Studies published online on 12 April 2021 in The Lancet Infectious Diseases and The Lancet Public Health suggest that COVID-19 variant B.1.1.7 is more transmissible, but does not increase disease severity. Researchers found no evidence that people with the B.1.1.7. variant experience worse symptoms or heightened risk of developing long COVID compared to those infected with a different COVID-19 strain.

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Historical developments

On December 14th 2020, the UK Government got a notification of the emergence of a SARS-CoV-2 variant. This lineage had no obvious genetically close precursor within publicly available genomic datasets and is now defined as lineage B.1.1.7, within the COVID-19 Genomics UK Consortium (COG-UK) dataset. Researchers expressed concern about transmissibility, pathogenicity, and effect of the variant on vaccine efficacy as they identified its defining features which include deletion and several mutations within the key encoding the spike protein in the receptor-binding domain.

The UK authorities increased physical distancing restrictions in London shortly afterwards on December 21st 2020, in an effort to curb further spread of this variant. The preliminary data on B.1.1.7, indicates that it is more transmissible, with some evidence suggesting it could also be associated with increased hospitalisations and deaths. However, because the researchers identified the variant only recently, these studies were limited by the amount of data available.

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The first study

In the study published in The Lancet Infectious Diseases, researchers Dr Dan Frampton and his colleagues sequenced viral genomes from the combined nose and throat swab samples, taken from patients with SARS-CoV-2 infection collected from November 9th 2020, for patients suffering from acute disease admitted to a ward at either University College London Hospitals (UCLH) or North Middlesex University Hospital (NMUH) on or before December 20th, 2020, for any clinical reason.

They selected the dates for the study as the first hospitalised patient with the B.1.1.7, variant was admitted on November 9th 2020, and the B.1.1.7, variant became dominant in both hospitals by December 20th, with this date coinciding with a surge in hospitalisations that stretched the capacity of the health services. Researchers included all hospitalised patients with a positive PCR test during this time period in the study.

Researchers have been raising concerns around the emergence of variants of concern in long-shedding, immune-compromised or treated patients, especially when treatment modalities and prophylaxis target the spike protein (eg, convalescent plasma, monoclonal antibodies, and vaccination).

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Increased viral load but no association with increased severity and death

The researchers published the paper in The Lancet Infectious Diseases journal based on a whole-genome sequencing and cohort study involving COVID-19 patients admitted to University College London Hospital and North Middlesex University Hospital, UK, between November 9 and December 20th, 2020. At this time point, both the original and B.1.1.7, variants were circulating in London, the vaccination programme was just starting, and before a significant surge in cases in early 2021 caused a strain on the National Health Service.

The researchers compared illness severity in people with and without B.1.1.7 and calculated viral load. Among 341 patients who had their COVID-19 test swabs sequenced, 58% (198/341) had B.1.1.7, and 42% (143/341) had a non-B.1.1.7. Infection (two patients’ data were excluded from further analysis).

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Findings from the study

1. The researchers did not find evidence of an association between the variant and increased disease severity, with 36% (72/198) of B.1.1.7, patients becoming severely ill or dying, compared with 38% (53/141) of those with a non-B.1.1.7 strain.
2. Patients with the variant tended to be younger, with 55% (109/198) of infections in people under 60 compared with 40% (57/141), for those who did not have B.1.1.7.
3. Infections with B.1.1.7 occurred more frequently in ethnic minority groups, accounting for 50% (86/172) of cases that included ethnicity data, compared with 29% (35/120) for non-B.1.1.7 strains.
4. In a regression analysis that included 289 patients, the researchers found that those with B.1.1.7 were no more likely to experience severe disease after accounting for hospital, sex, age, ethnicity, and underlying conditions.
5. Those with B.1.1.7, were no more likely to die than patients with a different strain, with 16% (31/198) of B.1.1.7, patients dying within 28 days compared with 17% (24/141) for those with a non-B.1.1.7, infection.
6. More patients with B.1.1.7, were given oxygen by mask or nasal cannula than those with a non-B.1.1.7, strain (44%, 88/198 vs 30%, 42/141, respectively). However, the authors say this is not a clear measure of disease severity, as patients may have received nasal prong oxygen for reasons unrelated to COVID-19, or as a consequence of underlying conditions.
7. To gain insights into the transmissibility of B.1.1.7, the authors used data generated by PCR testing of patient swabs to predict their viral load – the amount of virus in a person’s nose and throat. This analysis indicated that B.1.1.7, samples tended to contain greater quantities of the virus than non-B.1.1.7 swabs.

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Additional findings of the research

“One of the real strengths of our study is that it ran at the same time that B.1.1.7, was emerging and spreading throughout London and the south of England. Analysing the variant before the peak of hospital admissions and any associated strains on the health service gave us a crucial window of time to gain vital insights into how B.1.1.7, differs in severity or death in hospitalised patients from the strain of the first wave. Our study is the first in the UK to utilise whole-genome sequencing data generated in real-time and embedded in an NHS clinical service and integrated granular clinical data. We hope that this study provides an example of how such studies can be done for the benefit of patients throughout the NHS. As more variants continue to emerge, using this approach could help us better understand their key characteristics and any additional challenges that they may pose to public health," stated Dr Eleni Nastouli, from University College London Hospitals NHS Foundation Trust and the UCL Great Ormond Street Institute of Child Health, UK, in a press release from the journal.

The authors acknowledged that their study has some limitations thus, the researchers captured the disease severity within 14 days of a positive COVID-19 test. Hence, patients who may have deteriorated after 14 days may have been missed in the analysis, though the authors sought to mitigate this by capturing deaths at 28 days. The analyses also did not take account of any other treatments that patients were receiving such as steroids, antiviral medications, or convalescent plasma or the possibility that some patients may have received ventilation for reasons other than COVID-19.

"The authors’ observation that B.1.1.7 infections were associated with increased viral loads corroborates findings from two other studies and provides a mechanistic hypothesis that increased transmissibility is via increased respiratory shedding. Yet, disease severity and clinical outcomes between patients with B.1.1.7 and non-B.1.1.7 infections were similar after adjusting for differences in age, sex, ethnicity, and co-morbidities. Importantly, this study was done from November 9th to December 20th, 2020, before the late- December peak in UK COVID-19 infections, avoiding any confounding effect of the availability of healthcare resources on mortality. This finding is in contrast with three studies that reported increased mortality associated with lineage B.1.1.7”, Sean Wei Xiang Ong, Barnaby Edward Young, and David Chien Lye, from the National Centre for Infectious Diseases, Singapore, who were not involved in the study, wrote in a linked comment.

“Thus, although limited by a much smaller dataset, the study by Frampton and colleagues has important advantages over the three community studies. These advantages include the use of whole-genome sequencing, recruitment of hospitalised patients, and a population reflective of the spectrum of severity in whom increased virulence will have the greatest effect on outcomes”, they clarified. “The finding that lineage B.1.1.7  infection did not confer an increased risk of severe disease and mortality in this high-risk cohort is reassuring but requires further confirmation in larger studies”, they cautioned.

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The second study

The second study, published simultaneously in The Lancet Public Health by Dr Mark Graham of King's College London in England, and colleagues found no significant differences in reported symptoms or disease duration in patients with B.1.1.7 among users reporting their COVID-19 test results through an app. Researchers collected the test results and symptom reports from September 28 to December 20 from about 36,920 users of the COVID Symptom Study app. who tested positive for COVID-19 between 28 September and 27th December 2020.

Graham and colleagues put that together with data on the regional proportion of infections, symptoms, disease duration, re-infection rates, and transmissibility from the COVID-19 Genomics U.K. Consortium and Public Health England. The analysis covered 13 full weeks over the period when the proportion of B.1.1.7, grew most notably in London, South East and East of England. Researchers included users in a week if they had reported a positive test during the 14 days before or after that week. For each week in every region in the analysis (Scotland, Wales, and the seven NHS England regions), researchers calculated the proportion of users reporting any of 14 COVID-19 symptoms.

“We could only do this by aggregating two large sources of data: the extensive genetic sequencing of viral strains performed in the UK, and symptom and testing logs from millions of users on the COVID-symptom Study App. Thanks to them, we confirmed the increased transmissibility but also showed that B.1.1.7, clearly responded to lockdown measures and doesn’t appear to escape immunity gained by exposure to the original virus. If further new variants emerge, we will be scanning for changes in symptom reporting and re-infection rates, and sharing this information with health policymakers”, Dr Claire Steves, Reader and Honorary Consultant Physician, King’s College London, UK, who co-led the study, said in a press release from the journal.

For each region and symptom, researchers carried out a linear regression to examine the association between the proportion of B.1.1.7, in that region and the proportion of users reporting the symptom during the study period. The analysis adjusted for age, sex, and seasonal factors (regional temperature and humidity) that could affect reporting of some symptoms. The analysis revealed no statistically significant associations between the proportion of B.1.1.7, within regions and the type of symptoms people experienced.

There was also no evidence of any change in the total number of symptoms experienced by people with B.1.1.7 in the South East region, which experienced the earliest rise in B.1.1.7. The proportion of people who experienced long COVID (here defined as symptoms persisting for more than 28 days without a break of more than 7 days) was also not altered by B.1.1.7. The re-infection rate was low, with 0.7% (249/36,509) of those who reported a positive test before October 1st 2020, testing positive again more than 90 days later.

The analysis found no evidence that the re-infection rate was altered by B.1.1.7 for all regions except Scotland (where fewer data was available due to fewer users of the app), re-infections were more positively correlated with the overall regional rise in cases than the regional rise in the proportion of B.1.1.7, infections. No difference in re-infection rates was reported across study regions. However, the authors found that B.1.1.7, increased the overall reproduction number, or R number, by 1.35 times compared with the original strain.

This estimate is similar to those from other studies investigating the variant’s transmissibility. Despite this increase, the analysis indicates that the R number was below 1 – indicating falling transmission. During local and national lockdowns, even in the three regions (London, South East, and East of England) with the highest proportions of B.1.1.7, which accounted for 80% of infections.

“The wealth of data captured by the COVID Symptom Study app provided a unique opportunity to look for potential changes in symptoms and length of illness associated with the B.1.1.7 variant.  Reassuringly, our findings suggest that, despite being more easily spread, the variant does not alter the type or duration of symptoms experienced and we believe current vaccines and public health measures are likely to remain effective against it”, Dr Mark Graham, from King’s College London, UK, stated in a press release.

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Limitations of the study

It was not possible to assess the causal effects of B.1.1.7, due to the lack of information on the disease strain of individual positive cases reported through the app. Users may also have made errors when inputting their information through the app. People who sign up to the app are likely to be more interested in health and COVID-19 than the wider population and may exhibit different behaviour to other members of the population.

“This study adds to the consensus that B.1.1.7 has increased transmissibility, which has contributed in a large part to the sharp rise in cases in the UK over the study period and beyond, as well as ongoing third waves in European countries with growing burdens of B.1.1.7 cases. However, Graham and colleagues reach somewhat different conclusions about differences in symptoms than those of the UK Office for National Statistics, which reported that a higher proportion of individuals who tested positive for the B.1.1.7 variant had at least one symptom compared with those without the variant. Graham and colleagues acknowledge the limitations of using self-reported digital data for this type of analysis, including the inherent selection bias of app-based data, which could cause confounding that might explain some of the differences in findings”, writing in a linked comment, Dr Britta Jewell, from Imperial College London, UK, who was not involved in the study, said in the press release.

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Conclusion

Dr Jewell reported-

"The data suggests that, despite important changes in transmissibility and mortality, B.1.1.7 is similar enough to non-VOC lineages for current testing infrastructure and symptom profiles to identify new cases. Additionally, existing non-pharmaceutical interventions can reduce the Rt of B.1.1.7 to below 1, given adequate governmental planning. Fortunately, B.1.1.7 also appears to be quite effectively combated by existing vaccines."

Despite their limitations, these studies are important as specialists are eagerly examining the health impact of virus-variants on the disease.

Disclaimer- The views and opinions expressed in this article are those of the author's and do not necessarily reflect the official policy or position of M3 India.

Dr K S Parthasarathy is a former Secretary of the Atomic Energy Regulatory Board and a former Raja Ramanna Fellow, Department of Atomic Energy. A Ph. D. from the University of Leeds, UK, he is a medical physicist with a specialisation in radiation safety and regulatory matters. He was a Research Associate at the University of Virginia Medical Centre, Charlottesville, USA. He served the International Atomic Energy Agency as an expert and member in its Technical and Advisory Committees.