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Uncertainty quantification in Covid-19 spread: Lockdown effects
We develop a Bayesian inference framework to quantify uncertainties in epidemiological models. We use SEIJR and SIJR models involving populations of susceptible, exposed, infective, diagnosed, dead and recovered individuals to infer from Covid-19 data rate constants, as well as their variations in r...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Published by Elsevier B.V.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897887/ https://www.ncbi.nlm.nih.gov/pubmed/35280115 http://dx.doi.org/10.1016/j.rinp.2022.105375 |