Dynamic heterogeneity in COVID-19: Insights from a mathematical model
- DOI
- 10.1371/journal.pone.0301780
- Published
- 2024-05-31
- Container
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0301780,
title = {Dynamic heterogeneity in COVID-19: Insights from a mathematical model},
author = {Chrysovalantis Voutouri and C. Corey Hardin and Vivek Naranbhai and Mohammad R. Nikmaneshi and Melin J. Khandekar and Justin F. Gainor and Lance L. Munn and Rakesh K. Jain and Triantafyllos Stylianopoulos},
year = {2024},
journal = {PLOS ONE},
doi = {10.1371/journal.pone.0301780},
url = {https://doi.org/10.1371/journal.pone.0301780}
}RIS
TY - JOUR TI - Dynamic heterogeneity in COVID-19: Insights from a mathematical model AU - Chrysovalantis Voutouri AU - C. Corey Hardin AU - Vivek Naranbhai AU - Mohammad R. Nikmaneshi AU - Melin J. Khandekar AU - Justin F. Gainor AU - Lance L. Munn AU - Rakesh K. Jain AU - Triantafyllos Stylianopoulos PY - 2024 JO - PLOS ONE DO - 10.1371/journal.pone.0301780 UR - https://doi.org/10.1371/journal.pone.0301780 ER -
APA
Voutouri, C., Hardin, C. C., Naranbhai, V., Nikmaneshi, M. R., Khandekar, M. J., Gainor, J. F., Munn, L. L., Jain, R. K., & Stylianopoulos, T. (2024). Dynamic heterogeneity in COVID-19: Insights from a mathematical model. PLOS ONE. https://doi.org/10.1371/journal.pone.0301780
Source records
- crossref · retrieved 2026-09-26T20:34:17.572Z