Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info , a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

Regional connectivity drove bidirectional transmission of SARS-CoV-2 in the Middle East during travel restrictions

Regional connectivity and land 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. 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 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 in the early pandemic to more regional seeding for the travel restrictions period. We show that land travel, particularly freight transport, drove introduction risk during the travel restrictions period. High regional connectivity and land travel also drove Jordan's export risk. Our findings emphasize regional connectedness and land travel as drivers of transmission in the Middle East.

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

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 and/or sequencing capacity, which can also introduce biases^1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing^4,5. 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 developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified 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.

Emerging SARS-CoV-2 variants of concern were detected early and multiple cases of virus spread not captured by clinical genomic surveillance were identified using high-resolution wastewater and clinical sequencing.

Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations

The emergence of SARS-CoV-2 variants of concern has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the interpretable and opinionated visualizations in the variant and location focussed reports available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data, and the server infrastructure that enables widespread data dissemination via a high performance API that can be accessed using an R package. We present a case study that illustrates how outbreak.info can be used for genomic surveillance and as a hypothesis generation tool to understand the ongoing pandemic at varying geographic and temporal scales. With an emphasis on scalability, interactivity, interpretability, and reusability, outbreak.info provides a template to enable genomic surveillance at a global and localized scale.

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission

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.

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission

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.

Emergence of an early SARS-CoV-2 epidemic in the United States

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate 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 had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early 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 the festival dramatically accelerated transmission. 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 epidemics.

Emergence of an early SARS-CoV-2 epidemic in the United States

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.

Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework

Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.

Travel Surveillance and Genomics Uncover a Hidden Zika Outbreak during the Waning Epidemic

The Zika epidemic in the Americas has challenged surveillance and control. As the epidemic appears to be waning, it is unclear whether transmission is still ongoing, which is exacerbated by discrepancies in reporting. To uncover locations with lingering outbreaks, we investigated travel-associated Zika cases to identify transmission not captured by reporting. We uncovered an unreported outbreak in Cuba during 2017, a year after peak transmission in neighboring islands. By sequencing Zika virus, we show that the establishment of the virus was delayed by a year and that the ensuing outbreak was sparked by long-lived lineages of Zika virus from other Caribbean islands. Our data suggest that, although mosquito control in Cuba may initially have been effective at mitigating Zika virus transmission, such measures need to be maintained to be effective. Our study highlights how Zika virus may still be "silently" spreading and provides a framework for understanding outbreak dynamics. VIDEO ABSTRACT.

An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

Structure-based assessment of protein-protein interactions and accessibility of protein IX in adenoviruses with implications for antigen display

The exterior minor protein IX of adenoviruses (AdVs) is a frequent target of attachment of antigens and the modified AdVs are being used as potent vaccine platforms. The organization of protein IX is disticntly different between human adenoviruses (HAdVs) and non-HAdVs. The analysis of solvent accessibility, based on the near atomic resolution structures, suggests that the C-terminal residues of IX are more accessible in non-HAdVs (e.g., bovine adenovirus) than in HAdVs. Although the C-terminal fusions of IX are displayed on the capsid surface, they could disrupt the formation of tetrameric coiled-coils (4-HLXB) in HAdVs due to steric hinderance, thereby potentially affecting the capsid stability. Importantly, the parallel-antiparallel arrangement of helices seen in the 4-HLXB is not condusive for IX C-terminal fusions in HAdVs. In contrast, the parallel trimeric C-terminal coiled-coils in non-HAdVs are unlikely to be affected by the attachment of antigens and more efficiently displayed on the AdV surface.