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1.
Smruthi Karthikeyan; Joshua I Levy; Peter De Hoff; Greg Humphrey; Amanda Birmingham; Kristen Jepsen; Sawyer Farmer; Helena M. Tubb; Tommy Valles; Caitlin E Tribelhorn; Rebecca Tsai; Stefan Aigner; Shashank Sathe; Niema Moshiri; Benjamin Henson; Abbas Hakim; Nathan A Baer; Tom Barber; Pedro Belda-Ferre; Marisol Chacon; Willi Cheung; Evelyn S Crescini; Emily R Eisner; Alma L Lastrella; Elijah S Lawrence; Clarisse A Marotz; Toan T Ngo; Tyler Ostrander; Ashley Plascencia; Rodolfo A Salido; Phoebe Seaver; Elizabeth W Smoot; Daniel McDonald; Robert M Neuhard; Angela L Scioscia; Alysson M. Satterlund; Elizabeth H Simmons; Dismas B. Abelman; David Brenner; Judith Carbone Bruner; Anne Buckley; Michael Ellison; Jeffrey Gattas; Steven L Gonias; Matt Hale; Faith Kirkham Hawkins; Lydia Ikeda; Hemlata Jhaveri; Ted Johnson; Vince Kellen; Brendan Kremer; Gary C. Matthews; Ronald McLawhon; Pierre Ouillet; Daniel Park; Allorah Pradenas; Sharon Reed; Lindsay Riggs; Alison M. Sanders; Bradley Sollenberger; Angela Song; Benjamin White; Terri Winbush; Christine M Aceves; Catelyn Anderson; Karthik Gangavarapu; Emory Hufbauer; Ezra Kurzban; Justin Lee; Nathaniel L Matteson; Edyth Parker; Sarah A Perkins; Karthik S Ramesh; Refugio Robles-Sikisaka; Madison A Schwab; Emily Spencer; Shirlee Wohl; Laura Nicholson; Ian H Mchardy; David P Dimmock; Charlotte A Hobbs; Omid Bakhtar; Aaron Harding; Art Mendoza; Alexandre Bolze; David Becker; Elizabeth T Cirulli; Magnus Isaksson; Kelly M Schiabor Barrett; Nicole L Washington; John D Malone; Ashleigh Murphy Schafer; Nikos Gurfield; Sarah Stous; Rebecca Fielding-Miller; Tommi Gaines; Richard Garfein; Cheryl A. M. Anderson; Natasha K. Martin; Robert T Schooley; Brett Austin; Duncan R. MacCannell; Stephen F Kingsmore; William Lee; Seema Shah; Eric McDonald; Alexander T. Yu; Mark Zeller; Kathleen M Fisch; Christopher A. Longhurst; Patty Maysent; David Pride; Pradeep K. Khosla; Louise C Laurent; Gene W Yeo; Kristian G Andersen; Rob Knight.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21268143

RESUMO

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21251159

RESUMO

As of January of 2021, the highly transmissible B.1.1.7 variant of SARS-CoV-2, which was first identified in the United Kingdom (U.K.), has gained a strong foothold across the world. Because of the sudden and rapid rise of B.1.1.7, we investigated the prevalence and growth dynamics of this variant in the United States (U.S.), tracking it back to its early emergence and onward local transmission. We found that the RT-qPCR testing anomaly of S gene target failure (SGTF), first observed in the U.K., was a reliable proxy for B.1.1.7 detection. We sequenced 212 B.1.1.7 SARS-CoV-2 genomes collected from testing facilities in the U.S. from December 2020 to January 2021. We found that while the fraction of B.1.1.7 among SGTF samples varied by state, detection of the variant increased at a logistic rate similar to those observed elsewhere, with a doubling rate of a little over a week and an increased transmission rate of 35-45%. By performing time-aware Bayesian phylodynamic analyses, we revealed several independent introductions of B.1.1.7 into the U.S. as early as late November 2020, with onward community transmission enabling the variant to spread to at least 30 states as of January 2021. Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

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