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1.
Preprint in English | medRxiv | ID: ppmedrxiv-22269922

ABSTRACT

Regional connectivity and land-based travel have been identified as important drivers of SARS-CoV-2 transmission. However, the generalizability of this finding is understudied outside of well-sampled, highly connected regions such as Europe. In this study, we investigated the relative contributions of regional and intercontinental connectivity to the source-sink dynamics of SARS-CoV-2 for Jordan and the wider Middle East. By integrating genomic, epidemiological and travel data we show that the source of introductions into Jordan was dynamic across 2020, shifting from intercontinental seeding from Europe in the early pandemic to more regional seeding for the period travel restrictions were in place. We show that land-based travel, particularly freight transport, drove introduction risk during the period of travel restrictions. Consistently, high regional connectivity and land-based travel also disproportionately drove Jordans export risk to other Middle Eastern countries. Our findings emphasize regional connectedness and land-based travel as drivers of viral transmission in the Middle East. This demonstrates that strategies aiming to stop or slow the spread of viral introductions (including new variants) with travel restrictions need to prioritize risk from land-based travel alongside intercontinental air travel to be effective. HighlightsO_LIRegional connectivity drove SARS-CoV-2 introduction risk in Jordan during the period travel restrictions were in place in genomic and travel data. C_LIO_LILand-based travel rather than air travel disproportionately drove introduction risk during travel restrictions. C_LIO_LIHigh regional connectivity disproportionately drove Jordans export risk, with significant contribution from land-based travel. C_LIO_LIRegional transmission dynamics were underestimated in genomic data due to unrepresentative sampling. C_LI

2.
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 in English | medRxiv | ID: ppmedrxiv-21268143

ABSTRACT

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.

3.
Preprint in English | medRxiv | ID: ppmedrxiv-21251235

ABSTRACT

The emergence of the early COVID-19 epidemic in the United States (U.S.) went largely undetected, due to a lack of adequate testing and mitigation efforts. The city of New Orleans, Louisiana experienced one of the earliest and fastest accelerating outbreaks, coinciding with the annual Mardi Gras festival, which went ahead without precautions. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large, crowded events may have accelerated early transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana initially had limited sequence diversity compared to other U.S. states, and that one successful introduction of SARS-CoV-2 led to almost all of the early SARS-CoV-2 transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras and that the festival dramatically accelerated transmission, eventually leading to secondary localized COVID-19 epidemics throughout the Southern U.S.. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate COVID-19 epidemics on a local and regional scale.

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