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Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models
We consider a mixture-theoretic continuum model of the spread of COVID-19 in Texas. The model consists of multiple coupled partial differential reaction–diffusion equations governing the evolution of susceptible, exposed, infectious, recovered, and deceased fractions of the total population in a giv...
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| 出版年: | Comput Mech |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Berlin Heidelberg
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7394277/ https://ncbi.nlm.nih.gov/pubmed/32836598 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00466-020-01889-z |
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