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The origin and early spread of SARS-CoV-2 in Europe.

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TLDR
In this paper, a phylodynamic model with geographic structure was used to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures and found that the predominant lineage spreading in Europe during this time has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei, China or Germany.
Abstract
The investigation of migratory patterns during the SARS-CoV-2 pandemic before spring 2020 border closures in Europe is a crucial first step toward an in-depth evaluation of border closure policies. Here we analyze viral genome sequences using a phylodynamic model with geographic structure to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures. Based on SARS-CoV-2 genomes, we reconstruct a partial transmission tree of the early pandemic and coinfer the geographic location of ancestral lineages as well as the number of migration events into and between European regions. We find that the predominant lineage spreading in Europe during this time has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei, China or Germany. We do not find evidence for preferential migration paths from Hubei into different European regions or from each European region to the others. Sustained local transmission is first evident in Italy and then shortly thereafter in the other European regions considered. Before the first border closures in Europe, we estimate that the rate of occurrence of new cases from within-country transmission was within the bounds of the estimated rate of new cases from migration. In summary, our analysis offers a view on the early state of the epidemic in Europe and on migration patterns of the virus before border closures. This information will enable further study of the necessity and timeliness of border closures.

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The Lancet Commission on lessons for the future from the COVID-19 pandemic

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Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic

TL;DR: In this paper , the authors describe how phylogenetic and phylodynamic methods provide insight into viral evolution, focusing on the SARS-CoV-2 pandemic, and summarize their contributions to our understanding of SARS transmission and control.
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SARS-CoV-2 transmission dynamics in Belarus revealed by genomic and incidence data analysis

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Analysis of SARS-CoV-2 Variants From 24,181 Patients Exemplifies the Role of Globalization and Zoonosis in Pandemics

TL;DR: In this paper , the authors compared the incidence curves of SARS-CoV-2-associated deaths in different countries and reported the classification of the first viral variants detected in the IHU Méditerranée Infection in Marseille, France.
References
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Journal ArticleDOI

A new coronavirus associated with human respiratory disease in China.

TL;DR: Phylogenetic and metagenomic analyses of the complete viral genome of a new coronavirus from the family Coronaviridae reveal that the virus is closely related to a group of SARS-like coronaviruses found in bats in China.
Journal ArticleDOI

Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7.

TL;DR: The software package Tracer is presented, for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference, which provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more.
Journal ArticleDOI

The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.

TL;DR: The results suggest that early detection, hand washing, self-isolation, and household quarantine will likely be more effective than travel restrictions at mitigating this pandemic, and sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
Journal ArticleDOI

The reproductive number of COVID-19 is higher compared to SARS coronavirus.

TL;DR: The authors' review found the average R0 for 2019-nCoV to be 3.28, which exceeds WHO estimates of 1.4 to 2.5, and is higher than expected.
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