Global transmission network of SARS-CoV-2: from outbreak to pandemic

  1. Pavel Skums
  2. Alexander Kirpich
  3. Pelin Icer Baykal
  4. Alex Zelikovsky
  5. Gerardo Chowell

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Abstract

Background

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is straining health systems around the world. Although the Chinese government implemented a number of severe restrictions on people’s movement in an attempt to contain its local and international spread, the virus had already reached many areas of the world in part due to its potent transmissibility and the fact that a substantial fraction of infected individuals develop little or no symptoms at all. Following its emergence, the virus started to generate sustained transmission in neighboring countries in Asia, Western Europe, Australia, Canada and the United States, and finally in South America and Africa. As the virus continues its global spread, a clear and evidence-based understanding of properties and dynamics of the global transmission network of SARS-CoV-2 is essential to design and put in place efficient and globally coordinated interventions.

Methods

We employ molecular surveillance data of SARS-CoV-2 epidemics for inference and comprehensive analysis of its global transmission network before the pandemic declaration. Our goal was to characterize the spatial-temporal transmission pathways that led to the establishment of the pandemic. We exploited a network-based approach specifically tailored to emerging outbreak settings. Specifically, it traces the accumulation of mutations in viral genomic variants via mutation trees, which are then used to infer transmission networks, revealing an up-to-date picture of the spread of SARS-CoV-2 between and within countries and geographic regions.

Results and Conclusions

The analysis suggest multiple introductions of SARS-CoV-2 into the majority of world regions by means of heterogeneous transmission pathways. The transmission network is scale-free, with a few genomic variants responsible for the majority of possible transmissions. The network structure is in line with the available temporal information represented by sample collection times and suggest the expected sampling time difference of few days between potential transmission pairs. The inferred network structural properties, transmission clusters and pathways and virus introduction routes emphasize the extent of the global epidemiological linkage and demonstrate the importance of internationally coordinated public health measures.

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    SciScore for 10.1101/2020.03.22.20041145: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The remaining sequences were aligned to the consensus using MUSCLE [20] and trimmed to the same length, yielding n=319 aligned sequences of length 29772 base pairs (bp).
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)

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    Furthermore, the analysis is subject to the limitations associated with the nature of genomic data that include a small amount of cases in the beginning of the epidemics, underreporting and potential multiple sources of epidemic introductions. Further, the dataset available for this analysis is a convenience sample rather than a random sample within infected individuals, which results from the aggregation of data from different countries and sequencing labs and instruments. This is an inevitable consequence of sequencing data analysis since the procedure itself can be relatively expensive when implemented on a large scale [57, 55, 45], and the decision to sequence each particular case is largely done subjectively in each specific country and lab. In response to the rapidly growing number of cases of COVID-19 the authorities in different countries around the world have implemented unprecedentedly stringent travel and movement restrictions. Those measures were taken separately and independently country by country with different levels of escalation and at different times. In this context it is important to emphasize the importance of globally coordinated measures and collaborations that should be supported by timely and evidence-supported analysis of reliable epidemiological data of diverse nature. Automatic high-performance computing-based molecular near real-time surveillance systems such as Nextstrain [28], HIV-Trace [36] and GHOST [40] could be instrumental in such public h...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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  2. Version published to 10.1101/2020.03.22.20041145v1 on medRxiv