Evidence map›Paper›PMID 34494031›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification.

Jasmijn A Baaijens, Alessandro Zulli, Isabel M Ott, Mary E Petrone, Tara Alpert, Joseph R Fauver, Chaney C Kalinich, Chantal B F Vogels, Mallery I Breban, Claire Duvallet and 16 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Jasmijn A BaaijensDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Alessandro ZulliDepartment of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA.
Isabel M OttDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Mary E PetroneDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Tara AlpertDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Joseph R FauverDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Chaney C KalinichDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Chantal B F VogelsDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Mallery I BrebanDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Claire DuvalletBiobot Analytics, Inc., Cambridge, MA, USA.
Kyle McElroyBiobot Analytics, Inc., Cambridge, MA, USA.
Newsha GhaeliBiobot Analytics, Inc., Cambridge, MA, USA.
Maxim ImakaevBiobot Analytics, Inc., Cambridge, MA, USA.
Malaika Mckenzie-BennettGinkgo Bioworks, Inc., Boston, MA, USA.
Keith RobisonGinkgo Bioworks, Inc., Boston, MA, USA.
Alex PlocikGinkgo Bioworks, Inc., Boston, MA, USA.
Rebecca SchillingGinkgo Bioworks, Inc., Boston, MA, USA.
Martha PiersonGinkgo Bioworks, Inc., Boston, MA, USA.
Rebecca LittlefieldGinkgo Bioworks, Inc., Boston, MA, USA.
Michelle SpencerGinkgo Bioworks, Inc., Boston, MA, USA.
Birgitte B SimenGinkgo Bioworks, Inc., Boston, MA, USA.
Yale SARS-CoV-2 Genomic Surveillance Initiative
William P HanageCenter for Communicable Disease Dynamics and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Nathan D GrubaughDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Jordan PecciaDepartment of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA.
Michael BaymDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
NRSA Training CoreTL1TR001864 · NCATS · YALE UNIVERSITY · PI CANTLEY, LLOYD G, EDELMAN, E. JENNIFER · 2016 to 2025
$9.9M
Epidemiology of Infectious Diseases and BiodefenseT32AI007535 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI GRAD, YONATAN H, MURRAY, MEGAN B · 1998 to 2025
$4.8M
Evolutionary Tradeoffs in Antibiotic ResistanceR35GM133700 · NIGMS · HARVARD MEDICAL SCHOOL · PI BAYM, MICHAEL · 2019 to 2023
$2.4M
NCATS NIH HHS TL1 TR001864NCATS NIH HHS UL1 TR001863NIAID NIH HHS T32 AI007535NIGMS NIH HHS R35 GM133700NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.

Identifiers

PMID34494031
PMCPMC8423229

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.