Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

被引:235
作者
Graham, Mark S. [1 ]
Sudre, Carole H. [1 ,3 ,4 ]
May, Anna [5 ]
Antonelli, Michela [1 ]
Murray, Benjamin [1 ]
Varsaysky, Thomas [1 ]
Klaser, Kerstin [1 ]
Canas, Liane S. [1 ]
Molteni, Erika [1 ]
Modat, Marc [1 ]
Drew, David A. [6 ,7 ]
Nguyen, Long H. [6 ,7 ]
Polidori, Lorenzo [5 ]
Selvachandran, Somesh [5 ]
Hu, Christina [5 ]
Capdevila, Joan [5 ]
Hammers, Alexander [1 ]
Chan, Andrew T. [6 ,7 ]
Wolf, Jonathan [5 ]
Spector, Tins D. [2 ]
Steves, Claire J. [2 ]
Ourselin, Sebastien [1 ]
机构
[1] Kings Coll London, Sch Biomed Engn & Imaging Sci, London SE1 7EH, England
[2] Kings Coll London, Dept Twin Res & Genet Epidemiol, London, England
[3] UCL, Dept Populat Sci & Expt Med, MRC Unit Lifelong Hlth & Ageing, London, England
[4] UCL, Ctr Med Image Comp, Dept Comp Sci, London, England
[5] Zoe Global, London, England
[6] Massachusetts Gen Hosp, Clin & Translat Epidemiol Unit, Boston, MA 02114 USA
[7] Harvard Med Sch, Boston, MA 02115 USA
基金
英国医学研究理事会; 英国惠康基金;
关键词
D O I
10.1016/S2468-2667(21)00055-4
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, R-t, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0.7% [95% CI 0.6-0.8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0.56-0.69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0.38-0.56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the R-t of B.1.1.7 by a factor of 1.35 (95% CI 1.02-1.69) relative to pre-existing variants. However, R-t fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant.
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收藏
页码:E335 / E345
页数:11
相关论文
共 28 条
[1]  
[Anonymous], 2021, LANCET, V397, P445, DOI 10.1016/S0140-6736(21)00257-9
[2]  
[Anonymous], 2021, NEW EMERGING RESP VI
[3]  
Baltrusaitis Kristin, 2017, JMIR Public Health Surveill, V3, pe18, DOI 10.2196/publichealth.7304
[4]  
Bell John I, 2021, medRxiv, DOI [10.1101/2021.01.13.21249721, DOI 10.1101/2021.01.13.21249721V1, DOI 10.1101/2021.01.13.21249721]
[5]   An integrated national scale SARS-CoV-2 genomic surveillance network [J].
Aanensen, David M. ;
Abudahab, Khalil ;
Adams, Alexander ;
Afifi, Safiah ;
Alam, Mohammed T. ;
Alderton, Alex ;
Alikhan, Nabil-Fareed ;
Allan, John ;
Almsaud, Mai ;
Alrezaihi, Abdulrahman ;
Alruwaili, Muhannad ;
Amato, Roberto ;
Andersson, Monique ;
Angyal, Adrienn ;
Aranday-Cortes, Elihu ;
Ariani, Cristina ;
Armstrong, Stuart D. ;
Asamaphan, Patawee ;
Attwood, Stephen ;
Aydin, Alp ;
Badhan, Anjna ;
Baker, David ;
Baker, Paul ;
Balcazar, Carlos E. ;
Ball, Jonathan ;
Barton, Anjna Edward ;
Bashton, Matthew ;
Baxter, Laura ;
Beale, Matthew ;
Beaver, Charlotte ;
Beckett, Angela ;
Beer, Rob ;
Beggs, Andrew ;
Bell, Andrew ;
Bellis, Katherine L. ;
Bentley, Eleanor G. ;
Berriman, Matt ;
Betteridge, Emma ;
Bibby, David ;
Bicknell, Kelly ;
Birchley, Alec ;
Black, Gary ;
Blane, Beth ;
Bloomfield, Samuel ;
Bolt, Frankie ;
Bonsall, David G. ;
Bosworth, Andrew ;
Bourgeois, Yann ;
Boyd, Olivia ;
Bradshaw, Daniel .
LANCET MICROBE, 2020, 1 (03) :E99-E100
[6]   Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England [J].
Davies, Nicholas G. ;
Abbott, Sam ;
Barnard, Rosanna C. ;
Jarvis, Christopher, I ;
Kucharski, Adam J. ;
Munday, James D. ;
Pearson, Carl A. B. ;
Russell, Timothy W. ;
Tully, Damien C. ;
Washburne, Alex D. ;
Wenseleers, Tom ;
Gimma, Amy ;
Waites, William ;
Wong, Kerry L. M. ;
van Zandvoort, Kevin ;
Silverman, Justin D. ;
Diaz-Ordaz, Karla ;
Keogh, Ruth ;
Eggo, Rosalind M. ;
Funk, Sebastian ;
Jit, Mark ;
Atkins, Katherine E. ;
Edmunds, W. John .
SCIENCE, 2021, 372 (6538) :149-+
[7]  
Department of Health and Social Care Scientific Advisory Group for Emergencies UK, COR COVID 19 R VAL G
[8]   Rapid implementation of mobile technology for real-time epidemiology of COVID-19 [J].
Drew, David A. ;
Nguyen, Long H. ;
Steves, Claire J. ;
Menni, Cristina ;
Freydin, Maxim ;
Varsavsky, Thomas ;
Sudre, Carole H. ;
Cardoso, M. Jorge ;
Ourselin, Sebastien ;
Wolf, Jonathan ;
Spector, Tim D. ;
Chan, Andrew T. .
SCIENCE, 2020, 368 (6497) :1362-+
[9]   Rapid review of available evidence on the serial interval and generation time of COVID-19 [J].
Griffin, John ;
Casey, Miriam ;
Collins, Aine ;
Hunt, Kevin ;
McEvoy, David ;
Byrne, Andrew ;
McAloon, Conor ;
Barber, Ann ;
Lane, Elizabeth Ann ;
More, SImon .
BMJ OPEN, 2020, 10 (11)
[10]   Collider bias undermines our understanding of COVID-19 disease risk and severity [J].
Griffith, Gareth J. ;
Morris, Tim T. ;
Tudball, Matthew J. ;
Herbert, Annie ;
Mancano, Giulia ;
Pike, Lindsey ;
Sharp, Gemma C. ;
Sterne, Jonathan ;
Palmer, Tom M. ;
Smith, George Davey ;
Tilling, Kate ;
Zuccolo, Luisa ;
Davies, Neil M. ;
Hemani, Gibran .
NATURE COMMUNICATIONS, 2020, 11 (01)