In this short paper, we propose a new direction of cross-cutting research for prediction and control of spreading COVID-19 viruses over a human social network. Such a network consists of human agents whose behaviors are highly uncertain and biased. To predict and control such an uncertain network, we need to employ various researches such as control theory, signal processing, machine learning, and behavioral economics. In this article, we introduce our recent research results and propose future research topics to overcome the COVID-19 pandemic.

中文翻译：

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针对 COVID-19 的人类社交网络的控制、干预和行为经济学

在这篇简短的论文中，我们提出了跨领域研究的新方向，用于预测和控制 COVID-19 病毒在人类社交网络上的传播。这样的网络由行为高度不确定和有偏见的人类代理组成。为了预测和控制这样一个不确定的网络，我们需要运用控制理论、信号处理、机器学习和行为经济学等各种研究。在本文中，我们介绍了我们最近的研究成果，并提出了克服 COVID-19 大流行的未来研究课题。