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Manifesto for a post-pandemic modeling.

作者信息

Ausloos Marcel, Grech Dariusz, Di Matteo Tiziana, Kutner Ryszard, Schinckus Christophe, Stanley H Eugene

机构信息

School of Business, University of Leicester, Brookfield, Leicester LE2 1RQ, UK.

Department of Statistics and Econometrics, Bucharest University of Economic Studies, Calea Dorobantilor 15-17, Bucharest, 010552 Sector 1, Romania.

出版信息

Physica A. 2020 Dec 1;559:125086. doi: 10.1016/j.physa.2020.125086. Epub 2020 Aug 13.

DOI:10.1016/j.physa.2020.125086
PMID:32836719
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7425778/
Abstract
摘要

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本文引用的文献

1
Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China.考虑未检测到感染情况的2019冠状病毒病(COVID-19)传播的数学模型。以中国为例。
Commun Nonlinear Sci Numer Simul. 2020 Sep;88:105303. doi: 10.1016/j.cnsns.2020.105303. Epub 2020 Apr 30.
2
Memory effects on epidemic evolution: The susceptible-infected-recovered epidemic model.记忆效应对传染病演化的影响:易感染者-感染者-恢复者传染病模型。
Phys Rev E. 2017 Feb;95(2-1):022409. doi: 10.1103/PhysRevE.95.022409. Epub 2017 Feb 21.