The emergence of SARS-CoV-2 in Europe and the US

Worobey, Michael; Pekar, Jonathan E.; Larsen, Brendan B.; Nelson, Martha I.; Hill, Verity; Joy, Jeffrey B.; Rambaut, Andrew; Suchard, Marc A.; Wertheim, Joel O.; Lemey, Philippe

doi:10.1101/2020.05.21.109322

Cited by 66 publications

(96 citation statements)

References 29 publications

(28 reference statements)

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“…The presence of the γ and δ variants in and around Europe by pandemic day 59 and their subsequent appearance in eastern North America (first detected on pandemic day 66) is consistent with the suggestion that, early on, coronaviruses from Europe seeded infections in eastern North America 36 . As for the Asian seeding of infections in western North America 37 , μ and μα originated in China and dominated in the earliest phases of the pandemic. However, these mutants were replaced a few weeks later by μν genomes that were first isolated on pandemic day 59 in western North America and those found in eastern North America (μαβγδ genomes) ( Fig.…”

Section: A Mutational History Of Sars-cov-2mentioning

confidence: 99%

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Kumar

Tao

Weaver

et al. 2020

Preprint

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Severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, was quickly identified as the cause of COVID-19 disease soon after its earliest reports. The knowledge of the contemporary evolution of SARS-CoV-2 is urgently needed not only for a retrospective on how, when, and why COVID-19 has emerged and spread, but also for creating remedies through efforts of science, technology, medicine, and public policy. Global sequencing of thousands of genomes has revealed many common genetic variants, which are the key to unraveling the early evolutionary history of SARS-CoV-2 and tracking its global spread over time. However, our knowledge of fundamental events in the evolution and spread of this coronavirus remains grossly incomplete and highly uncertain. Here, we present the heretofore cryptic mutational history, phylogeny, and dynamics of SARS-CoV-2 from an analysis of tens of thousands of high-quality genomes. The reconstructed mutational progression is highly concordant with the timing of coronavirus sampling dates. It predicts the progenitor genome whose earliest offspring without any non-synonymous mutations were still spreading worldwide months after the report of COVID-19. Over time, mutations gave rise to seven major lineages that spread episodically, some of which arose in Europe and North America after the genesis of the ancestral lineages in China. Mutational barcoding establishes that North American coronaviruses harbor very different genome signatures than coronaviruses prevalent in Europe and Asia that have converged over time. These spatiotemporal patterns continue to evolve as the pandemic progresses and can be viewed live online.

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Section: A Mutational History Of Sars-cov-2mentioning

confidence: 99%

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Kumar

Tao

Weaver

et al. 2020

Preprint

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“…The SNV A23403G (resulting in D614G variant in spike protein) is a major viral mutation that has been observed in the major European countries of Italy, Spain, France, as well as Middle Eastern regions of Turkey and Israel [16,[64][65][66]. Some studies suggest that this D614G variant of the S spike protein provides greater survival and transmission ability to the virus, however there need to be additional studies conducted to confirm these claims [64].…”

Section: Subtypes Including the A23403g/d614g Spike Protein Variantmentioning

confidence: 99%

Genetic Grouping of SARS-CoV-2 Coronavirus Sequences using Informative Subtype Markers for Pandemic Spread Visualization

Zhao

Sokhansanj

Malhotra

et al. 2020

Preprint

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We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disease spread. Subtyping thereby advances the development of effective containment strategies and, potentially, therapeutic and vaccine strategies. However, identifying viral subtypes in real-time is challenging: SARS-CoV-2 is a novel virus, and the pandemic is rapidly expanding. Viral subtypes may be difficult to detect due to rapid evolution; founder effects are more significant than selection pressure; and the clustering threshold for subtyping is not standardized. We propose to identify mutational signatures of available SARS-CoV-2 sequences using a population-based approach: an entropy measure followed by frequency analysis. These signatures, Informative Subtype Markers (ISMs), define a compact set of nucleotide sites that characterize the most variable (and thus most informative) positions in the viral genomes sequenced from different individuals. Through ISM compression, we find that certain distant nucleotide variants covary, including non-coding and ORF1ab sites covarying with the D614G spike protein mutation which has become increasingly prevalent as the pandemic has spread. ISMs are also useful for downstream analyses, such as spatiotemporal visualization of viral dynamics. By analyzing sequence data available in the GISAID database, we validate the utility of ISM-based subtyping by comparing spatiotemporal analyses using ISMs to epidemiological studies of viral transmission in Asia, Europe, and the United States. In addition, we show the relationship of ISMs to phylogenetic reconstructions of SARS-CoV-2 evolution, and therefore, ISMs can play an important complementary role to phylogenetic tree-based analysis, such as is done in the Nextstrain project. The developed pipeline dynamically generates ISMs for newly added SARS-CoV-2 sequences and updates the visualization of pandemic spatiotemporal dynamics, and is available on Github at https://github.com/EESI/ISM and via an interactive website at https://covid19-ism.coe.drexel.edu/.

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“…Worobey et al (2020) provide genome-based evidence that later early cases were not part of the main epidemics in Washington and Italy.21 Data inaccuracies may, of course, also be relevant here, so it is possible that the model predictions are closer to the truth than are the data.…”

mentioning

confidence: 91%

“…Recent papers in epidemiology are also broadly related in that their observations motivate examining heterogeneous transmission. Worobey et al (2020) concludes that early imported cases formerly thought to have triggered epidemics in Washington and Italy appear to not be related to the subsequent epidemics there, suggesting that the communities in which they occurred had low enough R 0 so that the epidemics they started died out. Miller et al…”

Section: Introductionmentioning

confidence: 98%

Implications of Heterogeneous SIR Models for Analyses of COVID-19

Ellison

2020

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This paper provides a quick survey of results on the classic SIR model and variants allowing for heterogeneity in contact rates. It notes that calibrating the classic model to data generated by a heterogeneous model can lead to forecasts that are biased in several ways and to understatement of the forecast uncertainty. Among the biases are that we may underestimate how quickly herd immunity might be reached, underestimate differences across regions, and have biased estimates of the impact of endogenous and policy-driven social distancing.

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The emergence of SARS-CoV-2 in Europe and the US

Cited by 66 publications

References 29 publications

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Genetic Grouping of SARS-CoV-2 Coronavirus Sequences using Informative Subtype Markers for Pandemic Spread Visualization

Implications of Heterogeneous SIR Models for Analyses of COVID-19

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