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首页> 外文期刊>International journal of artificial life research >A Computational Model of Mitigating Disease Spread in Spatial Networks
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A Computational Model of Mitigating Disease Spread in Spatial Networks

机译：缓解疾病在空间网络中传播的计算模型

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This study examines the problem of disease spreading and containment in spatial networks, where the computational model is capable of detecting disease progression to initiate processes mitigating infection spreads. This paper focuses on disease spread from a central point in a 1 x 1 unit square spatial network, and makes the model respond by trying to selectively decimate the network and thereby contain disease spread. Attention is directed on the kinematics of disease spreading with respect to how damage is controlled by the model. In addition, the authors analyze both the sensitivity of disease progression on various parameter settings and the correlation of parameters of the model. As the result, this study suggests that the radius of containment process is the most critical parameter and its best values with the computational model would be a great help to reduce damages from disease spread of a future pandemic. The study can be applied to controlling other virus spread problems in spatial networks such as disease spread in a geographical network and virus spread in a brain cell network.
机译：这项研究检查了空间网络中疾病的传播和控制问题，该计算模型能够检测疾病的进展，从而启动缓解感染传播的过程。本文关注于从1 x 1单位正方形空间网络的中心点传播的疾病，并使模型通过尝试选择性地抽取网络从而抑制疾病传播来做出响应。关于模型如何控制损害，着眼于疾病传播的运动学。此外，作者分析了疾病进展对各种参数设置的敏感性以及模型参数的相关性。结果，该研究表明，遏制过程的半径是最关键的参数，其在计算模型中的最佳值将有助于减少未来大流行病的传播所造成的损害。该研究可用于控制空间网络中的其他病毒传播问题，例如地理网络中的疾病传播和脑细胞网络中的病毒传播。

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