The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence
Open accessAbstract
The northern state of Amazonas is among the regions in Brazil most heavily affected by the COVID-19 epidemic and has experienced two exponentially growing waves, in early and late 2020. Through a genomic epidemiology study based on 250 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from different Amazonas municipalities sampled between March 2020 and January 2021, we reveal that the first exponential growth phase was driven mostly by the dissemination of lineage B.1.195, which was gradually replaced by lineage B.1.1.28 between May and June 2020. The second wave coincides with the emergence of the variant of concern (VOC) P.1, which evolved from a local B.1.1.28 clade in late November 2020 and replaced the parental lineage in <2 months. Our findings support the conclusion that successive lineage replacements in Amazonas were driven by a complex combination of variable levels of social distancing measures and the emergence of a more transmissible VOC P.1 virus. These data provide insights to understanding the mechanisms underlying the COVID-19 epidemic waves and the risk of dissemination of SARS-CoV-2 VOC P.1 in Brazil and, potentially, worldwide. Analysis of circulating SARS-CoV-2 viruses during the first and second waves of COVID-19 in Amazonas, Brazil, shows successive lineage replacements led to predominance of the variant of concern P.1 and are associated with variable levels of social distancing.
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
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
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
IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies
Nguyen, L.-T., Schmidt, H. A., von Haeseler, A., & Minh, B. Q. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msu300 · Cited by 26,046
ModelFinder: fast model selection for accurate phylogenetic estimates
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A., & Jermiin, L. S. (2017) · Nature Methods · doi:10.1038/nmeth.4285 · Cited by 18,449
The variant call format and VCFtools
Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr330 · Cited by 16,200
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
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis
Bouckaert, R., Vaughan, T. G., Barido-Sottani, J., Duchêne, S., Fourment, M., Gavryushkina, A., Heled, J., Jones, G., Kühnert, D., De Maio, N., et al. (2019) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006650 · Cited by 4,556
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10
Suchard, M. A., Lemey, P., Baele, G., Ayres, D. L., Drummond, A. J., & Rambaut, A. (2018) · Virus Evolution · doi:10.1093/ve/vey016 · Cited by 3,792
Cited by
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Faria, N. R., Mellan, T. A., Whittaker, C., Claro, I. M., Candido, D. D. S., Mishra, S., Crispim, M. A. E., Sales, F. C. S., Hawryluk, I., McCrone, J. T., et al. (2021) · Science · doi:10.1126/science.abh2644 · Cited by 1,461
Self-citationRanzani, O. T., Hitchings, M. D. T., Dorion, M., D’Agostini, T. L., de Paula, R. C., de Paula, O. F. P., Villela, E. F. D. M., Torres, M. S. S., de Oliveira, S. B., Schulz, W., et al. (2021) · BMJ · doi:10.1136/bmj.n2015 · Cited by 348
SARS-CoV-2 Variants of Concern
Choi, J. Y., & Smith, D. M. (2021) · Yonsei Medical Journal · doi:10.3349/ymj.2021.62.11.961 · Cited by 293
Global disparities in SARS-CoV-2 genomic surveillance
Brito, A. F., Semenova, E., Dudas, G., Hassler, G. W., Kalinich, C. C., Kraemer, M. U. G., Ho, J., Tegally, H., Githinji, G., Agoti, C. N., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33713-y · Cited by 284
Self-citationZhang, L., Cui, Z., Li, Q., Yu, Y., Wu, J., Nie, J., Ding, R., Wang, H., Zhang, Y., Liu, S., et al. (2021) · doi:10.21203/rs.3.rs-492659/v1 · Cited by 5
Metadata
- Authors
- Naveca, F. G., Nascimento, V., de Souza, V. C., Corado, A. D. L., Nascimento, F., Silva, G., Costa, Á., Duarte, D., Pessoa, K., Mejía, M., Brandão, M. J., Jesus, M., Gonçalves, L., da Costa, C. F., Sampaio, V., Barros, D., Silva, M., Mattos, T., Pontes, G., Abdalla, L., Santos, J. H., Arantes, I., Dezordi, F. Z., Siqueira, M. M., Wallau, G. L., Resende, P. C., Delatorre, E., Gräf, T., & Bello, G.
- Venue
- Nature Medicine
- Published
- 2021-05-25
- Volume
- 27
- Issue
- 7
- Pages
- 1230-1238
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3165658327
- Cited by
- 462
- References
- 49
- FWCI
- 31.54
- Type
- journal article
- Language
- en
- Open access
- green
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: COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence. https://app.cochat.ai/papers/10.1038/s41591-021-01378-7
- The paper
- Naveca, F. G., Nascimento, V., de Souza, V. C., Corado, A. D. L., Nascimento, F., Silva, G., Costa, Á., Duarte, D., Pessoa, K., Mejía, M., Brandão, M. J., Jesus, M., Gonçalves, L., da Costa, C. F., Sampaio, V., Barros, D., Silva, M., Mattos, T., Pontes, G., . . . Bello, G. (2021). COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence. Nature Medicine. https://doi.org/10.1038/s41591-021-01378-7
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.