Wednesday, August 26, 2020

Very Brief Blog: Genomic Analysis of COVID and Boston Epidemiology

 Even though they are mostly (or all) clinically silent, there is a tremendous diversity of the SARS-CoV-2 virus at the point mutation level.   With the ready availability of NGS methods, this gives epidemiologists a very powerful tool for tracking the interlaced nature of community and workplace spread of virus.   Of course, this is difficulty if there are far too few people involved in tracking and they're using golf pencils on clipboards.   However, use of big data with SARS-CoV-2 genomics is at least possible.  I've harbored the hope that genomics and insightful big data analysis might also compensate for some of our weaknesses in public health deployment. 

An article this week in MedCityNews providers a genomic analysis tied to the infamous Biogen meeting in Boston in February, and how it relates to the spread of virus in the Boston region.

  • See MedCityNews, August 26, here.
  • See MedRxiv preprint by Lemieux et al., here.

I've clipped the abstract below:

SARS-CoV-2 has caused a severe, ongoing outbreak of COVID-19 in Massachusetts with 111,070 confirmed cases and 8,433 deaths as of August 1, 2020. To investigate the introduction, spread, and epidemiology of COVID-19 in the Boston area, we sequenced and analyzed 772 complete SARS-CoV-2 genomes from the region, including nearly all confirmed cases within the first week of the epidemic and hundreds of cases from major outbreaks at a conference, a nursing facility, and among homeless shelter guests and staff. 
The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. 
One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission, including outbreaks in homeless populations, and was exported to several other domestic and international sites. The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into MA early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data.