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Estimating infectiousness throughout SARS-CoV-2 infection course
Open accessAbstract
Correlates of infectiousness: The role that individuals with asymptomatic or mildly symptomatic severe acute respiratory syndrome coronavirus 2 have in transmission of the virus is not well understood. Jones et al. investigated viral load in patients, comparing those showing few, if any, symptoms with hospitalized cases. Approximately 400,000 individuals, mostly from Berlin, were tested from February 2020 to March 2021 and about 6% tested positive. Of the 25,381 positive subjects, about 8% showed very high viral loads. People became infectious within 2 days of infection, and in hospitalized individuals, about 4 days elapsed from the start of virus shedding to the time of peak viral load, which occurred 1 to 3 days before the onset of symptoms. Overall, viral load was highly variable, but was about 10-fold higher in persons infected with the B.1.1.7 variant. Children had slightly lower viral loads than adults, although this difference may not be clinically significant. Science , abi5273, this issue p. eabi5273
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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
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430
Self-citationEarly 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
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
Use of Ranks in One-Criterion Variance Analysis
Kruskal, W. H., & Wallis, W. A. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483441 · Cited by 13,912
brms : An R Package for Bayesian Multilevel Models Using Stan
Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476 · cited 1×
“We estimated associations of viral load and age with a thin-plate spline regression using the brms package (58, 59) in R (60).”
MethodStan : A Probabilistic Programming Language
Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i01 · Cited by 7,754
Virological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661 · cited 5×
“0, in accordance with our SARS-CoV-2 assay limit of detection and sample dilution (19).”
BackgroundMethodInfluentialSelf-citationLi, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020) · Science · doi:10.1126/science.abb3221 · Cited by 3,633
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An evidence review of face masks against COVID-19
Howard, J., Huang, A., Li, Z., Tufekci, Z., Zdimal, V., van der Westhuizen, H.-M., von Delft, A., Price, A., Fridman, L., Tang, L.-H., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2014564118 · Cited by 1,529
Lamers, M. M., & Haagmans, B. L. (2022) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00713-0 · Cited by 983
The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19
Consiglio, C. R., Cotugno, N., Sardh, F., Pou, C., Amodio, D., Rodriguez, L., Tan, Z., Zicari, S., Ruggiero, A., Pascucci, G. R., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.016 · Cited by 919
Miller, S. L., Nazaroff, W. W., Jimenez, J. L., Boerstra, A., Buonanno, G., Dancer, S. J., Kurnitski, J., Marr, L. C., Morawska, L., & Noakes, C. (2021) · Indoor Air · doi:10.1111/ina.12751 · Cited by 734
SARS-CoV-2 detection, viral load and infectivity over the course of an infection
Walsh, K. A., Jordan, K., Clyne, B., Rohde, D., Drummond, L., Byrne, P., Ahern, S., Carty, P. G., O'Brien, K. K., O'Murchu, E., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.06.067 · Cited by 608
Metadata
- Authors
- Jones, T. C., Biele, G., Mühlemann, B., Veith, T., Schneider, J., Beheim-Schwarzbach, J., Bleicker, T., Tesch, J., Schmidt, M. L., Sander, L. E., Kurth, F., Menzel, P., Schwarzer, R., Zuchowski, M., Hofmann, J., Krumbholz, A., Stein, A., Edelmann, A., Corman, V. M., & Drosten, C.
- Venue
- Science
- Published
- 2021-07-09
- Volume
- 373
- Issue
- 6551
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W3164220019
- Cited by
- 740
- References
- 27
- FWCI
- 40.28
- Type
- journal article
- Language
- en
- Open access
- hybrid
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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.