinfections that have occurred during the period when most infections were with the Omicron variants, compared with earlier variants.

A reinfection was identified in this analysis if any one of the following three conditions were met.

For time since previous infection and number of negative tests, if there is either:

  • a positive test 120 days or more after an initial first positive test and following one or more negative tests

  • a positive test 90 days or more after an initial first positive test and following two or more negative tests, or, for positive tests on or after 20 December 2021 when Omicron became the main variant, following one or more negative tests

  • a positive test 60 days or more after an initial first positive test and following three or more negative tests

  • a positive test after an initial first positive test and following four or more negative tests

For high viral load:

Where both the first positive test and subsequent positive test have a high viral load, or there has been an increase in viral load between first positive test and subsequent positive tests.

For evidence of different variant types:

Where there is evidence, based on either genetic sequencing data or gene positivity from the polymerase chain reaction (PCR) swab test, that the variant differs between positive tests.

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8. Strengths and limitations

More information on strengths and limitations is available in the Coronavirus (COVID-19) Infection Survey statistical bulletin.

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10. Cite this statistical bulletin

Office for National Statistics (ONS), released 19 October 2022, ONS website, statistical bulletin, Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: 19 October 2022

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Contact details for this Statistical bulletin

Eleanor Fordham, Zoë Charnock and Rhian Carbury
infection.survey.analysis@ons.gov.uk
Telephone: +44 1633 560499