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Volume 28, Number 3—March 2022
Research

Spatiotemporal Analyses of 2 Co-Circulating SARS-CoV-2 Variants, New York State, USA

Alexis Russell1, Collin O’Connor1, Erica Lasek-Nesselquist1, Jonathan Plitnick, John P. Kelly, Daryl M. Lamson, and Kirsten St. GeorgeComments to Author 
Author affiliations: New York State Department of Health, Albany, New York, USA (A. Russell, C. O’Connor, E. Lasek-Nesselquist, J. Plitnick, J.P. Kelly, K. St. George); State University of New York at Buffalo, Buffalo, New York, USA (C. O’Connor); State University of New York at Albany, Albany (E. Lasek-Nesselquist, K. St. George)

Main Article

Figure 3

Time-calibrated phylogeny of severe acute respiratory syndrome coronavirus 2 variant B.1.526, New York and other states, USA, December 2020–April 2021. Left panel represents a maximum-likelihood phylogeny of 980 genomes from New York and other US states generated in IQTree 1.6.12 (20) with timescale inferred by TreeTime 0.7.6 (22) and ancestral state reconstruction performed in BEAST 2.6.2 (23). Faceted panels indicate the source of B.1.526 introductions into different regions of New York and other states (domestic). Only introductions supported by an ancestral state probability of >0.7 are shown. Bottom panel shows locations sampled and sample sizes. A, April; J, January; O, October.

Figure 3. Time-calibrated phylogeny of severe acute respiratory syndrome coronavirus 2 variant B.1.526, New York and other states, USA, December 2020–April 2021. Left panel represents a maximum-likelihood phylogeny of 980 genomes from New York and other US states generated in IQTree 1.6.12 (20) with timescale inferred by TreeTime 0.7.6 (22) and ancestral state reconstruction performed in BEAST 2.6.2 (23). Faceted panels indicate the source of B.1.526 introductions into different regions of New York and other states (domestic). Only introductions supported by an ancestral state probability of >0.7 are shown. Bottom panel shows locations sampled and sample sizes. A, April; J, January; O, October.

Main Article

References
  1. Grubaugh  ND, Hodcroft  EB, Fauver  JR, Phelan  AL, Cevik  M. Public health actions to control new SARS-CoV-2 variants. Cell. 2021;184:1127–32. DOIPubMedGoogle Scholar
  2. Lauring  AS, Hodcroft  EB. Genetic variants of SARS-CoV-2—what do they mean? JAMA. 2021;325:529–31. DOIPubMedGoogle Scholar
  3. Frampton  D, Rampling  T, Cross  A, Bailey  H, Heaney  J, Byott  M, et al. Genomic characteristics and clinical effect of the emergent SARS-CoV-2 B.1.1.7 lineage in London, UK: a whole-genome sequencing and hospital-based cohort study. Lancet Infect Dis. 2021;21:1246–56. DOIPubMedGoogle Scholar
  4. Kidd  M, Richter  A, Best  A, Cumley  N, Mirza  J, Percival  B, et al. S-variant SARS-CoV-2 lineage B1.1.7 is associated with significantly higher viral load in samples tested by TaqPath polymerase chain reaction. J Infect Dis. 2021;223:1666–70. DOIPubMedGoogle Scholar
  5. Planas  D, Bruel  T, Grzelak  L, Guivel-Benhassine  F, Staropoli  I, Porrot  F, et al. Sensitivity of infectious SARS-CoV-2 B.1.1.7 and B.1.351 variants to neutralizing antibodies. Nat Med. 2021;27:917–24. DOIPubMedGoogle Scholar
  6. Tegally  H, Wilkinson  E, Giovanetti  M, Iranzadeh  A, Fonseca  V, Giandhari  J, et al. Detection of a SARS-CoV-2 variant of concern in South Africa. Nature. 2021;592:438–43. DOIPubMedGoogle Scholar
  7. West  AP Jr, Wertheim  JO, Wang  JC, Vasylyeva  TI, Havens  JL, Chowdhury  MA, et al. Detection and characterization of the SARS-CoV-2 lineage B.1.526 in New York. Nat Commun. 2021;12:4886. DOIPubMedGoogle Scholar
  8. World Health Organization. Epidemiological update: variants of SARS-CoV-2 in the Americas. 2021 Mar [cited 2021 Dec 9]. https://iris.paho.org/handle/10665.2/53382
  9. Thompson  CN, Hughes  S, Ngai  S, Baumgartner  J, Wang  JC, McGibbon  E, et al.; PhD1. PhD1. PhD1. Rapid emergence and epidemiologic characteristics of the SARS-CoV-2 B.1.526 variant—New York City, New York, January 1–April 5, 2021. MMWR Morb Mortal Wkly Rep. 2021;70:712–6. DOIPubMedGoogle Scholar
  10. Annavajhala  MK, Mohri  H, Wang  P, Nair  M, Zucker  JE, Sheng  Z, et al. Emergence and expansion of SARS-CoV-2 B.1.526 after identification in New York. Nature. 2021;597:703–8. DOIPubMedGoogle Scholar
  11. Alpert  T, Brito  AF, Lasek-Nesselquist  E, Rothman  J, Valesano  AL, MacKay  MJ, et al. Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States. Cell. 2021;184:2595–2604.e13. DOIPubMedGoogle Scholar
  12. Jung  I, Kulldorff  M, Richard  OJ. A spatial scan statistic for multinomial data. Stat Med. 2010;29:1910–8. DOIPubMedGoogle Scholar
  13. Kulldorff  M. Software for the spatial and space-time scan statistics. 2018 [2021 Dec 9]. http://www.satscan.org
  14. Desjardins  MR, Hohl  A, Delmelle  EM. Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters. Appl Geogr. 2020;118:102202. DOIPubMedGoogle Scholar
  15. Iyengar  VS. Space-time clusters with flexible shapes. MMWR Suppl. 2005;54:71–6.PubMedGoogle Scholar
  16. Takahashi  K, Kulldorff  M, Tango  T, Yih  K. A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring. Int J Health Geogr. 2008;7:14. DOIPubMedGoogle Scholar
  17. Shepard  D. A two-dimensional interpolation function for irregularly-spaced data. 1968 Jan 1 [cited 2021 Jun 8]. http://portal.acm.org/citation.cfm?doid=800186.810616
  18. Rogerson  PA, Plane  DA. Geographical analysis of population: with applications to planning and business. International edition. Hoboken (New Jersey): John Wiley and Sons Ltd; 1994.
  19. Katoh  K, Standley  DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80. DOIPubMedGoogle Scholar
  20. Nguyen  L-T, Schmidt  HA, von Haeseler  A, Minh  BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74. DOIPubMedGoogle Scholar
  21. Minh  BQ, Nguyen  MAT, von Haeseler  A. Ultrafast approximation for phylogenetic bootstrap. Mol Biol Evol. 2013;30:1188–95. DOIPubMedGoogle Scholar
  22. Sagulenko  P, Puller  V, Neher  RA. TreeTime: Maximum-likelihood phylodynamic analysis. Virus Evol. 2018;4:vex042. DOIPubMedGoogle Scholar
  23. Bouckaert  R, Vaughan  TG, Barido-Sottani  J, Duchêne  S, Fourment  M, Gavryushkina  A, et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLOS Comput Biol. 2019;15:e1006650. DOIPubMedGoogle Scholar
  24. Rambaut  A, Drummond  AJ, Xie  D, Baele  G, Suchard  MA. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Syst Biol. 2018;67:901–4. DOIPubMedGoogle Scholar
  25. Yu  G, Smith  DK, Zhu  H, Guan  Y, Lam  TT-Y. ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol. 2017;8:28–36. DOIGoogle Scholar
  26. Neher  R. The virus is under increasing selection pressure. Max-Planck-Gesellschaft. 2021 [cited 2021 Aug 10]. https://www.mpg.de/16371358/coronavirus-variants
  27. Campbell  F, Archer  B, Laurenson-Schafer  H, Jinnai  Y, Konings  F, Batra  N, et al. Increased transmissibility and global spread of SARS-CoV-2 variants of concern as at June 2021. Euro Surveill. 2021;26:2100509. DOIPubMedGoogle Scholar

Main Article

1These authors contributed equally to this article.

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Page updated: February 21, 2022
Page reviewed: February 21, 2022
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