Winter Coronavirus (COVID-19) Infection Study: estimates of epidemiological characteristics, 1 February 2024
Updated 14 March 2024
Applies to England and Scotland
© Crown copyright 2024
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This publication describes the prevalence of the SARS-CoV-2 virus in England and Scotland. SARS-CoV-2 is a coronavirus that causes COVID-19.
Test positivity describes the proportion of lateral flow device (LFD) tests taken by participants in the study that are positive for SARS-CoV-2. However, because tests are imperfect, some tests will return false negative results when an infected individual is tested. A very small number of positive tests may also be false positives when an uninfected individual is tested.
Prevalence is an estimate of the proportion of the population who are infected. It is calculated by adjusting positivity to account for imperfect test performance. This correction is important in this study as LFD tests are used. LFD tests return more false negatives than the polymerase chain reaction (PCR) tests that were used in the previous Office for National Statistics (ONS) Coronavirus (COVID-19) Infection Survey (CIS). Estimates of prevalence are useful for individuals who want to understand their risk of exposure to SARS-CoV-2.
To ensure estimates are representative of the wider population, the prevalence estimates from this cohort are adjusted through reweighting. The reweighting approach used by this study aims to provide an estimate of prevalence that is representative of the whole population in terms of age, geography, and sex. The study only includes participants aged over 2 years and therefore all the analyses conducted, and population projections used in this report do not include individuals aged under 3 years.
In future publications we will include estimates for incidence (the number of new infections each day) and the infection hospitalisation risk (the probability that someone infected with SARS-CoV-2 will require hospital admission). Information on unweighted positivity is available from the ONS Winter CIS publication.
Main points
Prevalence of SARS-CoV-2 in England and Scotland was broadly stable in the 2 weeks leading up to 24 January 2024.
In England and Scotland, the estimated prevalence of SARS-CoV-2 on 24 January 2024 was 2.0% (95% Credible Interval (CrI): 1.5%, 2.5%) which is equivalent to around
1,177,000 individuals (95% CrI: 922,000 to 1,480,000) being infected with SARS-CoV-2 in England and Scotland combined. This corresponds to around 1 in 50 (95% CrI: 1 in 67 to 1 in 40).
In England, the estimated prevalence of SARS-CoV-2 on 24 January 2024 was 2.0% (95% CrI: 1.6% to 2.5%), which is equivalent to around 1,091,000 individuals (95% CrI: 854,000 to 1,378,000) being infected with SARS-CoV-2 in England. This corresponds to 1 in 50 (95% CrI: 1 in 62 to 1 in 40).
In Scotland, the estimated prevalence of SARS-CoV-2 on 24 January 2024 was
1.6% (95% CrI: 1.2% to 2.2%), which is equivalent to around 85,000 individuals (95% CrI: 62,000 to 115,000) being infected with SARS-CoV-2 in Scotland. This corresponds to around 1 in 62 (95% CrI: 1 in 83 to 1 in 45).
Prevalence was broadly stable across all age groups in the past 2 weeks.
Figure 1. Estimates of prevalence over time in combined England and Scotland between 14 November 2023 and 24 January 2024
Estimated prevalence in England and Scotland
On 24 January 2024, the estimated prevalence of SARS-CoV-2 in England and Scotland was 2.0% (95% CrI: 1.5% to 2.5%) (Figure 1 and Table 1). Prevalence was broadly stable over the past 2 weeks from 2.2% (95% CrI: 1.8% to 2.6%) on the 10 January 2024.
On 24 January 2024, prevalence of SARS-CoV-2 was estimated to be 2.0% (95% CrI: 1.6% to 2.5%) in England and 1.6% (95% CrI: 1.2% to 2.2%) in Scotland. The estimated prevalence in England and Scotland was broadly stable over the past 2 weeks, from 2.2% (95% CrI: 1.8% to 2.6%) and 1.8% (95% CrI: 1.4% to 2.3%) on 10 January 2024, respectively (Figure 2a and 2b).
Figure 2a. Estimates of prevalence over time in England between 14 November 2023 and 24 January 2024
Figure 2b. Estimates of prevalence over time in Scotland between 14 November 2023 and 24 January 2024
Table 1. The current estimates of prevalence in England and Scotland, and the separate estimates for England and Scotland
| Date | Location | Prevalence |
|---|---|---|
| 24/01/2024 | England and Scotland | 2.0% (95% CrI: 1.5%, 2.5%) |
| 24/01/2024 | England | 2.0% (95% CrI: 1.6%, 2.5%) |
| 24/01/2024 | Scotland | 1.6% (95% CrI: 1.2%, 2.2%) |
Estimated prevalence in England and Scotland by age
The estimated prevalence for the age groups in England and Scotland from the 14 November to 24 January 2024 is referred to in Figure 3 and Table 2. Prevalence was broadly stable across all age groups over the past 2 weeks. As the sample sizes used to estimate prevalence for each age group are smaller than the overall study’s sample size, there is higher uncertainty compared to national estimates, which is reflected in wider credible intervals.
Figure 3. Estimates of prevalence over time by age group in combined England and Scotland between 14 November 2023 and 24 January 2024
Table 2. The combined England and Scotland current estimates for prevalence by age group
| Date | Age group | Prevalence |
|---|---|---|
| 24/01/2024 | 3 to 17 years | 1.4% (95% CrI: 1.0%, 2.0%) |
| 24/01/2024 | 18 to 34 years | 2.5% (95% CrI: 1.8%, 3.3%) |
| 24/01/2024 | 35 to 44 years | 2.8% (95% CrI: 2.1%, 3.6%) |
| 24/01/2024 | 45 to 54 years | 2.1% (95% CrI: 1.6%, 2.7%) |
| 24/01/2024 | 55 to 64 years | 1.8% (95% CrI: 1.4%, 2.3%) |
| 24/01/2024 | 65 to 74 years | 1.3% (95% CrI: 1.0%, 1.6%) |
| 24/01/2024 | 75 years and over | 1.3% (95% CrI: 1.0%, 1.7%) |
Estimated prevalence in the regions of England
The estimated prevalence for the regions of England from the 14 November to 24 January 2024 is referred to in Figure 4 and Table 3. Prevalence was broadly stable across all regions over the past 2 weeks. There is considerable uncertainty in the estimated prevalence for the regions of England. As the sample sizes used to estimate prevalence for each region of England are smaller than the overall study’s sample size, there is higher uncertainty compared to national estimates, which is reflected in wider credible intervals.
Figure 4. Estimates of prevalence over time in regions of England between 14 November 2023 and 24 January 2024
Table 3. Current estimates of prevalence in the regions of England
| Date | Region | Prevalence |
|---|---|---|
| 24/01/2024 | North East | 1.8% (95% CrI: 1.2%, 2.6%) |
| 24/01/2024 | North West | 1.8% (95% CrI: 1.3%, 2.4%) |
| 24/01/2024 | Yorkshire and The Humber | 1.7% (95% CrI: 1.3%, 2.3%) |
| 24/01/2024 | East Midlands | 2.0% (95% CrI: 1.5%, 2.8%) |
| 24/01/2024 | West Midlands | 1.9% (95% CrI: 1.4%, 2.6%) |
| 24/01/2024 | East of England | 2.0% (95% CrI: 1.5%, 2.7%) |
| 24/01/2024 | London | 2.0% (95% CrI: 1.5%, 2.7%) |
| 24/01/2024 | South East | 2.1% (95% CrI: 1.6%, 2.8%) |
| 24/01/2024 | South West | 2.3% (95% CrI: 1.7%, 3.0%) |
Methodology
Demographics are over or underrepresented in the survey, and it is important to account for this to produce nationally representative estimates of SARS-CoV-2 prevalence.
A Multilevel Regression and Post-Stratification (MRP) approach is used to estimate the prevalence for different subgroups. MRP helps reduce the uncertainty in prevalence estimates for subgroups that might be under-represented or under-sampled in the original survey, offering a more representative and accurate estimation of prevalence for the entire population. This is achieved by incorporating external information about the size of different subgroups. The MRP model used estimates a national prevalence trend over time, and adjustments are then made to this national trend for each combination of age group, sex, and region. The difference between prevalence in different subgroup may vary over time, and the model is able to make different adjustments at different points in time. All the analyses conducted in this report do not include individuals aged under 3 years.
An important part of understanding prevalence is adjusting for imperfect test sensitivity, which causes false negatives to be observed in the data. False negatives are when an individual is truly positive, but their test provides a negative result. We developed a model that estimates how many false negatives we expect to observe in the data, allowing us to adjust for the presence of false negatives when calculating prevalence. The model also adjusts for test specificity, though with high test specificity it has a minimal influence on the estimated prevalence.
In the survey, once a participant tests positive for SARS-CoV-2, they are asked to take repeat tests every other day until they return 2 negative tests. This repeat testing data is used to estimate the false negative rates of LFDs, over time, for the cohort. This allows us to further model the test sensitivity as it evolves over the epidemic phases. As the study gathers further data the diagnostic performance of the LFD test will be updated.
Individuals appear to be more likely to test earlier or before the testing window if they are symptomatic. As a result, tests taken earlier in the window are more likely to be positive than tests taken later in the testing window. Our model includes an adjustment for this effect, based upon which day of their testing window they took their test. Testing behaviour patterns changed over the winter bank holiday period which has been accounted for in the model.
Data sources
Based on responses from the Winter Coronavirus (COVID-19) Infection Study (Winter CIS), commissioned and funded by UK Health Security Agency (UKHSA), to deliver real-time information to help assess the effects of COVID-19 on the lives of individuals and the community, and help understand the potential winter pressures on our health services. The study has been launched jointly by ONS and UKHSA, with data collected via online questionnaire completion and self-reported lateral flow device (LFD) results from previous participants of the COVID-19 Infection Survey (CIS). The ONS 2023 to 2024 population projections will be published alongside the report on positivity.
Authors
Alex Glaser – UKHSA
Alexander Phillips – UKHSA, University of Liverpool
Andre Charlett – UKHSA
Christopher Overton – UKHSA, University of Liverpool
Jonathon Mellor – UKHSA
Julie Day – UKHSA
Martyn Fyles – UKHSA
Owen Jones – UKHSA
Robert Paton – UKHSA
Steven Riley – UKHSA, Imperial College London
Thomas Ward – UKHSA
Glossary
Prevalence
The estimated proportion of individuals who are infected with the SARS-CoV-2 virus at a given point in time.
Incidence
The estimated number of new infections occurring on a given day.
Infection hospitalisation risk (IHR)
Measures the risk of hospital admission given that you have been infected with the SARS-CoV-2 virus.
Infection fatality risk (IFR)
Measures the risk of death given that you have been infected with the SARS-CoV-2 virus.
Vaccine effectiveness
How effectively vaccinations protect people from health outcomes such as infection, symptomatic disease, hospitalisation, and mortality.