The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Transmission dynamics and evolutionary history of 2019‐nCoV
Open accessAbstract
To investigate the time origin, genetic diversity, and transmission dynamics of the recent 2019‐nCoV outbreak in China and beyond, a total of 32 genomes of virus strains sampled from China, Thailand, and the USA with sampling dates between 24 December 2019 and 23 January 2020 were analyzed. Phylogenetic, transmission network, and likelihood‐mapping analyses of the genome sequences were performed. On the basis of the likelihood‐mapping analysis, the increasing tree‐like signals (from 0% to 8.2%, 18.2%, and 25.4%) over time may be indicative of increasing genetic diversity of 2019‐nCoV in human hosts. We identified three phylogenetic clusters using the Bayesian inference framework and three transmission clusters using transmission network analysis, with only one cluster identified by both methods using the above genome sequences of 2019‐nCoV strains. The estimated mean evolutionary rate for 2019‐nCoV ranged from 1.7926 × 10−3 to 1.8266 × 10−3 substitutions per site per year. On the basis of our study, undertaking epidemiological investigations and genomic data surveillance could positively impact public health in terms of guiding prevention efforts to reduce 2019‐nCOV transmission in real‐time.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209
Guindon, S., Dufayard, J.-F., Lefort, V., Anisimova, M., Hordijk, W., & Gascuel, O. (2010) · Systematic Biology · doi:10.1093/sysbio/syq010 · Cited by 18,376
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Posterior summarization in Bayesian phylogenetics using tracer 1.7
Rambaut, A., Drummond, A. J., Xie, D., Baele, G., & Suchard, M. A. (2018) · Systematic Biology · doi:10.1093/sysbio/syy032 · Cited by 11,159
Identification of a novel coronavirus in patients with severe acute respiratory syndrome
Drosten, C., Günther, S., Preiser, W., van der Werf, S., Brodt, H.-R., Becker, S., Rabenau, H., Panning, M., Kolesnikova, L., Fouchier, R. A. M., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa030747 · Cited by 4,574
Data, disease and diplomacy: GISAID's innovative contribution to global health
Elbe, S., & Buckland‐Merrett, G. (2017) · Global Challenges · doi:10.1002/gch2.1018 · Cited by 1,928
Moderate mutation rate in the SARS coronavirus genome and its implications
Zhao, Z., Li, H., Wu, X., Zhong, Y., Zhang, K., Zhang, Y.-P., Boerwinkle, E., & Fu, Y.-X. (2004) · BMC Evolutionary Biology · doi:10.1186/1471-2148-4-21 · Cited by 286
Cited by
Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody
Pinto, D., Park, Y.-J., Beltramello, M., Walls, A. C., Tortorici, M. A., Bianchi, S., Jaconi, S., Culap, K., Zatta, F., De Marco, A., et al. (2020) · Nature · doi:10.1038/s41586-020-2349-y · Cited by 1,885
Structural and functional analysis of a potent sarbecovirus neutralizing antibody
Pinto, D., Park, Y.-J., Beltramello, M., Walls, A. C., Tortorici, M. A., Bianchi, S., Jaconi, S., Culap, K., Zatta, F., De Marco, A., et al. (2020) · doi:10.1101/2020.04.07.023903 · Cited by 1,752
Emergence of genomic diversity and recurrent mutations in SARS-CoV-2
van Dorp, L., Acman, M., Richard, D., Shaw, L. P., Ford, C. E., Ormond, L., Owen, C. J., Pang, J., Tan, C. C. S., Boshier, F. A. T., et al. (2020) · Infection, Genetics and Evolution · doi:10.1016/j.meegid.2020.104351 · Cited by 774
Thomson, E. C., Rosen, L. E., Shepherd, J. G., Spreafico, R., da Silva Filipe, A., Wojcechowskyj, J. A., Davis, C., Piccoli, L., Pascall, D. J., Dillen, J., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.037 · Cited by 606
Walls, A. C., Fiala, B., Schäfer, A., Wrenn, S., Pham, M. N., Murphy, M., Tse, L. V., Shehata, L., O’Connor, M. A., Chen, C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.043 · Cited by 532
Metadata
- Authors
- Li, X., Wang, W., Zhao, X., Zai, J., Zhao, Q., Li, Y., & Chaillon, A.
- Venue
- Journal of Medical Virology
- Publisher
- Wiley
- Published
- 2020-02-14
- Volume
- 92
- Issue
- 5
- Pages
- 501-511
- ISSN
- 0146-6615 (ISSN-L)
- 1096-9071
- OpenAlex
- W3004826757
- Cited by
- 321
- References
- 7
- FWCI
- 8.93
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Transmission dynamics and evolutionary history of 2019‐nCoV. https://app.cochat.ai/papers/10.1002/jmv.25701
- The paper
- Li, X., Wang, W., Zhao, X., Zai, J., Zhao, Q., Li, Y., & Chaillon, A. (2020). Transmission dynamics and evolutionary history of 2019‐nCoV. Journal of Medical Virology. https://doi.org/10.1002/jmv.25701
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.