PropertyValue
?:abstract
  • Synergistic effects of bacteria on viral stability and transmission are widely documented but remain unclear in the context of SARS-CoV-2. We collected 972 samples from hospitalized patients with coronavirus disease 2019 (COVID-19), their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and contextualized the massive microbial diversity in this dataset through meta-analysis of over 20,000 samples. Sixteen percent of surfaces from COVID-19 patient rooms were positive, with the highest prevalence in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples increasingly resembled the patient microbiome over time, SARS-CoV-2 was detected less there (11%). Despite viral surface contamination in almost all patient rooms, no health care workers contracted the disease, suggesting that personal protective equipment was effective in preventing transmissions. SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity across human and surface samples, and higher biomass in floor samples. 16S microbial community profiles allowed for high SARS-CoV-2 classifier accuracy in not only nares, but also forehead, stool, and floor samples. Across distinct microbial profiles, a single amplicon sequence variant from the genus Rothia was highly predictive of SARS-CoV-2 across sample types and had higher prevalence in positive surface and human samples, even compared to samples from patients in another intensive care unit prior to the COVID-19 pandemic. These results suggest that bacterial communities may contribute to viral prevalence both in the host and hospital environment.
is ?:annotates of
?:creator
?:doi
?:doi
  • 10.1101/2020.11.19.20234229
?:journal
  • medRxiv
?:license
  • cc-by
?:pdf_json_files
  • document_parses/pdf_json/90dab8695bccacd9105bb264151b0140e012c236.json; document_parses/pdf_json/716eddb3dd27c9039aefb0ed2410d21d95b43634.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7685343.xml.json
?:pmcid
?:pmid
?:pmid
  • 33236030.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • MedRxiv; Medline; PMC; WHO
?:title
  • Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment
?:type
?:year
  • 2020-11-22

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