当前位置: X-MOL 学术Expert Syst. Appl. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
#stayhome to contain Covid-19: Neuro-SIR - Neurodynamical epidemic modeling of infection patterns in social networks.
Expert Systems with Applications ( IF 7.5 ) Pub Date : 2020-09-03 , DOI: 10.1016/j.eswa.2020.113970
Ilias N Lymperopoulos 1
Affiliation  

An innovative neurodynamical model of epidemics in social networks – the Neuro-SIR – is introduced. Susceptible–Infected–Removed (SIR) epidemic processes are mechanistically modeled as analogous to the activity propagation in neuronal populations. The workings of infection transmission from individual to individual through a network of social contacts, is driven by the dynamics of the threshold mechanism of leaky integrate-and-fire neurons. Through this approach a dynamically evolving landscape of the susceptibility of a population to a disease is formed. In this context, epidemics with varying velocities and scales are triggered by a small fraction of infected individuals according to the configuration of various endogenous and exogenous factors representing the individuals’ vulnerability, the infectiousness of a pathogen, the density of a contact network, and environmental conditions. Adjustments in the length of immunity (if any) after recovery, enable the modeling of the Susceptible–Infected–Recovered–Susceptible (SIRS) process of recurrent epidemics. Neuro-SIR by supporting an impressive level of heterogeneities in the description of a population, contagiousness of a disease, and external factors, allows a more insightful investigation of epidemic spreading in comparison with existing approaches. Through simulation experiments with Neuro-SIR, we demonstrate the effectiveness of the #stayhome strategy for containing Covid-19, and successfully validate the simulation results against the classical epidemiological theory. Neuro-SIR is applicable in designing and assessing prevention and control strategies for spreading diseases, as well as in predicting the evolution pattern of epidemics.



中文翻译:

#stayhome包含Covid-19:Neuro-SIR-社交网络中感染模式的神经动力学流行病建模。

介绍了社交网络中流行病的创新神经动力学模型– Neuro-SIR。从机理上讲,易感性感染消除型(SIR)的流行过程类似于在神经元群体中的活动传播。感染通过社会交往网络从一个人传播到另一个人的工作方式,是由泄漏的整合并发射神经元的阈值机制的动力学驱动的。通过这种方法,形成了人口对疾病易感性的动态演变格局。在这种情况下,根据代表个体脆弱性,病原体传染性的各种内源性和外源性因素的配置,一小部分受感染的个体会触发不同速度和规模的流行病。联络网络的密度和环境条件。恢复后调整免疫力的长度(如果有),可以对复发性流行病的易感性-感染性-恢复性-易感性(SIRS)过程进行建模。Neuro-SIR通过在人群描述,疾病的传染性和外部因素方面支持令人印象深刻的异质性水平,使得与现有方法相比,可以更深入地研究流行病的传播。通过Neuro-SIR的模拟实验,我们证明了包含Covid-19的#stayhome策略的有效性,并针对经典的流行病学理论成功验证了模拟结果。Neuro-SIR适用于设计和评估传播疾病的预防和控制策略,

更新日期:2020-09-03
down
wechat
bug