Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model.
- DOI
- 10.1038/s41598-024-60060-3
- Published
- 2024 Apr 25
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-60060-3,
title = {Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model.},
author = {Glemain B and de Lamballerie X and Zins M and Severi G and Touvier M and Deleuze JF and SAPRIS-SERO study group and Lapidus N and Carrat F},
year = {2024},
journal = {Scientific reports},
doi = {10.1038/s41598-024-60060-3},
url = {https://doi.org/10.1038/s41598-024-60060-3}
}RIS
TY - JOUR TI - Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model. AU - Glemain B AU - de Lamballerie X AU - Zins M AU - Severi G AU - Touvier M AU - Deleuze JF AU - SAPRIS-SERO study group AU - Lapidus N AU - Carrat F PY - 2024 JO - Scientific reports DO - 10.1038/s41598-024-60060-3 UR - https://doi.org/10.1038/s41598-024-60060-3 ER -
APA
B, G., X, D. L., M, Z., G, S., M, T., JF, D., group, S. S., N, L., & F, C. (2024). Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model.. Scientific reports. https://doi.org/10.1038/s41598-024-60060-3
Source records
- pubmed · retrieved 2026-09-26T16:43:41.640Z