The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index; none of the 9 sources its claims cite is checked for support yet.
Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7
Open accessPublished version of a preprint
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
26 Own result · 14 Own method · 11 Own interpretation · 6 Not checked yet · 5 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Sensitivity analyses
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 271
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Abstract
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
- Also stated in: § Cox regression analyses · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Abstract
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Stratifying by broad age groups and by sex, residence type, ethnicity, IMD, region and specimen date, death rates within 28 days of a positive SARS-CoV-2 test were higher among SGTF than non-SGTF cases in 98 of the 104 strata assessed (94%; Fig. 1d-i and Supplementary Table 2).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 271
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Approximately 49% of individuals in the study sample are missing data on SGTF status, due to their test not having been processed at one of the three laboratories using the Thermo Fisher TaqPath COVID-19 assay or the test being inconclusive.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although we caution that symptomatic screening status may lie on the causal pathway between SGTF status and death, we found that this adjustment had no effect on the relative hazard of SGTF (1.54 (1.39-1.71);analysis of complete cases).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Further investigations
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Among those with known SGTF status, the crude death rate associated with COVID-19 was 1.86 deaths per 10,000 person-days of follow-up in the SGTF group, versus 1.42 deaths per 10,000 person-days in the non-SGTF group (Fig. 1c and Extended Data Table 2).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 271
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 25
- Probably not a substantial claim. 26
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Cox regression analyses
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A small proportion (10.4%) of SGTF tests are inconclusive.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Just over half of those tested (1,146,534; 51.1%) had a conclusive SGTF reading and, of these, 58.8% had SGTF.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Characteristics of the study population
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“there were 17,913 age-0 individuals compared to 10,132 age-1 individuals in the dataset”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plainn = 17,913- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Characteristics of the study population
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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 ).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 273
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The IPW analysis gave similar results to the analysis of the complete cases, yielding a hazard ratio of 1.58 (1.40-1.78).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 273
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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%).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plainn = 2,245,263- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 271
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Misclassification analysis
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- 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.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“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%).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Characteristics of the study population
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Nature | Vol 593 | 13 May 2021 | 271
plainn = 19,615- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Sensitivity analyses
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“SGTF prevalence was the lowest in the most-deprived quintile of the index of multiple deprivation 3 (IMD) (53.9%).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Characteristics of the study population
What the sources say
- Not checked yetcites [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).
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Characteristics of the study population
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Area of residence and specimen date were expected to be potentially strong confounding factors.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Discussion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Unfortunately, we were unable to account for vaccination status in this analysis.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Misclassification of an exposure can result in bias in its estimated association with the outcome.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Misclassification analysis
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The baseline hazard in the Cox model was stratified by both specimen date and LTLA, therefore finely controlling for these variables.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Discussion
What the sources say
- Not checked yetcites [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 yetcites [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 yetcites [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).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“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 .”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Abstract
What the sources say
- Not checked yetcites [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
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § Discussion · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Absolute risks
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- 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.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We do not identify any mechanism for the increased mortality here.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
plainn = 2,245,263- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Abstract
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Statistical methods
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial 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.
“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.”
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?
In the citing paper
“and an estimated 50% increased mortality 194,195,202 .”
From The biological and clinical significance of emerging SARS-CoV-2 variants (2021) · cites this paper as [194]
In the citing paper
“Other studies have assessed the relative mortality of the VOC with similar conclusions [7-10], however, our results are the first to include detailed information on the presence of comorbidities.”
From Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England, 16 November to 5 February (2021) · cites this paper as [9]
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.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
“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”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Data sources
Reported 51.1 · recomputed 48.935425
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > Misclassification analysis
“downloaded from the Microreact platform 15 (https://microreact.org/) on 11 January 2020 to estimate p VOC .”
§ Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7 > 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.”
Citations
Cites
Regression Models and Life-Tables
Cox, D. R. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00899.x · Cited by 39,793
Regression Models and Life-Tables
Cox, D. R. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-4380-9_37 · Cited by 26,297
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2021) · Science · doi:10.1126/science.abg3055 · Cited by 2,581
Self-citationEstimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2020) · doi:10.1101/2020.12.24.20248822 · Cited by 2,557
Self-citationReview of inverse probability weighting for dealing with missing data
Seaman, S. R., & White, I. R. (2011) · Statistical Methods in Medical Research · doi:10.1177/0962280210395740 · Cited by 1,696
Challen, R., Brooks-Pollock, E., Read, J. M., Dyson, L., Tsaneva-Atanasova, K., & Danon, L. (2021) · BMJ · doi:10.1136/bmj.n579 · Cited by 776
Microreact: visualizing and sharing data for genomic epidemiology and phylogeography
Argimón, S., Abudahab, K., Goater, R. J. E., Fedosejev, A., Bhai, J., Glasner, C., Feil, E. J., Holden, M. T. G., Yeats, C. A., Grundmann, H., et al. (2016) · Microbial Genomics · doi:10.1099/mgen.0.000093 · Cited by 732
An integrated national scale SARS-CoV-2 genomic surveillance network
(2020) · The Lancet Microbe · doi:10.1016/s2666-5247(20)30054-9 · Cited by 261
Grint, D. J., Wing, K., Williamson, E., McDonald, H. I., Bhaskaran, K., Evans, D., Evans, S. J., Walker, A. J., Hickman, G., Nightingale, E., et al. (2021) · Eurosurveillance · doi:10.2807/1560-7917.es.2021.26.11.2100256 · Cited by 189
Keogh, R. H., Shaw, P. A., Gustafson, P., Carroll, R. J., Deffner, V., Dodd, K. W., Küchenhoff, H., Tooze, J. A., Wallace, M. P., Kipnis, V., et al. (2020) · Statistics in Medicine · doi:10.1002/sim.8532 · Cited by 180
Self-citation
Cited by
Sorted by citations
Items 101–200 of 957
Emerging SARS-CoV-2 Variants: Genetic Variability and Clinical Implications
Dubey, A., Choudhary, S., Kumar, P., & Tomar, S. (2021) · Current Microbiology · doi:10.1007/s00284-021-02724-1 · Cited by 79
Immunity to SARS-CoV-2 up to 15 months after infection
Marcotte, H., Piralla, A., Zuo, F., Du, L., Cassaniti, I., Wan, H., Kumagai‐Braesch, M., Andréll, J., Percivalle, E., Sammartino, J. C., et al. (2022) · iScience · doi:10.1016/j.isci.2022.103743 · Cited by 83
Tackling COVID-19 with neutralizing monoclonal antibodies
Corti, D., Purcell, L. A., Snell, G., & Veesler, D. (2021) · Cell · doi:10.1016/j.cell.2021.07.027 · Cited by 78
“Indeed, the B.1.1.7 variant was found to be more transmissible and cause more severe infections compared to the parental virus (Davies et al., 2021a, 2021b; Munitz et al., 2021).”
InfluentialRotondo, J. C., Martini, F., Maritati, M., Mazziotta, C., Mauro, G. D., Lanzillotti, C., Barp, N., Gallerani, A., Tognon, M. G., & Contini, C. (2021) · Viruses · doi:10.3390/v13091687 · Cited by 81
Counoupas, C., Johansen, M. D., Stella, A. O., Nguyen, D. H., Ferguson, A. L., Aggarwal, A., Bhattacharyya, N. D., Grey, A., Hutchings, O., Patel, K., et al. (2021) · npj Vaccines · doi:10.1038/s41541-021-00406-4 · Cited by 78
An early warning system for emerging SARS-CoV-2 variants
Subissi, L., von Gottberg, A., Thukral, L., Worp, N., Munnink, B. B. O., Rathore, S., Abu-Raddad, L. J., Aguilera, X., Alm, E., Archer, B. N., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01836-w · Cited by 79
SARS-CoV-2 Quasispecies Provides an Advantage Mutation Pool for the Epidemic Variants
Sun, F., Wang, X., Tan, S., Dan, Y., Lu, Y., Zhang, J., Xu, J., Tan, Z., Xiang, X., Zhou, Y., et al. (2021) · Microbiology Spectrum · doi:10.1128/spectrum.00261-21 · Cited by 76
Virologic Features of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children
Yonker, L. M., Boucau, J., Regan, J., Choudhary, M. C., Burns, M. D., Young, N. R., Farkas, E. J., Davis, J. P., Moschovis, P. P., Kinane, T. B., et al. (2021) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiab509 · Cited by 76
Mourier, T., Shuaib, M., Hala, S. M., Mfarrej, S., Alofi, F. S., Naeem, R., Alsomali, A., Jorgensen, D., Subudhi, A. K., Ben-Rached, F., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28287-8 · Cited by 75
Xia, S., Lan, Q., Zhu, Y., Wang, C., Xu, W., Li, Y., Wang, L., Jiao, F., Zhou, J., Hua, C., et al. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00712-2 · Cited by 73
A highly virulent variant of HIV-1 circulating in the Netherlands
Wymant, C., Bezemer, D., Blanquart, F., Luca Ferretti, A., Gall, A., Hall, M. D., Golubchik, T., Bakker, M., Ong, S. H., Zhao, L., et al. (2022) · Science · doi:10.1126/science.abk1688 · Cited by 72
Herrera, D., & Campos, G. D. L. (2022) · BMC Infectious Diseases · doi:10.1186/s12879-022-07262-0 · Cited by 78
Wang, H., Jean, S., Eltringham, R., Madison, J., Snyder, P. J., Tu, H., Jones, D. M., & Leber, A. L. (2021) · Journal of Clinical Microbiology · doi:10.1128/jcm.00926-21 · Cited by 72
SARS-CoV-2 variants, immune escape, and countermeasures
Zhang, Y., Zhang, H. C., & Zhang, W. (2022) · Frontiers of Medicine · doi:10.1007/s11684-021-0906-x · Cited by 72
Goethem, N. V., Chung, P. Y. J., Meurisse, M., Vandromme, M., Mot, L. D., Brondeel, R., Stouten, V., Klamer, S., Cuypers, L., Braeye, T., et al. (2022) · Viruses · doi:10.3390/v14061297 · Cited by 69
Schmidt, M., Hajage, D., Landoll, M., Péquignot, B., Langouet, E., Amalric, M., Dessap, A. M., Chiscano‐Camón, L., Surman, K., Finnerty, D., et al. (2023) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(22)00438-6 · Cited by 69
Zhang, H., Deng, S., Ren, L., Zheng, P., Hu, X., Jin, T., & Tan, X. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109708 · Cited by 69
Vitamin D and COVID-19: An Overview of Recent Evidence
Ghelani, D. P., Alesi, S., & Mousa, A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms221910559 · Cited by 71
Evolution of the SARS-CoV-2 spike protein in the human host
Wrobel, A. G., Benton, D. J., Roustan, C., Borg, A., Hussain, S., Martin, S. R., Rosenthal, P. B., Skehel, J. J., & Gamblin, S. J. (2022) · Nature Communications · doi:10.1038/s41467-022-28768-w · Cited by 69
Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
Brizzi, A., Whittaker, C., Servo, L. M. S., Hawryluk, I., Junior, C. A. P., de Souza, W. M., Aguiar, R. S., de Araújo, L. J. T., Bastos, L. S., Blenkinsop, A., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01807-1 · Cited by 74
Evolution of the SARS-CoV-2 Omicron Variants: Genetic Impact on Viral Fitness
Liu, W., Huang, Z., Xiao, J., Wu, Y., Xia, N., & Yuan, Q. (2024) · Viruses · doi:10.3390/v16020184 · Cited by 68
Brown, J. C., Goldhill, D. H., Zhou, J., Peacock, T. P., Frise, R., Goonawardane, N., Baillon, L., Kugathasan, R., Pinto, A., McKay, P. F., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.24.432576 · Cited by 70
Modelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era
Barnard, R. C., Davies, N. G., Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group, Munday, J. D., Lowe, R., Knight, G. M., Leclerc, Q. J., Tully, D. C., Hodgson, D., Pung, R., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32404-y · Cited by 68
Self-citationA SARS-CoV-2 Nucleocapsid Variant that Affects Antigen Test Performance
Bourassa, L. A., Perchetti, G. A., Phung, Q., Lin, M. J., Mills, M. G., Roychoudhury, P., Harmon, K. G., Reed, J. C., & Greninger, A. L. (2021) · Journal of Clinical Virology · doi:10.1016/j.jcv.2021.104900 · Cited by 66
Molecular evolution of SARS‐CoV‐2 from December 2019 to August 2022
Wolf, J. M., Wolf, L. M., Bello, G. L., Maccari, J. G., & Nasi, L. A. (2022) · Journal of Medical Virology · doi:10.1002/jmv.28366 · Cited by 69
SARS-CoV-2 escaped natural immunity, raising questions about vaccines and therapies
Andreano, E., & Rappuoli, R. (2021) · Nature Medicine · doi:10.1038/s41591-021-01347-0 · Cited by 66
One year into the pandemic: Short-term evolution of SARS-CoV-2 and emergence of new lineages
Gónzález‐Candelas, F., Shaw, M., Phan, T. G., Kulkarni‐Kale, U., Paraskevis, D. N., Luciani, F., Kimura, H., & Sironi, M. (2021) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2021.104869 · Cited by 65
Hamer, S. A., Ghai, R. R., Zecca, I. B., Auckland, L. D., Roundy, C. M., Davila, E., Busselman, R. E., Tang, W., Pauvolid‐Corrêa, A., Killian, M. L., et al. (2021) · Transboundary and Emerging Diseases · doi:10.1111/tbed.14122 · Cited by 65
COVID-19 vaccination in patients with multiple myeloma: a consensus of the European Myeloma Network
Ludwig, H., Sonneveld, P., Facon, T. T. F., Miguel, J. F. S., Avet‐Loiseau, H., Mohty, M., Mateos, M.-V., Moreau, P., Cavo, M., Pawlyn, C., et al. (2021) · The Lancet Haematology · doi:10.1016/s2352-3026(21)00278-7 · Cited by 66
SARS-CoV-2 variants and effectiveness of vaccines: a review of current evidence
Tatsi, E., Filippatos, F., & Michos, A. G. (2021) · Epidemiology and Infection · doi:10.1017/s0950268821002430 · Cited by 68
Verkhivker, G. M., Agajanian, S., Öztaş, D. Y., & Gupta, G. (2021) · Biochemistry · doi:10.1021/acs.biochem.1c00139 · Cited by 62
Muhsen, K., Na’aminh, W., Lapidot, Y., Goren, S., Amir, Y., Perlman, S., Green, M. S., Chodick, G., & Cohen, D. (2021) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2021.100130 · Cited by 65
Carcereny, A., Martínez-Velázquez, A., Bosch, A., Allende, A., Truchado, P., Cascales, J., Romalde, J. L., Lois, M., Polo, D., Sánchez, G., et al. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c03589 · Cited by 62
Rapid and accurate detection of SARS-CoV-2 mutations using a Cas12a-based sensing platform
He, C., Lin, C., Mo, G., Xi, B., Li, A., Huang, D., Wan, Y., Chen, F., Liang, Y., Zuo, Q., et al. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113857 · Cited by 61
Multiple COVID-19 Waves and Vaccination Effectiveness in the United States
Lin, L., Zhao, Y., Chen, B., & He, D. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19042282 · Cited by 62
SARS-CoV-2 variants – Evolution, spike protein, and vaccines
Chen, K.-W. K., Huang, D. T., & Huang, L. (2022) · Biomedical Journal · doi:10.1016/j.bj.2022.04.006 · Cited by 63
Upper respiratory tract mucosal immunity for SARS-CoV-2 vaccines
Fraser, R., Resendiz, A. O., Mazein, A., & Dockrell, D. H. (2023) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2023.01.003 · Cited by 61
SARS-CoV-2 Infectivity and Severity of COVID-19 According to SARS-CoV-2 Variants: Current Evidence
Dao, T. L., Hoang, V. T., Colson, P., Lagier, J., Million, M., Raoult, D., Levasseur, A., & Gautret, P. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10122635 · Cited by 61
Impact of vaccination and non-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland
Shattock, A. J., Rutte, E. A. L., Dünner, R. P., Sen, S., Kelly, S. L., Chitnis, N., & Penny, M. A. (2021) · Epidemics · doi:10.1016/j.epidem.2021.100535 · Cited by 64
Modular basis for potent SARS-CoV-2 neutralization by a prevalent VH1-2-derived antibody class
Rapp, M., Guo, Y., Reddem, E. R., Yu, J., Liu, L., Wang, P., Cerutti, G., Katsamba, P. S., Bimela, J. S., Bahna, F. A., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108950 · Cited by 59
The ins and outs of SARS-CoV-2 variants of concern (VOCs)
Salehi-Vaziri, ., Fazlalipour, M., Khorrami, S. M. S., Azadmanesh, K., Pouriayevali, M. H., Jalali, T., Shoja, Z., & Maleki, A. (2022) · Archives of Virology · doi:10.1007/s00705-022-05365-2 · Cited by 61
A randomised trial of anti-GM-CSF otilimab in severe COVID-19 pneumonia (OSCAR)
Patel, J., Bass, D., Beishuizen, A., Ruiz, X. B., Boughanmi, H., Cahn, A. P., Colombo, H. R., Criner, G. J., Davy, K., de Miguel‐Díez, J., et al. (2022) · European Respiratory Journal · doi:10.1183/13993003.01870-2021 · Cited by 59
Efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine against SARS-CoV-2 lineages circulating in Brazil
Clemens, S. A. C., Folegatti, P. M., Emary, K. R. W., Weckx, L. Y., Ratcliff, J., Bibi, S., Mendes, A. V. A., Milan, E. P., Pittella, A. M., Schwarzbold, A. V., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25982-w · Cited by 57
Jeffery-Smith, A., Rowland, T. A. J., Patel, M., Whitaker, H., Iyanger, N., Williams, S. V., Giddings, R., Thompson, L., Zavala, M., Aiano, F., et al. (2021) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(21)00253-1 · Cited by 60
CRISPR‐Mediated Profiling of Viral RNA at Single‐Nucleotide Resolution
Chen, D., Huang, W., Zhang, Y., Chen, B., Tan, J., Yuan, Q., & Yang, Y. (2023) · Angewandte Chemie International Edition · doi:10.1002/anie.202304298 · Cited by 59
Verma, J. K., & Subbarao, N. (2021) · Virology · doi:10.1016/j.virol.2021.06.009 · Cited by 56
Early epidemiological signatures of novel SARS-CoV-2 variants: establishment of B.1.617.2 in EnglandPreprint
Challen, R., Dyson, L., Overton, C. E., Guzman-Rincon, L. M., Hill, E. M., Stage, H. B., Brooks‐Pollock, E., Pellis, L., Scarabel, F., Pascall, D. J., et al. (2021) · medRxiv · doi:10.1101/2021.06.05.21258365 · Cited by 59
Therapeutic effect of CT-P59 against SARS-CoV-2 South African variant
Ryu, D.-K., Song, R., Kim, M., Kim, Y., Kim, C.-M., Kim, J., Kwon, K.-S., Tijsma, A. S. L., Nuijten, P. M., van Baalen, C. A., et al. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.06.016 · Cited by 55
Trends in ICU Mortality From Coronavirus Disease 2019: A Tale of Three Surges
Auld, S. C., Harrington, K. R. V., Adelman, M. W., Robichaux, C. J., Overton, E. C., Caridi-Scheible, M. E., Coopersmith, C. M., & Murphy, D. J. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000005185 · Cited by 55
Understanding the Secret of SARS-CoV-2 Variants of Concern/Interest and Immune Escape
Lou, F., Li, M., Pang, Z., Jiang, L., Guan, L., Tian, L., Hu, J., Fan, J., & Fan, H. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.744242 · Cited by 54
The way of SARS-CoV-2 vaccine development: success and challenges
Dong, Y., Dai, T., Wang, B., Zhang, L., Zeng, L., Huang, J., Yan, H., Zhang, L., & Zhou, F. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00796-w · Cited by 53
Galanis, P., Vraka, I. S., Katsiroumpa, A., Siskou, O. C., Konstantakopoulou, O., Katsoulas, T. A., Mariolis-Sapsakos, T. D., & Καϊτελίδου, Δ. (2022) · Vaccines · doi:10.3390/vaccines10071097 · Cited by 55
The molecular basis for SARS-CoV-2 binding to dog ACE2
Zhang, Z., Zhang, Y., Liu, K., Li, Y., Lu, Q., Wang, Q., Zhang, Y., Wang, L., Liao, H., Zheng, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24326-y · Cited by 52
SARS-CoV-2: phenotype, genotype, and characterization of different variants
Saberiyan, M., Karimi, E., Khademi, Z., Movahhed, P., Safi, A., & Ghahfarrokhi, A. M. (2022) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-022-00352-6 · Cited by 56
Lung fibrosis: Post-COVID-19 complications and evidences
Hirawat, R., Jain, N., Saifi, M. A., Rachamalla, M., & Godugu, C. (2022) · International Immunopharmacology · doi:10.1016/j.intimp.2022.109418 · Cited by 54
Kiem, C. T., Massonnaud, C., Lévy-Bruhl, D., Poletto, C., Colizza, V., Bosetti, P., Fontanet, A. L., Gabet, A., Olié, V., Zanetti, L. C. D. S., et al. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.101001 · Cited by 57
Dominance of Alpha and Iota variants in SARS-CoV-2 vaccine breakthrough infections in New York City
Duerr, R., Dimartino, D., Marier, C., Zappile, P., Wang, G., Lighter, J., Elbel, B. D., Troxel, A. B., & Heguy, A. (2021) · Journal of Clinical Investigation · doi:10.1172/jci152702 · Cited by 53
Andrade, V. M., Christensen-Quick, A., Agnes, J. T., Tur, J., Reed, C., Kalia, R., Marrero, I., Elwood, D., Schultheis, K., Purwar, M., et al. (2021) · npj Vaccines · doi:10.1038/s41541-021-00384-7 · Cited by 51
Nel, A. E., & Miller, J. F. (2021) · ACS Nano · doi:10.1021/acsnano.1c01845 · Cited by 50
Inequitable COVID-19 vaccine distribution and the intellectual property rights prolong the pandemic
Altındiş, E. (2021) · Expert Review of Vaccines · doi:10.1080/14760584.2022.2014819 · Cited by 50
NeutrobodyPlex—monitoring SARS-CoV-2 neutralizing immune responses using nanobodies
Wagner, T. R., Kaiser, P. D., Gramlich, M., Ostertag, E., Ruétalo, N., Junker, D., Häring, J., Traenkle, B., Becker, M., Dulovic, A., et al. (2021) · EMBO Reports · doi:10.15252/embr.202052325 · Cited by 50
Lives saved and hospitalizations averted by COVID-19 vaccination in New York City: a modeling study
Shoukat, A., VILCHES, T. N., Moghadas, S. M., Sah, P., Schneider, E. C., Shaff, J., Zucker, J. R., Quinn, C., Chokshi, D. A., & Galvani, A. P. (2021) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2021.100085 · Cited by 51
SARS-CoV-2 accessory protein ORF8 is secreted extracellularly as a glycoprotein homodimer
Matsuoka, K., Imahashi, N., Ohno, M., Ode, H., Nakata, Y., Kubota, M., Sugimoto, A., Imahashi, M., Yokomaku, Y., & Iwatani, Y. (2022) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2022.101724 · Cited by 49
Infection with SARS-CoV-2 Variants Is Associated with Different Long COVID Phenotypes
Spinicci, M., Graziani, L., Tilli, M., Nkurunziza, J., Vellere, I., Borchi, B., Mencarini, J., Campolmi, I., Gori, L., Giovannoni, L., et al. (2022) · Viruses · doi:10.3390/v14112367 · Cited by 49
Parker, M. D., Stewart, H., Shehata, O. M., Lindsey, B. B., Shah, D. R., Hsu, S. N., Keeley, A. J., Partridge, D. G., Leary, S., Cope, A., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03565-9 · Cited by 49
Nissinen, R., Leirisalo-Repo, M., Peltomaa, R., Palosuo, T., & Vaarala, O. (2004) · Annals of the Rheumatic Diseases · doi:10.1136/ard.2003.008599 · Cited by 50
Chen, L., Lu, L., Choi, C. Y.-K., Cai, J., Tsoi, H., Chu, A. W., Ip, J. D., Chan, W.-M., Zhang, R., Zhang, X., et al. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciab656 · Cited by 48
Xiong, S., Zhang, L., Qadir, A. S., Richner, J. M., Class, J., Rehman, J., & Malik, A. B. (2021) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.121.316925 · Cited by 48
Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies
Rouzine, I. M., & Rozhnova, G. (2023) · Communications Medicine · doi:10.1038/s43856-023-00320-x · Cited by 49
Long, S. W., Olsen, R. J., Christensen, P. A., Subedi, S., Olson, R., Davis, J. J., Saavedra, M. O., Yerramilli, P., Pruitt, L., Reppond, K., et al. (2021) · American Journal Of Pathology · doi:10.1016/j.ajpath.2021.03.004 · Cited by 46
Wollschläger, P., Tödt, D., Gerlitz, N., Pfaender, S., Bollinger, T., Sing, A., Dangel, A., Ackermann, N., Korn, K., Ensser, A., et al. (2021) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.05.025 · Cited by 47
Veneti, L., Seppälä, E. M., Storm, M. L., Salamanca, B. V., Buanes, E. A., Aasand, N., Naseer, U., Bragstad, K., Hungnes, O., Bøås, H., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0258513 · Cited by 46
Spike protein of SARS-CoV-2 variants: a brief review and practical implications
Candido, K. L., Eich, C. R., de Fariña, L. O., Kadowaki, M. K., Silva, J. L. D. C., Maller, A., & Simão, R. D. C. G. (2022) · Brazilian Journal of Microbiology · doi:10.1007/s42770-022-00743-z · Cited by 46
SARS‐CoV‐2 virulence evolution: Avirulence theory, immunity and trade‐offs
Alizon, S., & Sofonea, M. T. (2021) · Journal of Evolutionary Biology · doi:10.1111/jeb.13896 · Cited by 53
COVID-19, the first pandemic in the post-genomic era
van Dorp, L., Houldcroft, C. J., Richard, D., & Balloux, F. (2021) · Current Opinion in Virology · doi:10.1016/j.coviro.2021.07.002 · Cited by 49
Emergence of SARS-CoV-2 Variants in the World: How Could This Happen?
Parra-Lucares, A., Segura, P., Rojas, V. A., Pumarino, C., Saint-Pierre, G., & Toro, L. (2022) · Life · doi:10.3390/life12020194 · Cited by 49
Brunotte, L., Zheng, S., Mecate‐Zambrano, A., Tang, J. P., Ludwig, S., Rescher, U., & Schloer, S. (2021) · Pharmaceutics · doi:10.3390/pharmaceutics13091400 · Cited by 45
The Development of SARS-CoV-2 Variants: The Gene Makes the Disease
Pérez-Gómez, R. (2021) · Journal of Developmental Biology · doi:10.3390/jdb9040058 · Cited by 47
Biological Properties of SARS-CoV-2 Variants: Epidemiological Impact and Clinical Consequences
Hoteit, R., & Yassine, H. M. (2022) · Vaccines · doi:10.3390/vaccines10060919 · Cited by 47
Furukawa, K., Tjan, L. H., Kurahashi, Y., Sutandhio, S., Nishimura, M., Arii, J., & Mori, Y. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.10780 · Cited by 47
Lin, X., Glier, M. B., Kuchinski, K. S., Mierlo, T. R.-V., McVea, D., Tyson, J. R., Prystajecky, N., & Ziels, R. M. (2021) · mSystems · doi:10.1128/msystems.01068-21 · Cited by 47
Yang, Z. L., Zhang, S., Tang, Y., Zhang, S., Xu, D.-Q., Yue, S., & Liu, Q. (2022) · Aging and Disease · doi:10.14336/ad.2021.1210 · Cited by 46
Peng, L., Hu, Y., Mankowski, M. C., Ren, P., Chen, R. E., Wei, J., Zhao, M., Li, T., Tripler, T. N., Ye, L., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29288-3 · Cited by 43
Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests
Roland, T., Böck, C., Tschoellitsch, T., Maletzky, A., Hochreiter, S., Meier, J., & Klambauer, G. (2022) · Journal of Medical Systems · doi:10.1007/s10916-022-01807-1 · Cited by 42
Pathogen evolution during vaccination campaigns
Day, T., Kennedy, D. A., Read, A. F., & Gandon, S. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001804 · Cited by 42
Rice, A., Verma, M. S., Shin, A., Zakin, L., Sieling, P. A., Tanaka, S., Balint, J. P., Dinkins, K., Adisetiyo, H., Morimoto, B., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-94364-5 · Cited by 43
Alves, P. A., de Oliveira, E. G., Franco-Luiz, A. P. M., Almeida, L. T., Gonçalves, A. B., Borges, I. A., Rocha, F. D. S., Rocha, R. P., Bezerra, M. F., Miranda, P., et al. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.713713 · Cited by 43
Hybrid CRISPR/Cas protein for one-pot detection of DNA and RNA
Guk, K., Yi, S., Kim, H., Bae, Y., Yong, D., Kim, S., Lee, K., Lim, E., Kang, T., & Jung, J. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114819 · Cited by 42
Circulating SARS-CoV-2 variants in Italy, October 2020–March 2021
Lai, A., Bergna, A., Menzo, S., Zehender, G., Caucci, S., Ghisetti, V., Rizzo, F. M., Maggi, F., Cerutti, F., Giurato, G., et al. (2021) · Virology Journal · doi:10.1186/s12985-021-01638-5 · Cited by 41
SARS-CoV-2 Delta variant induces enhanced pathology and inflammatory responses in K18-hACE2 mice
Lee, K. S., Wong, T. Y., Russ, B. P., Horspool, A. M., Miller, O. A., Rader, N. A., Givi, J. P., Winters, M. T., Wong, Z. Y., Cyphert, H. A., et al. (2022) · PLoS ONE · doi:10.1371/journal.pone.0273430 · Cited by 42
Gout and the risk of COVID-19 diagnosis and death in the UK Biobank: a population-based study
Topless, R., Gaffo, A., Stamp, L. K., Robinson, P. C., Dalbeth, N., & Merriman, T. R. (2022) · The Lancet Rheumatology · doi:10.1016/s2665-9913(21)00401-x · Cited by 40
Superspreading in the emergence of COVID-19 variants
Gómez‐Carballa, A., Pardo‐Seco, J., Bello, X., Martinón‐Torres, F., & Salas, A. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.09.003 · Cited by 42
Brandherm, L., Kobaš, A. M., Klöhn, M., Brüggemann, Y., Pfaender, S., Rassow, J., & Kreimendahl, S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179233 · Cited by 39
Christie, M. J., Irving, A. T., Forster, S. C., Marsland, B. J., Hansbro, P. M., Hertzog, P. J., Nold‐Petry, C. A., & Nold, M. F. (2021) · Science Immunology · doi:10.1126/sciimmunol.abd0205 · Cited by 41
COVID-19 rise in Bangladesh correlates with increasing detection of B.1.351 variant
Saha, S., Tanmoy, A. M., Hooda, Y., Tanni, A. A., Goswami, S., Sium, S. M. A., Sajib, M. S. I., Malaker, R., Islam, S., Rahman, H., et al. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2021-006012 · Cited by 39
Zelyas, N. J., Pabbaraju, K., Croxen, M. A., Lynch, T., Buss, E., Murphy, S. A., Shokoples, S., Wong, A. A., Kanji, J. N., & Tipples, G. A. (2021) · Microbiology Spectrum · doi:10.1128/spectrum.00315-21 · Cited by 38
Modeling waning and boosting of COVID-19 in Canada with vaccination
Childs, L. M., Dick, D. W., Feng, Z., Heffernan, J. M., Li, J., & Röst, G. (2022) · Epidemics · doi:10.1016/j.epidem.2022.100583 · Cited by 41
Projecting the impact of a two-dose COVID-19 vaccination campaign in Ontario, Canada
VILCHES, T. N., Zhang, K., Exan, R. V., Langley, J. M., & Moghadas, S. M. (2021) · Vaccine · doi:10.1016/j.vaccine.2021.03.058 · Cited by 39
Xiao, H., Hu, J., Huang, C., Feng, W., Liu, Y., Kumblathan, T., Tao, J., Xu, J., Le, X. C., & Zhang, H. (2023) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2023.117000 · Cited by 39
Cabecinhas, A. R. G., Roloff, T. C., Stange, M., Bertelli, C., Huber, M., Ramette, A., Chen, C., Nadeau, S., Gerth, Y., Yerly, S., et al. (2021) · Microorganisms · doi:10.3390/microorganisms9040677 · Cited by 37
Metadata
- 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.
- Venue
- Nature
- Published
- 2021-03-15
- Volume
- 593
- Issue
- 7858
- Pages
- 270-274
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC9170116
- OpenAlex
- W3137149656
- Cited by
- 921
- References
- 12
- Citations by year
- 2026: 12 · 2025: 37 · 2024: 74 · 2023: 130 · 2022: 303 · 2021: 362
- FWCI
- 68.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- 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.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
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 ›
Are you an author, or do you see a problem with this page? Request a review
