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基于不确定性和自相关函数的改进型易感-感染-易感传染病方程。

Improved susceptible-infectious-susceptible epidemic equations based on uncertainties and autocorrelation functions.

作者信息

Nakamura Gilberto M, Cardoso George C, Martinez Alexandre S

机构信息

Université Paris-Saclay, CNRS/IN2P3, and Université de Paris, IJCLab, 91405 Orsay, France.

Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP), Universidade de São Paulo (USP), Ribeirão Preto 14040-901, Brazil.

出版信息

R Soc Open Sci. 2020 Feb 19;7(2):191504. doi: 10.1098/rsos.191504. eCollection 2020 Feb.

Abstract

Compartmental equations are primary tools in the study of disease spreading processes. They provide accurate predictions for large populations but poor results whenever the integer nature of the number of agents is evident. In the latter instance, uncertainties are relevant factors for pathogen transmission. Starting from the agent-based approach, we investigate the role of uncertainties and autocorrelation functions in the susceptible-infectious-susceptible (SIS) epidemic model, including their relationship with epidemiological variables. We find new differential equations that take uncertainties into account. The findings provide improved equations, offering new insights on disease spreading processes.

摘要

compartmental方程是研究疾病传播过程的主要工具。它们能对大量人群做出准确预测,但只要个体数量的整数性质明显,结果就很差。在后一种情况下,不确定性是病原体传播的相关因素。从基于个体的方法出发,我们研究了不确定性和自相关函数在易感-感染-易感(SIS)流行病模型中的作用,包括它们与流行病学变量的关系。我们发现了考虑不确定性的新微分方程。这些发现提供了改进的方程,为疾病传播过程提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0e0/7062106/cedbace574e8/rsos191504-g1.jpg

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