On Assessing Control Actions for Epidemic Models on Temporal Networks
On Assessing Control Actions for Epidemic Models on Temporal Networks
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DOI：
10.1109/lcsys.2020.2993104
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发表时间：
2020-05
影响因子：
3
通讯作者：
Lorenzo Zino;A. Rizzo;M. Porfiri
中科院分区：
文献类型：
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作者：
Lorenzo Zino;A. Rizzo;M. Porfiri
在这封信中，我们提出了一种基于时间网络的流行病模型，该模型明确封装了两种不同的控制动作。我们在活动驱动网络（ADN）的理论框架内开发我们的模型，该网络已成为捕获网络动态过程复杂性的宝贵工具，并在与时间网络形成相当的时间尺度上共同演化。具体来说，我们补充了易感者-感染者-易感性流行病模型，该模型具有公共卫生政策中非药物干预措施的典型特征：i）提高认识的行动，诱导人们采取自我保护行为，ii）限制感染者的社会活动的政策。在大规模人群的热力学极限下，我们使用平均场方法来分析得出流行阈值，这为在疫情爆发的早期阶段制定遏制行动提供了可行的见解。通过所提出的模型，可以通过解决优化问题来设计最佳的流行病控制政策作为两种策略的组合。最后，使用同质 ADN 上地方病流行率的分析计算来优化校准减轻地方病的控制行动。提供模拟来支持我们的理论结果。
In this letter, we propose an epidemic model over temporal networks that explicitly encapsulates two different control actions. We develop our model within the theoretical framework of activity driven networks (ADNs), which have emerged as a valuable tool to capture the complexity of dynamical processes on networks, coevolving at a comparable time scale to the temporal network formation. Specifically, we complement a susceptible–infected–susceptible epidemic model with features that are typical of nonpharmaceutical interventions in public health policies: i) actions to promote awareness, which induce people to adopt self-protective behaviors, and ii) confinement policies to reduce the social activity of infected individuals. In the thermodynamic limit of large-scale populations, we use a mean-field approach to analytically derive the epidemic threshold, which offers viable insight to devise containment actions at the early stages of the outbreak. Through the proposed model, it is possible to devise an optimal epidemic control policy as the combination of the two strategies, arising from the solution of an optimization problem. Finally, the analytical computation of the epidemic prevalence in endemic diseases on homogeneous ADNs is used to optimally calibrate control actions toward mitigating an endemic disease. Simulations are provided to support our theoretical results.