SARS-CoV-2 genome sequence prevalence and growth rate update: 6 December 2023
Updated 27 March 2024
Applies to England
© Crown copyright 2024
This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk.
Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.
This publication is available at https://www.gov.uk/government/publications/sars-cov-2-genome-sequence-prevalence-and-growth-rate/sars-cov-2-genome-sequence-prevalence-and-growth-rate-update-6-december-2023
Variant prevalence
Testing policy and sequencing should be considered when interpreting variant data. Information about surveillance systems for England are reported by the UK Health Security Agency (UKHSA) in the national flu and COVID-19 surveillance reports.
The prevalence of lineages amongst UK sequences by Phylogenetic Assignment of Named Global Outbreak Lineages (Pangolin) designation is presented in Figure 1. Lineages are shown if there are more than or equal to 5,000 sequences since 12 June 2023 or if they represent more than or equal to 1% of sequences within a single week over the last 6 weeks. Lineages that do not meet these criteria are combined with their parent lineage (for example, BA.2.4 is combined with BA.2).
The lineages have been assigned using the accurate Ultrafast Sample placement on Existing tRee (UShER) mode and version 1.23.1 of the Pangolin data.
Figure 2 shows the relationship between lineages shown in Figure 1. The figure details the hierarchical relationship of the lineages from left to right, starting with B.1.1.529 through 15 sublineage levels, including aliases and the parent lineages for any recombinants included in the prevalence figures (for example, BJ.1 and BM.1.1.1 are the parent lineages for the XBB recombinant). Lineages that have been combined with a lineage ancestral to B.1.1.529 in Figure 1 are not included in Figure 2. The percentage of each lineage in the most recent week of data in Figure 1 is shown next to the relevant lineage labels in Figure 2. Where a sublineage has a percentage in Figure 2, it is excluded from the percentage given for any parent lineages. Any lineages that are not present in the most recent week of genomic data will not have a percentage in Figure 2. The colours in Figure 2 correspond to the lineage colours in Figure 1.
Figure 1. Prevalence of Pangolin lineages in the UK sequence data with a specimen date from week beginning 12 June 2023 to week beginning 13 November 2023, as of 30 November 2023
The total number of valid sequence results per week is shown by the black line. The ‘Other’ category in this plot contains all lineages that do not meet the relevant criteria after combining smaller sub-lineages. ‘Unassigned’ are sequences that could not be assigned a lineage by Pangolin. Lineages present in at least 2% of sequences in the most recent week are labelled to the right of the plot.
Figure 2. Sankey diagram showing the relationship between Pangolin lineages observed in UK sequence data since 12 June 2023. Data shown as of 30 November 2023
Proportions are given for lineages that are observed in sequences with a specimen date between 13 November 2023 and 19 November 2023. Lineage colours match those in Figure 1.
Variant modelling
Two models are currently used to estimate the growth advantage of emerging lineages: a logistic regression generalised linear model (GLM) and a generalised additive model (GAM). Models are fit to a geographically stratified sample of Pillar 1 cases to ensure that relative growth rates are estimated in relation to a local set of co-circulating lineages. Tests associated with travel are excluded. A full description of methods can be found in the variant technical briefing series. In recent months there are fewer tests to model than earlier in the year (see Figure 1). This is due to reduced sampling effort and lower prevalence. Moreover, the proliferation of lineages to monitor means that sample sizes for specific lineages can be small. Uncertainty in our modelled relative growth rates is therefore increased, which is reflected in larger confidence intervals on the estimates.
We aim to select lineages and/or groups of lineages that are both specific enough to pick up on emerging signals but broad enough to maximise statistical power. Any lineage that has made up more than 1.5% of the total samples and with at least 50 sequenced cases within 6 weeks of the most recent specimen date is modelled separately. Lineages that do not meet these criteria will be added to a group with their closest parent lineage but will not be aggregated further than one. If the condition cannot be met for a particular lineage (for example, it does not have a close parent lineage at high enough prevalence) it will not be modelled. Lineages with a different high-level parent will never be aggregated together (for example, we will not aggregate BA.2 and BA.5 to B.1.1.529). Unassigned lineages are excluded from this analysis. Note that these aggregations will often be broader than in the prevalence plot presented in Figure 1. The relative growth rate of broad lineage classes (for example, parent lineages that include many distant child lineages) will be less informative than explicit modelling of specific sublineages. This is why we set a limit of one level when aggregating child lineages into parents. Methods of lineage collapsing for the growth rate analysis are therefore still being refined.
Growth rates were based on sequences sampled through Pillar 1 testing (primarily positive tests conducted in hospital) in England (Table 1). The sampling range for both the logistic regression GLM and GAM is from 6 July 2023 to 21 November 2023. The model fit for any lineage with a positive growth rate advantage (with 95% confidence intervals (CIs) that do not cross zero) are shown in Figure 3. The lineages that were estimated to have a positive growth rate advantage with reasonable uncertainty (CIs not below zero in the GAM) are JN.1 (84.23%, GAM), BA.2.86.1 (23.35%, GAM), and HK.6 (16.41%).
Table 1. Growth rate (GR) of English sequence lineages as of 21 November 2023†
| Lineage* | Lineage group composition** | Pillar 1 sample size*** | Weekly growth rate advantage (GAM) | Estimated prevalence¥ (GAM) | Weekly growth rate advantage (GLM) |
|---|---|---|---|---|---|
| JN.1 (BA.2.86.1.1) | JN.1 (100%) | 96 | 84.23% (95% CI: 63.99 to 104.48) | 7.53% (95% CI: 5.98 to 9.45) | 66.33% (95% CI: 36.95 to 95.71) |
| BA.2.86.1 | BA.2.86.1 (68.97%); JN.3 (17.66%); JN.2 (13.37%) | 419 | 23.35% (95% CI: 15.14 to 31.56) | 14.45% (95% CI: 12.4 to 16.78) | 7.18% (95% CI: -6.52 to 20.89) |
| JD.1.1 (XBB.1.5.102.1.1) | JD.1.1 (91.81%); JD.1.1.1 (4.74%); JD.1.1.2 (2.59%); JD.1.1.3 (0.86%) | 232 | 21.51% (95% CI: -3.53 to 46.55) | 6.57% (95% CI: 5.1 to 8.43) | 35.52% (95% CI: 15.8 to 55.24) |
| HK.6 (XBB.1.9.2.5.1.1.6) | HK.6 (100%) | 110 | 16.41% (95% CI: 0.75 to 32.06) | 2.95% (95% CI: 2.04 to 4.23) | 26.18% (95% CI: 24.49 to 27.87) |
| EG.5.1.6 (XBB.1.9.2.5.1.6) | EG.5.1.6 (100%) | 100 | 3.29% (95% CI: -2.14 to 8.72) | 2.3% (95% CI: 1.72 to 3.07) | 12.78% (95% CI: -14.76 to 40.33) |
| EG.5.1.1 (XBB.1.9.2.5.1.1) | EG.5.1.1 (86.57%); HK.11 (6.87%); HK.1 (3.88%); HK.2 (0.9%); HK.7 (0.6%)… | 335 | 2.3% (95% CI: -6.09 to 10.69) | 6.81% (95% CI: 5.42 to 8.52) | 0.32% (95% CI: -16.76 to 17.4) |
| GW.5.1.1 (XBB.1.19.1.5.1.1) | GW.5.1.1 (100%) | 89 | 1.73% (95% CI: -19.24 to 22.7) | 1.71% (95% CI: 1.07 to 2.74) | 34.01% (95% CI: -2.55 to 70.57) |
| HV.1 (XBB.1.9.2.5.1.6.1) | HV.1 (100%) | 195 | 1.19% (95% CI: -11.26 to 13.65) | 4.48% (95% CI: 3.4 to 5.9) | 9% (95% CI: -15.04 to 33.03) |
| JF.1 (XBB.1.16.6.1) | JF.1 (100%) | 116 | 0.85% (95% CI: -16.79 to 18.5) | 2.37% (95% CI: 1.59 to 3.54) | -1.15% (95% CI: -29.83 to 27.54) |
| GS.4.1 (XBB.2.3.11.4.1) | GS.4.1 (100%) | 99 | 0.84% (95% CI: -22.73 to 24.41) | 1.62% (95% CI: 1.01 to 2.58) | -17.62% (95% CI: -56.49 to 21.25) |
| EG.10.1 (XBB.1.9.2.10.1) | EG.10.1 (100%) | 80 | 0.11% (95% CI: -10.57 to 10.79) | 1.64% (95% CI: 1.09 to 2.46) | -30.12% (95% CI: -64.3 to 4.06) |
| FL.1.5.2 (XBB.1.9.1.1.5.2) | FL.1.5.2 (100%) | 82 | -2.28% (95% CI: -15.52 to 10.97) | 1.62% (95% CI: 1.05 to 2.49) | -10.6% (95% CI: -52.95 to 31.74) |
| XBB.1.16.15 | XBB.1.16.15 (87.18%); JM.2 (6.59%); JM.1 (6.23%) | 273 | -6.12% (95% CI: -16.99 to 4.75) | 4.27% (95% CI: 3.22 to 5.64) | -6.72% (95% CI: -28.35 to 14.92) |
| JG.3 (XBB.1.9.2.5.1.3.3) | JG.3 (100%) | 236 | -7.07% (95% CI: -27.13 to 12.98) | 7.4% (95% CI: 6.07 to 8.99) | 18.63% (95% CI: 0.54 to 36.72) |
| FL.1.5.1 (XBB.1.9.1.1.5.1) | FL.1.5.1 (97.3%); HN.1 (2.7%) | 148 | -10.61% (95% CI: -18.29 to -2.92) | 2.43% (95% CI: 1.78 to 3.31) | -24.26% (95% CI: -49.96 to 1.44) |
| XBB.1.16 | XBB.1.16 (50.25%); XBB.1.16.17 (18.91%); XBB.1.16.1 (6.47%); XBB.1.16.9 (4.98%); XBB.1.16.2 (4.48%)… | 201 | -11.61% (95% CI: -28.67 to 5.44) | 2.85% (95% CI: 1.99 to 4.06) | -7.29% (95% CI: -37.84 to 23.26) |
| XBB.1.16.6 | XBB.1.16.6 (100%) | 139 | -12.82% (95% CI: -27.13 to 1.5) | 2.03% (95% CI: 1.37 to 3.01) | 9% (95% CI: -27.48 to 45.49) |
| EG.5.1 (XBB.1.9.2.5.1) | EG.5.1 (53.95%); EG.5.1.4 (17.53%); EG.5.1.8 (15.12%); EG.5.1.5 (5.5%); EG.5.1.7 (4.47%)… | 291 | -14.75% (95% CI: -27.42 to -2.08) | 3.87% (95% CI: 2.86 to 5.23) | -40.06% (95% CI: -61.28 to -18.83) |
| EG.5.1.3 (XBB.1.9.2.5.1.3) | EG.5.1.3 (95.83%); JG.1 (3.12%); JG.2 (1.04%) | 192 | -22.62% (95% CI: -34.91 to -10.34) | 2.11% (95% CI: 1.44 to 3.07) | -29.06% (95% CI: -55.23 to -2.89) |
| HK.3 (XBB.1.9.2.5.1.1.3) | HK.3 (88.29%); HK.3.2 (8.56%); HK.3.1 (3.15%) | 222 | -25.81% (95% CI: -48.16 to -3.47) | 4.6% (95% CI: 3.3 to 6.39) | 15.76% (95% CI: -4.6 to 36.12) |
| GE.1 (XBB.2.3.10.1) | GE.1 (81.88%); GE.1.3 (8.72%); GE.1.1 (4.7%); GE.1.2 (4.7%) | 149 | -30.61% (95% CI: -44.8 to -16.41) | 1.26% (95% CI: 0.79 to 1.99) | -6.25% (95% CI: -45.25 to 32.76) |
| XBB.1.16.11 | XBB.1.16.11 (100%) | 201 | -71.55% (95% CI: -109.68 to -33.43) | 0.88% (95% CI: 0.45 to 1.69) | -47.76% (95% CI: -77.69 to -17.83) |
*Listed parent lineages include all sub-lineages, other than those explicitly modelled.
** The top 5 contributing lineages to the modelled group in the most recent 6 weeks (10 October 2023 to 21 November 2023). More than 5 sublineages are indicated by “…”
*** Sample size is for Pillar 1 samples in England in the most recent 6 weeks (10 October 2022 to 21 November 2023).
¥ Estimated prevalence for the 21 November 2023.
† Sampling range for both logistic regression and generalised additive models (GAM) is from 6 July 2023 to 21 November 2023.
CI = confidence intervals.
Figure 3. Modelled prevalence of lineage groups with a growth rate advantage over other circulating lineages
The black line shows the central estimate and blue shaded regions the 95% confidence intervals. Points show the national level proportions, with the size being indicative of the sample size for that particular lineage. The grey portion of the ribbon denotes that this period of time is likely to be backfilled with more sequenced cases, making proportions unreliable.
Variant designation
V-23DEC-01 (JN.1)
JN.1 was first raised as a signal in monitoring on 27 October 2023 as part of routine horizon scanning. This signal was raised due to the lineage containing L455S in Spike and increasing sequence prevalence in international data. The JN.1 lineage was subsequently designated V-23DEC-01 on 4 December 2023 due to increasing sequence prevalence within the UK and international data. Designating the lineage as a variant assigns it a fixed genomic case definition and facilitates monitoring through surveillance.
As of 4 December 2023, 302 UK sequences have been classified as JN.1, of which 223 were from England. As of 5 December 2023, 3,618 international sequences have been classified as JN.1 are present on GISAID, including UK sequences.
A full variant definition for V-23DEC-01 will be available on GitHub over the coming days.
Sources and acknowledgments
Data sources
Data used in this investigation is derived from the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) data set, the UKHSA genomic programme data set and the UKHSA Second Generation Surveillance System. International data has been gathered from the Global Initiative on Sharing All Influenza Data (GISAID).
Authors of this report
UKHSA COVID Vaccines and Epidemiology Team
UKHSA Genomics Public Health Analysis Team
UKHSA Infectious Disease Modelling Team
UKHSA TARZET Technical Secretariat