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_nickdavies's profile
Nick Davies
Nick Davies
Nick Davies
@_nickdavies

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Nick Davies

@_nickdavies

Evolutionary biologist & epidemiologist. COVID-19, antibiotic resistance, cooperation & insect societies. Assistant professor @LSHTM @CMMID_lshtm. He/him.

London, England
bit.ly/3yeVK5z
Joined March 2019

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    Nick Davies‏ @_nickdavies 15 Mar 2021

    Our paper “Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7” is in Nature today. We find that B.1.1.7, the UK coronavirus variant identified in late 2020, is associated with 55% higher COVID-19 mortality than other lineages. https://www.nature.com/articles/s41586-021-03426-1 … 1/16pic.twitter.com/Jv9790BBYi

    5:42 AM - 15 Mar 2021
    • 1,325 Retweets
    • 2,273 Likes
    • Николай М. Irene Wellman Kevin Newman ping Kim Daigle Esteban Pardo 𝕷𝖆𝖚𝖗𝖆 💉💉🚀 💙😷 ↔️ 👩🏻‍🔬🧬🧫🧪🌱🤞🕯 mark daly Juan Enriquez
    57 replies 1,325 retweets 2,273 likes
      1. New conversation
      2. Nick Davies‏ @_nickdavies 15 Mar 2021

        The LSHTM team has been analysing B.1.1.7 for signs of increased or decreased severity since late December. We first identified a signal of higher mortality in mid-January. This led to an announcement by the PM and @uksciencechief on 22 January. https://www.bbc.co.uk/news/health-55768627 … 2/16

        4 replies 52 retweets 141 likes
        Show this thread
      3. Nick Davies‏ @_nickdavies 15 Mar 2021

        In that early report, we estimated that B.1.1.7 was associated with a ~35% increase in mortality, based on around 2600 deaths, of which 384 had the SGTF marker for B.1.1.7. Our updated analysis is based on 4900 deaths, around 3100 of which had SGTF. 3/16pic.twitter.com/dQFd0s2Efx

        1 reply 35 retweets 124 likes
        Show this thread
      4. Nick Davies‏ @_nickdavies 15 Mar 2021

        Using a statistical technique called a Cox proportional hazards model, we found that people infected with B.1.1.7 had a 55% (95% CI 39–72%) higher rate of mortality within 28 days of receiving a positive test. 4/16pic.twitter.com/b5ChqT8IbE

        2 replies 54 retweets 125 likes
        Show this thread
      5. Nick Davies‏ @_nickdavies 15 Mar 2021

        The analysis controls for age, sex, deprivation, ethnicity & care home/residential/other residence type. We only compare death rates among people living in the same local authority, who were tested on the same day, to control for changes in test rates and hospital pressure. 5/16pic.twitter.com/YNgetw9Vls

        1 reply 32 retweets 110 likes
        Show this thread
      6. Nick Davies‏ @_nickdavies 15 Mar 2021

        We did not find any statistically significant differences in the increased mortality rate associated with B.1.1.7 by age, sex, IMD, ethnicity, or residence type. 6/16pic.twitter.com/EqK4oTBaUz

        2 replies 33 retweets 94 likes
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      7. Nick Davies‏ @_nickdavies 15 Mar 2021

        We did lots of sensitivity analyses. 7/16pic.twitter.com/lQw5pfr73o

        1 reply 17 retweets 56 likes
        Show this thread
      8. Nick Davies‏ @_nickdavies 15 Mar 2021

        While we use a statistical model to account for all the confounding factors, you do not need a model to see that B.1.1.7 is associated with higher mortality in this study sample. The raw data show the pattern clearly. The stats are there to get a clearer estimate. 8/16pic.twitter.com/noGn8q5kBR

        3 replies 32 retweets 106 likes
        Show this thread
      9. Nick Davies‏ @_nickdavies 15 Mar 2021

        I think the most convincing way of looking at the raw data is by comparing the observed number of deaths per follow-up day, stratified here by a number of characteristics. Diamonds higher than circles = increased mortality among subjects with SGTF (the marker for B.1.1.7). 9/16pic.twitter.com/ZVP5FnFgpz

        2 replies 22 retweets 60 likes
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      10. Nick Davies‏ @_nickdavies 15 Mar 2021

        Our study sample is people tested in the community. If those infected with B.1.1.7 were less likely to get a test, we might only detect severe cases & hence overestimate mortality. But we found no major differences in test seeking (if anything, slight increase for B.1.1.7). 10/16pic.twitter.com/V2Y05Kaq4A

        2 replies 20 retweets 68 likes
        Show this thread
      11. Nick Davies‏ @_nickdavies 15 Mar 2021

        Other groups working contemporaneously and since have found similar results: Challen et al https://www.bmj.com/content/372/bmj.n579 … Grint et al https://www.medrxiv.org/content/10.1101/2021.03.04.21252528v1.full.pdf … Patone et al https://www.medrxiv.org/content/10.1101/2021.03.11.21253364v1.full.pdf … Bager et al (Denmark) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3792894 … And others https://www.gov.uk/government/publications/nervtag-update-note-on-b117-severity-11-february-2021 … 11/16

        1 reply 25 retweets 77 likes
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      12. Nick Davies‏ @_nickdavies 15 Mar 2021

        Overall, the emerging picture is pretty consistent. 12/16pic.twitter.com/WD4OwFpiwm

        1 reply 19 retweets 65 likes
        Show this thread
      13. Nick Davies‏ @_nickdavies 15 Mar 2021

        What does this mean? First, it helps to explain why the UK has seen so many COVID-19 deaths in the last three months, together with the increased infectiousness of B.1.1.7, as we described here: https://science.sciencemag.org/content/early/2021/03/03/science.abg3055 … 13/16

        2 replies 52 retweets 107 likes
        Show this thread
      14. Nick Davies‏ @_nickdavies 15 Mar 2021

        Second, it adds more evidence that other countries may have a difficult time in the months ahead. Vaccines are effective against B.1.1.7 and will help a lot. https://science.sciencemag.org/content/371/6534/1152 … https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3779160 … 14/16

        6 replies 60 retweets 160 likes
        Show this thread
      15. Nick Davies‏ @_nickdavies 15 Mar 2021

        Thanks to: coauthors @Jarvis_Stats John Edmunds @NP_Jewell @karlado @RuthHKeogh; @cmmid_lshtm & @LSHTM; peer reviewers; @rjchallen, @leondanon, SPI-M & NERVTAG for discussions. Big thanks to @PHE_uk for allowing us to release anonymised data: https://github.com/nicholasdavies/cfrvoc … 15/16

        2 replies 17 retweets 71 likes
        Show this thread
      16. Nick Davies‏ @_nickdavies 15 Mar 2021

        And for funding support, thanks to @NIHRresearch @UKRI_News @The_MRC @GCRF @ESRC @EU_Commission @NIH @NIAIDNews @royalsociety @wellcometrust. 16/16

        11 replies 8 retweets 57 likes
        Show this thread
      17. End of conversation

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