Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England - Science

A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading toward fixation.

A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases.

Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59–74%) in Denmark, Switzerland, and the United States.

In December 2020, evidence began to emerge that a novel SARS-CoV-2 variant, Variant of Concern 202012/01 (lineage B.1.1.7, henceforth VOC 202012/01), was rapidly outcompeting preexisting variants in southeast England (1).

As of 15 February 2021, VOC 202012/01 comprises roughly 95% of new SARS-CoV-2 infections in England, and has now been identified in at least 82 countries (2).

The proportion of COVID-19 cases attributable to VOC 202012/01 is rapidly increasing in all regions of England, following an initial expansion in the South East (Fig. 1A), and is spreading at comparable rates among males and females and across age and socioeconomic strata (Fig. 1B).

One potential explanation for the spread of VOC 202012/01 within England is a founder effect: that is, if certain regions had higher levels of transmission as a result of more social interactions, variants that were more prevalent within these regions could become more common overall.

(A) Proportion of S gene target failure among positive Pillar 2 community SARS-CoV-2 tests in upper-tier local authorities of England from 1 October 2020–10 January 2021, sorted by latitude.

Tier 4 local authorities are areas within the South East, East of England, and London regions that were placed under stringent restrictions from 20 December 2020 due to high prevalence of VOC 202012/01 and growing case rates.

VOC 202012/01 appears unmatched in its ability to outcompete other SARS-CoV-2 lineages in England.

Analyzing the COG-UK dataset (13), which comprises over 150,000 sequenced SARS-CoV-2 samples from across the UK, we found that the relative population growth rate of VOC 202012/01 in the first 31 days following its initial phylogenetic observation was higher than that of all 307 other lineages with enough observations to obtain reliable growth-rate estimates (Fig. 2A and fig. S1).

While the relative growth rate of VOC 202012/01 has declined slightly over time, it remains among the highest of any lineage as a function of lineage age (Fig. 2B), and the lineage continues to expand.

(A) Average relativized growth rate, i.e., a measure of variant fitness relative to other variants present during the 31 days following initial phylogenetic observation of a given variant, for all lineages in the COG-UK dataset, highlighting many lineages that have risen to prominence including B.1.177, the lineage with the highest relative abundance during the IPO of VOC 202012/01.

The shaded regions show conservative 95% rejection intervals; VOC 202012/01 is the first strain to exceed this threshold of faster relativized growth.

While many lineages exhibit above-average rates of growth, VOC 202012/01 has had the highest average relativized growth of any lineage in the history of COG-UK surveillance of SARS-COV-2.

(C) Muller plots of the relative abundances of the major SARS-CoV-2 variants in the UK, based on a multinomial spline fit to COG-UK sequence data (Table 1 and table S1, separate-slopes multinomial spline model).

(D) Mean reproduction number over 7-day periods in 149 upper-tier local authorities of England (colored by the NHS England region they are within) plotted against the weekly proportion of Pillar 2 community SARS-CoV-2 tests with S gene target failure shows the spread of VOC 202012/01, a corresponding increase in the reproduction number by local authority, and the eventual impact of targeted government restrictions from 20 December 2020.

A time-varying multinomial spline model estimates an increased growth rate for VOC 202012/01 of +0.104 days−1 (95% CI 0.100–0.108) relative to the previously dominant lineage, B.1.177 (Table 1, model 1a; Fig. 2C and figs. S2 and S3).

The growth advantage of VOC 202012/01 persists under more conservative model assumptions (Table 1, model 1b; fig. S4), is consistent across all regions of the UK (table S1, model 2a; fig. S5), and is similar when measured from S gene target failures among community COVID-19 tests instead of COG-UK sequence data (Table 1, model 2h; fig. S6).

Data from other countries yield similar results: we estimate that R for VOC 202012/01 relative to other lineages is 55% (45–66%) higher in Denmark, 74% (66–82%) higher in Switzerland, and 59% (56–63%) higher in the United States, with consistent rates of displacement across regions within each country (Table 1, models 3a–c; figs. S6 and S7).

This yielded an estimated increase in R for VOC 202012/01 of 43% (38–48%), increasing to a 57% (52–62%) increase if the spline was not included (Table 1, model 4a–b).

The various statistical models we fitted yield slightly different estimates for the growth rate of VOC 202012/01, reflecting different assumptions and model structures, but all identify a substantially increased growth rate (table S1).

To understand possible biological mechanisms for why VOC 202012/01 spreads more quickly than preexisting variants, we extended an age- and regionally-structured mathematical model of SARS-CoV-2 transmission (10, 15) to consider two co-circulating variants (fig. S8 and tables S2 and S3).

A shorter generation time could account for an increased growth rate without requiring a higher reproduction number, which would make control of VOC 202012/01 via social distancing measures relatively easier to achieve.

We fit each model to time series of COVID-19 deaths, hospital admissions, hospital and ICU bed occupancy, PCR prevalence, seroprevalence, and the proportion of community SARS-CoV-2 tests with S gene target failure across the three most heavily affected NHS England regions, over the period of 1 March–24 December 2020 (Fig. 3 and figs. S9 to S14).

(A) Relative frequency of VOC 202012/01 (black line and ribbon shows observed S gene target failure frequency with 95% binomial credible interval; purple line and ribbon shows mean and 95% credible interval from model fit).

Illustrative model fits for the South East NHS England region: (C) fitted two-strain increased transmissibility model with VOC 202012/01 included; (D) fitted two-strain increased transmissibility model with VOC 202012/01 removed; (E) fitted single-strain model without emergence of VOC 202012/01.

We fitted a combined model incorporating the five hypotheses above, but it was not able to identify a single consistent mechanism across NHS England regions, demonstrating that a wide range of parameter values are compatible with the observed growth rate of VOC 202012/01 (fig. S14).

The increased transmissibility model does not identify a clear increase or decrease in the severity of disease associated with VOC 202012/01, finding similar odds of hospitalisation (estimated odds ratio of hospitalisation given infection, 0.92 [95% credible intervals 0.77–1.10]), critical illness (OR 0.90 [0.58–1.40]), and death (OR 0.90 [0.68–1.20]), based upon fitting to the three most heavily affected NHS England regions (Fig. 3B).

However, the fitted model finds strong evidence of higher relative transmissibility, estimated at 65% (95% CrI: 39–93%) higher than preexisting variants for the three most heavily affected NHS England regions, or 82% (43–130%) when estimated across all seven NHS England regions (Table 1, model 5a).

Without the introduction of a new variant with a higher growth rate, the model is unable to reproduce observed dynamics (Fig. 3, D and E, and figs. S17 to S19), further highlighting that changing contact patterns do not explain the spread of VOC 202012/01.

Using the best-performing transmission model (increased transmissibility) fitted to all seven NHS England regions, we compared projected epidemic dynamics under different assumptions about control measures from mid-December 2020 to the end of June 2021.

As a sensitivity analysis, we also ran model projections with a seasonal component such that transmission is 20% higher in the winter than in the summer (22), but this did not qualitatively affect our results (fig. S24 and table S5).

Combining multiple behavioral and epidemiological data sources with statistical and dynamic modelling, we estimated that the novel SARS-CoV-2 variant VOC 202012/01 has a 43–90% (range of 95% credible intervals 38–130%) higher reproduction number than preexisting variants of SARS-CoV-2 in England, assuming no changes to the generation interval.

The UK government initiated a third national lockdown on 5 January 2021 in response to the rapid spread of VOC 202012/01, including school closures.

Increased transmission resulting from VOC 202012/01 will raise the herd immunity threshold, meaning the potential burden of SARS-CoV-2 is larger and higher vaccine coverage will be required to achieve herd immunity.

Although VOC 202012/01 was first identified in England, a rapidly spreading variant has also been detected in South Africa (25, 26), where there has been a marked increase in transmission in late 2020.

Our transmission model does not explicitly capture care home or hospital transmission of SARS-CoV-2, and is fit to each region of England separately rather than pooling information across regions and explicitly modelling transmission between regions.

We identify increased transmissibility as the most parsimonious mechanistic explanation for the higher growth rate of VOC 202012/01, but a longer infectious period also fits the data well (table S4) and is supported by longitudinal testing data (17).

In response to rising cases in southeast England and concerns over VOC 202012/01, the UK government announced on 19 December 2020 that a number of regions in southeast England would be placed into a new, more stringent ‘Tier 4’, corresponding to a Stay at Home alert level.

As cases continued to rise and VOC 202012/01 spread throughout England, on 5 January 2021 a third national lockdown was introduced in England, with schools and universities closed and individuals advised to stay at home, with measures to be kept in place until at least mid-February 2021.

To assess the spread of VOC 202012/01 in the United Kingdom, we used publicly-available sequencing-based data from the COG-UK Consortium (13) (5 February 2020–6 January 2021) and Pillar 2 SARS-CoV-2 testing data provided by Public Health England (1 October 2020–7 January 2021) for estimating the frequency of S gene target failure in England.

To assess the spread of VOC 202012/01 in Denmark, Switzerland and the USA, we used publicly available sequence data giving the incidence of VOC 202012/01 aggregated by week and region provided by the Danish Covid-19 Genome Consortium and the Statens Serum Institut (32) (15 October 2020–28 January 2021), sequence and RT-PCR 501Y.V1 rescreening data giving the incidence of VOC 202012/01 in different regions of Switzerland provided by Christian Althaus and Tanja Stadler and the Geneva University Hospitals, the Swiss Viollier Sequencing Consortium from ETH Zürich, the Risch laboratory, the University Hospital Basel, the Institute for Infectious Diseases, University of Bern and the Swiss National Covid-19 Science Task Force (33, 34) (2 November 2020–11 Feb 2021), and publicly available US nation-wide Helix SARS-CoV-2 Surveillance data, comprising both S-gene target failure data and randomly selected S-negative samples that were sequenced to infer the proportion of S-negative samples that were the VOC (35, 36) (6 September–11 February 2020).

To estimate the increase in growth rate of VOC 202012/01, we fitted a set of multinomial and binomial generalized linear mixed models (GLMMs), in which we estimated the rate by which the VOC displaces other resident SARS-CoV-2 variants across different regions in the UK, based on both the COG-UK sequence data as well as the S gene target failure data.

We extended a previously developed modelling framework structured by age (in 5-year age bands, with no births, deaths, or aging due to the short timescales modeled) and by geographical region (10, 15) to include two variants of SARS-CoV-2 (VOC 202012/01 and non-VOC 202012/01).

We fitted this model to multiple regionally-stratified data sources across the 7 NHS England regions as previously: deaths, hospital admissions, hospital bed occupancy, ICU bed occupancy, daily incidence of new infections, PCR prevalence of active infection, seroprevalence, and the daily frequency of VOC 202012/01 across each of the regions as measured by S gene target failure frequency corrected for false positives.

Our individual transmission model fits to separate NHS regions of England produce independent estimates of parameters such as relative transmissibility and differences in odds of hospitalisation or death resulting from infection with VOC 202012/01.

The apparent frequency of VOC 202012/01 could be inflated relative to reality if this variant leads to increased test-seeking behavior (e.g., if it leads to a higher rate of symptoms than preexisting variants).

However, this would not explain the growth in the relative frequency of VOC 202012/01 over time.

Mathematically, if variant 1 has growth rate r1 and variant 2 has growth rate r2, the relative frequency over time is a2 exp(r2t) / (a1 exp(r1t) + a2 exp(r2t)), where a1 and a2 are the frequency of variant 1 and 2, respectively, at time t = 0.

However, if variant 1 has probability x of being reported and variant 2 has probability y, and both have growth rate r, the relative frequency over time is a2 y exp(rt) / (a1 x exp(rt) + a2 y exp(rt)), which is constant.