Probabilistic predictions of SIS epidemics on networks based on population-level observations.

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作者： T,Zerenner ^[1] ; F,Di Lauro ^[2] ; M,Dashti ^[3] ; L,Berthouze ^[4] ; I Z,Kiss ^[5]

作者单位： Department of Mathematics, University of Sussex, Falmer, Brighton, BN1 9QH, UK. Electronic address: t.zerenner@sussex.ac.uk. ^[1] Department of Mathematics, University of Sussex, Falmer, Brighton, BN1 9QH, UK; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7FL, UK. ^[2] Department of Mathematics, University of Sussex, Falmer, Brighton, BN1 9QH, UK. ^[3] Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QH, UK. ^[4] Department of Mathematics, University of Sussex, Falmer, Brighton, BN1 9QH, UK. Electronic address: i.z.kiss@sussex.ac.uk. ^[5]

关键词 Bayesian inference Birth-and-death processes Epidemics Network inference Uncertainty quantification

主题词贝叶斯定理(Bayes Theorem);疾病易感性(Disease Susceptibility);疾病流行(Epidemics);人类(Humans);偏差(Uncertainty)

DOI 10.1016/j.mbs.2022.108854

PMID 35659615

发布时间 2022-07-26

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