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Cited by 957SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research StudiesCOVID-19 epidemiological studies

Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7

Open access
CMMID COVID-19 Working Group, Davies, Nicholas G., Jarvis, Christopher I., Edmunds, W. John, Jewell, Nicholas P., Diaz-Ordaz, Karla, Keogh, Ruth H.·2021·Nature
DOI 10.1038/s41586-021-03426-1PMC PMC9170116

Published version of a preprint

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Abstract

SARS-CoV-2 lineage B.1.1.7, a variant that was first detected in the UK in September 2020 1, has spread to multiple countries worldwide. Several studies have established that B.1.1.7 is more transmissible than pre-existing variants, but have not identified whether it leads to any change in disease severity 2. Here we analyse a dataset that links 2,245,263 positive SARS-CoV-2 community tests and 17,452 deaths associated with COVID-19 in England from 1 November 2020 to 14 February 2021. For 1,146,534 (51%) of these tests, the presence or absence of B.1.1.7 can be identified because mutations in this lineage prevent PCR amplification of the spike (S) gene target (known as S gene target failure (SGTF)1). On the basis of 4,945 deaths with known SGTF status, we estimate that the hazard of death associated with SGTF is 55% (95% confidence interval, 39-72%) higher than in cases without SGTF after adjustment for age, sex, ethnicity, deprivation, residence in a care home, the local authority of residence and test date. This corresponds to the absolute risk of death for a 55-69-year-old man increasing from 0.6% to 0.9% (95% confidence interval, 0.8-1.0%) within 28 days of a positive test in the community. Correcting for misclassification of SGTF and missingness in SGTF status, we estimate that the hazard of death associated with B.1.1.7 is 61% (42-82%) higher than with pre-existing variants. Our analysis suggests that B.1.1.7 is not only more transmissible than pre-existing SARS-CoV-2 variants, but may also cause more severe illness.

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Crossref · 10.1038/s41586-021-03426-1

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 9 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Infections with B.1.1.7 were associated with higher viral concentrations in nasopharyngeal swabs, as measured by Ct values using PCR testing.

    “Infections with the B.1.1.7 variant are associated with higher viral concentrations in nasopharyngeal swabs, as measured by C t values using PCR testing (Extended Data Fig. 6).”
    Quote in the paperNot a substantial claim
  • Findingown data

    Comparison with ONS random community sampling suggested that S-gene dropout samples were not overrepresented in the testing data relative to their community prevalence.

    “This comparison suggests that S-gene dropout samples are not overrepresented in testing data relative to the prevalence of S-gene dropout in the community”
    Quote in the paperSubstantial claim
  • Findingown data

    SGTF prevalence rose steeply over the study period, from 5.8% in 1-21 November 2020 to 94.3% in 24 January-14 February 2021.

    “The prevalence of SGTF increased steeply over time (Fig. 1a), from 5.8% during 1-21 November 2020 to 94.3% during 24 January-14 February 2021.”
    Quote in the paperSubstantial claim
  • Findingown data

    Based on 4,945 deaths with known SGTF status, the adjusted hazard of death within 28 days of a positive community test was 55% higher for SGTF than non-SGTF cases (95% CI 39-72%).

    “On the basis of 4,945 deaths with known SGTF status, we estimate that the hazard of death associated with SGTF is 55% (95% confidence interval, 39-72%) higher than in cases without SGTF after adjustment for age, sex, ethnicity, deprivation, residence in a care home, the local authority of residence and test date.”
    • Also stated in: § Cox regression analyses · hedged
      “For the analysis of the complete cases, the estimated hazard ratio for SGTF was 1.55 (95% confidence interval, 1.39-1.72),indicating that the hazard of death in the 28 days after a positive test is 55% (39-72%) higher for SGTF than for non-SGTF cases.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: In the complete-case analysis, death is independent of whether SGTF status is observed or missing, given the individual's other characteristics included in the survival model.
  • Findingown data

    After correcting for SGTF misclassification and missingness, the estimated hazard of death associated with B.1.1.7 was 61% higher than with pre-existing variants (95% CI 42-82%).

    “Correcting for misclassification of SGTF and missingness in SGTF status, we estimate that the hazard of death associated with B.1.1.7 is 61% (42-82%) higher than with pre-existing variants.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: In the IPW analysis, whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights.
  • May combine two claims. 25
  • Classified as probably not a substantial claim. 26

  • May combine two claims.

    Findingown data

    There was strong evidence that the hazard ratio for SGTF changed over time (likelihood ratio test P = 0.009), with estimated hazard ratios of 1.14 (0.92-1.40) on day 1, 1.58 (1.42-1.75) on day 14 and 2.24 (1.75-2.87) on day 28 after a positive test.

    “There was strong evidence of non-proportionality of hazards (likelihood ratio test P χ ( =11) = 0.009 1 2 ) (Fig. 2a and Extended Data Fig. 3), with the estimated time-varying hazard ratio increasing over time: 1.14 (0.92-1.40) on day 1 after the positive test, 1.58 (1.42-1.75) on day 14 and 2.24 (1.75-2.87) on day 28.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In the SGTF group, 10.4% of tests were inconclusive.

    “A small proportion (10.4%) of SGTF tests are inconclusive.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In the subset with known SGTF status, 58.8% had SGTF.

    “Just over half of those tested (1,146,534; 51.1%) had a conclusive SGTF reading and, of these, 58.8% had SGTF.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Findingown data

    The dataset contained 17,913 individuals recorded as age 0 and 10,132 recorded as age 1.

    “there were 17,913 age-0 individuals compared to 10,132 age-1 individuals in the dataset”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    SGTF prevalence was similar in male and female individuals but lower in older age groups, at 59.0% in 1-34-year-olds versus 55.4% in those aged 85 years or older.

    “For those samples for which SGTF status was measured, SGTF prevalence was similar in male and female individuals, but lower in the older age groups: 59.0% in 1-34-year-old individuals compared with 55.4% in those aged 85 years and older.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In the IPW analysis, the hazard ratio increased with time since positive test but less markedly than in the complete-case analysis, and the increase did not significantly differ from zero (Wald test P = 0.23).

    “Similar to the analysis of the complete cases, the IPW analysis recovered an increasing hazard ratio with time since a positive test, but the increase was less marked (Fig. 2b) and did not significantly differ from zero (Wald test P χ ( =1.4) = 0.23 1 2 ).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the IPW analysis, whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights.

  • May combine two claims.

    Findingown data

    The IPW analysis gave results similar to the complete-case analysis, with a hazard ratio for SGTF of 1.58 (95% CI 1.40-1.78).

    “The IPW analysis gave similar results to the analysis of the complete cases, yielding a hazard ratio of 1.58 (1.40-1.78).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the IPW analysis, whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights.

  • Classified as probably not a substantial claim. May combine two claims.

    Findingown data

    The main analysis dataset contained 2,245,263 individuals, of whom 1,098,729 (48.9%) had missing or inconclusive SGTF status.

    “The full dataset used for the main analysis comprises 2,245,263 individuals, with SGTF status missing or inconclusive for 1,098,729 (48.9%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    During the study period, 17,642 of 57,750 COVID-19 deaths in England (30.5%) were linked to a positive Pillar 2 test, and 4,945 of those linked deaths had non-missing SGTF status.

    “Of the 57,750 deaths associated with COVID-19 in England during the study period, 17,642 deaths (30.5%) can be linked to a positive Pillar 2 test; among these, 4,945 have non-missing SGTF status.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Missingness in SGTF status varied substantially by NHS England region, from 21.2% in the North West to 71.1% in the South West, largely explained by proximity to a Lighthouse laboratory able to produce an SGTF reading.

    “Missingness in SGTF status also differed substantially between regions of NHS England, ranging from 21.2% in the North West to 71.1% in the South West, which is largely explained by proximity to a Lighthouse laboratory that is capable of producing an SGTF reading (Extended Data Fig. 1).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In the misclassification analysis, the hazard ratio associated with pVOC was 1.58 (95% CI 1.42-1.76) for complete cases and 1.61 (95% CI 1.42-1.82) for IPW.

    “Again restricting the analysis to specimens from 1 November 2020 onward, we find a hazard ratio associated with p VOC of 1.58 (1.42-1.76)for the analysis of the complete cases and 1.61 (1.42-1.82)for the IPW analysis (Fig. 2c, d).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: In the IPW analysis, whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    SGTF prevalence was lower in care or nursing home residents (54.3%) than in residential accommodation (58.8%).

    “In keeping with these age patterns, SGTF prevalence was lower in individuals living in a care or nursing home (54.3%) than those in residential accommodation (58.8%).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    In total, 19,615 people in the study sample died (0.87%), and 17,452 of these deaths (89.0%) occurred within 28 days of the first positive test.

    “In total, 19,615 people in the study sample are known to have died (0.87% of 2,245,263).Crude death rates were substantially higher in the elderly and in those living in a care or nursing home (Supplementary Table 1).The standard definition of a death associated with COVID-19 in England is any death that occurred within 28 days of the first positive SARS-CoV-2 test of an individual; 17,452 of the”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Schoenfeld residual tests gave P = 0.001 for SGTF, P = 0.039 for age, P = 0.101 for sex, P = 0.937 for IMD decile, P = 0.969 for ethnicity, P = 0.064 for residence type, and P = 0.027 globally.

    “P = 0.001 for SGTF (a); P = 0.039 for age (b); P = 0.101 for sex (c); P = 0.937 for IMD decile (d); P = 0.969 for ethnicity (e-g); P = 0.064 for residence type (h-i); and P = 0.027 globally.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    SGTF prevalence was lowest in the most-deprived IMD quintile (53.9%).

    “SGTF prevalence was the lowest in the most-deprived quintile of the index of multiple deprivation 3 (IMD) (53.9%).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [3] McLennan, D. et al. English Indices of Deprivation 2019. https://www.gov.uk/government/publications/english-indices-of-deprivation-2019-technical-report (Ministry of Housing, Communities & Local Government 2019).

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    The study included 1,098,729 Pillar 2 tests with non-missing SGTF status, which was 51.1% of Pillar 2 tests and 40.2% of combined Pillar 1 and Pillar 2 tests; SGTF status could be assessed for only 8.6% of COVID-19 deaths.

    “So, although our study includes 1,098,729 Pillar 2 tests with non-missing SGTF status, which represents 51.1% of the 2,245,263 Pillar 2 tests over this period and 40.2% of the 2,736,806 combined Pillar 1 (hospital) and Pillar 2 (community) SARS-CoV-2 tests over this period, we can only assess SGTF status for 8.6% (4,945/57,750) of the individuals who died from COVID-19 over the study period.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    SGTF prevalence by self-identified ethnicity was 58.0% in white, 57.6% in Asian, 69.6% in Black, and 64.8% in other, mixed or unknown ethnicity groups.

    “SGTF prevalence by self-identified ethnicity was 58.0% in the white group, 57.6% in the Asian group, 69.6% in the Black group and 64.8% in the other, mixed or unknown ethnicity group.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The analysis tested whether the SGTF-hazard association was modified by age, sex, IMD, ethnicity, or residence type, comparing models with and without interactions using likelihood ratio tests.

    “We assessed whether the association between SGTF and the hazard was modified by age, sex, IMD, ethnicity and residence type.Models with and without interactions were compared using likelihood ratio tests for the analyses of the complete cases.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisereasoning

    Area of residence and specimen date were expected to be strong confounders of the SGTF-mortality association.

    “Area of residence and specimen date were expected to be potentially strong confounding factors.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The main analysis was restricted to tests collected after 1 November 2020 so that SGTF results not caused by lineage B.1.1.7 would not be over-represented.

    “For our main analysis, we included only tests from after 1 November 2020 to avoid including an excess of tests with SGTF not resulting from infection by lineage B.1.1.7.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    No clear difference was found in SGTF frequency between community tests and a random sample of SARS-CoV-2 infections, suggesting that variant-associated changes in test-seeking propensity do not explain the findings.

    “However, we find no clear difference in SGTF frequency among community tests relative to a random sample of SARS-CoV-2 infections in the population (Extended Data Fig. 7), which suggests that variant-associated changes in test-seeking propensity do not explain our findings.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The analysis could not account for vaccination status.

    “Unfortunately, we were unable to account for vaccination status in this analysis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    In the IPW analyses, standard errors accounted for the weights but not for the fact that the weights were estimated, which makes them conservative.

    “For IPW analyses, the standard errors accounted for the weights, although the fact that the weights were estimated was not accounted for; this results in conservative standard errors.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The low proportion of deaths with assessable SGTF status is explained by higher mortality among people first testing positive in hospital and by missing SGTF data.

    “This is explained by differing mortality rates among individuals who first test positive in a hospital compared to those who are tested in the community, as the former group are much more likely to have a severe illness, as well as by missingness in the SGTF data.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisereasoning

    Misclassification of an exposure can bias its estimated association with an outcome.

    “Misclassification of an exposure can result in bias in its estimated association with the outcome.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    The Cox model's baseline hazard was stratified by specimen date and lower-tier local authority, which controlled finely for those variables.

    “The baseline hazard in the Cox model was stratified by both specimen date and LTLA, therefore finely controlling for these variables.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The findings are consistent with earlier reports by the authors and other groups and with contemporaneous studies.

    “Our findings are consistent with earlier reports by ourselves and other groups 7 and with contemporaneous studies [8][9][10][11] assessing the risk of severe outcomes among individuals with B.1.1.7 infection.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [7] Scientific Advisory Group for Emergencies. NERVTAG: Update Note on B.1.1.7 Severity, 11 February 2021. https://www.gov.uk/government/publications/nervtag-update-note-on-b117-severity-11-february-2021 (2021).

      Not checked in the free run.

    • cites [8] Challen, R. et al. Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study. BMJ 372, n579 (2021). source

      Not checked in the free run.

    • cites [9] Grint, D. J. et al. Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England. Euro Surveill. 26, 21002  (2021).

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    SARS-CoV-2 lineage B.1.1.7 is more transmissible than pre-existing variants.

    “Several studies have established that B.1.1.7 is more transmissible than pre-existing variants, but have not identified whether it leads to any change in disease severity 2 .”
    • Also stated in: § Discussion · plain
      “We previously found that B.1.1.7 is substantially more transmissible than pre-existing SARS-CoV-2 variants, but could not robustly identify any associated change in disease severity using population-level analysis of early data 2 .”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [2] Davies, N. G. et al. Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science https://doi.org/10.1126/science.abg3055 (2021). source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    The proportional hazards assumption was checked by adding covariate-by-time interactions separately for SGTF and each covariate, and by examining Schoenfeld residual plots.

    “The assumption of proportional hazards was assessed by including in the model an interaction between each covariate and time, which was performed separately for SGTF and for each other covariate.Schoenfeld residual plots were also obtained for each covariate (Extended Data Fig. 3).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Estimated absolute 28-day mortality risk increased substantially with SGTF in older age groups, but remained below 1% in most individuals younger than 70 years.

    “These estimates reflect a substantial increase in absolute risk among older age groups, but the risk of death associated with COVID-19 after a positive test in the community remains below 1% in most individuals who are younger than 70 years old.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The baseline risk of death among individuals tested in the community between August and October 2020 is illustrative of the case fatality ratio associated with pre-existing SARS-CoV-2 variants.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    This stratification created many strata matched on specimen date and lower-tier local authority; only strata containing both deaths and survivors contributed, making the analysis similar to a matched nested case-control design.

    “The stratification gives a large number of strata matched by specimen date and LTLA.Only those strata that contain individuals who died and individuals who survived contribute to the analysis.The analysis is therefore similar to the analysis that would be performed had we created a matched nested case-control sample.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    The study did not identify a mechanism for the increased mortality.

    “We do not identify any mechanism for the increased mortality here.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The missingness model's fit was checked with a Q-Q plot, and Hosmer-Lemeshow and Hinkley tests were used to select the model.

    “The fit of the missingness model was assessed using a Q-Q plot (Extended Data Fig. 4), and Hosmer-Lemeshow and Hinkley tests were used to choose the most appropriate model.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisereasoning

    Sex, age, residence type, ethnicity, and IMD were also identified as potential confounders.

    “The following variables were also identified as potential confounding factors: sex, age, residence type (residential, care or nursing home, or other or unknown), ethnicity (white, Asian, Black or other, mixed or unknown) and IMD.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Missing data were rare for sex, age, and IMD/regional covariates, and specimen dates were complete.

    “There was a small amount of missing data for sex (n = 14, <0.01%), age (n = 171, <0.01%), and IMD and regional covariates (n = 3,817, 0.16%).There were no missing specimen dates.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    B.1.1.7 may cause more severe illness as well as being more transmissible.

    “Our analysis suggests that B.1.1.7 is not only more transmissible than pre-existing SARS-CoV-2 variants, but may also cause more severe illness.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The administrative censoring date was set to 10 days before the most recent death linkable to SGTF status (14 February 2021) to reduce bias from late death reporting.

    “the administrative censoring date, which we chose as the date of the most recent death linkable to SGTF status minus 10 days (that is, 14 February 2021) to minimize any potential bias due to late reporting of deaths.”
    Quote in the paperSubstantial claim
37 of 37

  • The authors state this as an assumption.

    In the complete-case analysis, death is independent of whether SGTF status is observed or missing, given the individual's other characteristics included in the survival model.

    “The analysis of the complete cases assumes that whether an individual dies is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the survival model”

  • The authors state this as an assumption.

    In the IPW analysis, whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights.

    “whereas the IPW analysis assumes that whether an individual has SGTF is independent of whether their SGTF status is observed or missing, given the individual's other characteristics included in the model used to derive weights for IPW 5 .”

  • The authors state this as an assumption.

    The baseline risk of death among individuals tested in the community between August and October 2020 is illustrative of the case fatality ratio associated with pre-existing SARS-CoV-2 variants.

    “applying hazard ratios for SGTF to the baseline risk of death among individuals tested in the community between August and October 2020 (assumed to be illustrative of the case fatality ratio associated with pre-existing variants of SARS-CoV-2)”

  • The authors state this as an assumption.

    The complete-case analysis assumes that missing SGTF status is independent of the outcome given the variables in the models, a type of missing-not-at-random assumption that may depend on the underlying SGTF value.

    “This analysis of complete cases assumes that for each analysis, the missing data-in this case missing SGTF status-are independent of the outcome of interest given the variables included in the models.This is a specific type of 'missing not at random' assumption, as in particular it is allowed to depend on the underlying value of SGTF.”

  • The authors state this as an assumption.

    The IPW analysis assumes that SGTF status is missing at random.

    “We also performed an analysis of the complete cases using inverse probability weights 5 (IPW) to address the missing data on SGTF, under a 'missing at random' assumption.”

  • The authors state this as an assumption.

    The analysis assumes that censoring is uninformative.

    “The analysis assumes that censoring is uninformative, which is plausible as all censoring is administrative.”

  • The authors state this as an assumption.

    A negative SGTF test is assumed to indicate absence of B.1.1.7 infection.

    “A negative test of SGTF is assumed to be indicative of an absence of infection with B.1.1.7.”

  • The authors state this as an assumption.

    Poisson confidence intervals for mortality rates assume constant rates.

    “Exact Poisson confidence intervals are used for mortality rates, assuming constant rates.”

  • The authors state this as an assumption.

    The Cox model assumes proportional hazards for SGTF and the covariates.

    “We began by assuming the proportionality of the hazards for SGTF and the covariates included in the model.”
9 of 9

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Non-missing SGTF count does not match its stated percentage

    Minor

    The stated count is 48.94% of the total, not 51.1%. Elsewhere, the paper identifies 1,098,729 as the number with missing SGTF status.

    Reported 51.1 · recomputed 48.935425

  • Sequencing download predates detection of B.1.1.7

    Minor

    The stated download date is in January 2020, eight months before the paper says B.1.1.7 was first detected. That chronology is inconsistent with using the downloaded sequences to estimate the variant's prevalence.

2 of 2

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Authors
CMMID COVID-19 Working Group, Davies, N. G., Jarvis, C. I., Edmunds, W. J., Jewell, N. P., Diaz-Ordaz, K., & Keogh, R. H.
Affiliations
London School of Hygiene & Tropical Medicine (GB)
Corresponding author
Davies, Nicholas G.
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2021-03-15
Volume
593
Issue
7858
Pages
270-274
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-021-03426-1
PMC
PMC9170116
OpenAlex
W3137149656
Cited by
921
References
12
Citations by year
2026: 12 · 2025: 37 · 2024: 74 · 2023: 130 · 2022: 303 · 2021: 362 · 2020: 2
FWCI
68.81
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
Funders
  • Wellcome Trust (208812/Z/17/Z, 206471/Z/17/Z, 218554/Z/19/Z)
  • UK Research and Innovation (ES/P010873/1, MR/S017968/1, ES/P010873)
  • National Institute for Health Research Health Protection Research Unit (NIHR200908, NIHR200929)
  • National Institute for Health and Care Research ((NIHR200929), (NIHR200908), NIHR-INF-1846)
  • Research Councils UK (ES/P010873/1)
  • European Commission (101003688)
  • Public Health England
  • National Institutes of Health
  • Medical Research Council (NIHR200908, MR/S017968/1, MC_PC_19065)
  • Economic and Social Research Council (ES/P010873/1)
  • National Institute of Allergy and Infectious Diseases (R01AI148127)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
Keywords
COVID-19 mortality, S-gene target failure, spike gene mutations, disease severity, SARS-CoV-2 variants, England
MeSH terms
COVID-19, SARS-CoV-2, Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, England, Ethnicity, Female, Homes for the Aged, Humans, Infant, Male, Middle Aged, Phylogeny, Time Factors, Proportional Hazards Models, Survival Analysis, Risk Assessment, Evolution, Molecular, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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