Research Article

Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events

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Science  05 Feb 2021:
Vol. 371, Issue 6529, eabe3261
DOI: 10.1126/science.abe3261

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  • Superspreading: The engine of the SARS-CoV-2 pandemic
    • Antonio Salas, Professor at the USC, Spain, INCIFOR, Facultade de Medicina (USC) and GenPoB (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
    • Other Contributors:
      • Xabier Bello, PhD student, INCIFOR, Facultade de Medicina (USC) and GenPoB (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
      • Jacobo Pardo-Seco, PhD, INCIFOR, Facultade de Medicina (USC) and GenPoB (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
      • Federico Martinon-Torres, MD, PhD, Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico (USC - SERGAS) Galicia, Spain
      • Alberto Gomez-Carballa, PhD, INCIFOR, Facultade de Medicina (USC) and GenPoB (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain

    A growing amount of evidence point to a key role of superspreaders in the SARS-CoV-2 pandemic. A few superspreader events have been recently reported (e.g. Boston (USA), Spain); each of them has been responsible for important coronavirus local outbreaks. By examining >160K SARS-CoV-2 entire genomes from the GISAID database, we were able to detect hundreds of these events (including those already reported in the literature) that have occurred worldwide since the beginning of the pandemic.

    Dear Editor,
    We read with interest the article by Lemieux et al. on the impact of two SARS-CoV-2 superspreading events occurring in Boston (USA) in February 2020. Their contribution, based on the analysis of 772 complete SARS-CoV-2 genomes, indicates that a small number of patients were responsible for most of the contagions. In August 2020, based on the analysis of >4,700 complete coronavirus genomes, we reported ( variation patterns compatible with the existence of superspreaders on a worldwide scale. In fact, one of the two events reported was identified in our analysis (see #H32 in our Supplemental Table S4 [corresponding to strain A2a2c] in, together with at least a further 49 potential superspreaders (one of the most outstan...

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    Competing Interests: None declared.
  • RE: Boston Superspreader

    The in depth analysis of the events that contributed to the defusion and spread of the virus early in 2020 in Boston is informative and increases our knowledge of how this virus gains such a hold of the population in the U.S. However, the failure to identify the international business conference prevents readers from understanding how they maybe impacted by that event. The nursing homes were identified by location which gave local residents and understanding of the areas affected. If your not going to describe where the attendees to the conference came from and returned to, then the conference should have been identified at the very least.

    Competing Interests: None declared.
  • RE: Phylogenetic Analysis of COVID-19 Superspreading Events

    The impressive and exhaustive phylogenetic approach to the evolution of viral infectious disease, by a team of medical experts of the evolutionary relationships among biological entities that underlie COVID-19, should be read by medical specialists and non-specialists alike.

    A small number of introductions of the virus was found to have led to most cases, with varying transmission dynamics in superspreading events that provide the link between transmission from a single source or individual clusters and a wider spread of secondary infections in the community.

    With over 70 million cases of COVID-19 observed worldwide and over 16 million in the USA, and with deaths numbering 1.6 million and 300,000, respectively, as of 11 December 2020, superspreading events need to be controlled in order to mitigate the pandemic.

    The critical discussion of sampling, statistical techniques, data collection, ancestral state reconstruction, and analysis of superspreading events is impressive.

    It is worth noting that the numbers of cases linked to various superspreading events are based on estimates, so there are measurement errors in the generated data that might be accommodated in predicting the numbers of likely infections arising from future superspreading events.

    Competing Interests: None declared.

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