Wu Jiang, Zuo Renxian, He Chaocheng, Xiong Hang, Zhao Kang, Hu Zhongyi
School of Information Management, Wuhan University, Wuhan, 430072, China.
Center for Ecommerce Research and Development, Wuhan University, Wuhan, 430072, China.
Physica A. 2022 Jun 15;596:127119. doi: 10.1016/j.physa.2022.127119. Epub 2022 Mar 3.
With the COVID-19 pandemic, better understanding of the co-evolution of information and epidemic diffusion networks is important for pandemic-related policies. Using the microscopic Markov chain method, this study proposed an aware-susceptible-infected model (ASI) to explore the effect of information literacy on the spreading process in such multiplex networks. We first introduced a parameter that adjusts the self-protection related execution ability of aware individuals in order to emphasis the importance of protective behaviors compared to awareness in decreasing the infection probability. The model also captures individuals' heterogeneity in their information literacy. Simulation experiments found that the high information-literate individuals are more sensitive to information adoption. In addition, epidemic information can help to suppress the epidemic diffusion only when individuals' abilities of transforming awareness into actual protective behaviors attain a threshold. In communities dominated by highly literate individuals, a larger information literacy gap can improve awareness acquisition and thus help to suppress the epidemic among the whole group. By contrast, in communities dominated by low information-literate individuals, a smaller information literacy gap can better prevent the epidemic diffusion. This study contributes to the literature by revealing the importance of individuals' heterogeneity of information literacy on epidemic spreading in different communities and has implications for how to inform people when a new epidemic disease emerges.
在新冠疫情期间，更好地理解信息传播网络与疫情扩散网络的共同演化对于制定疫情相关政策至关重要。本研究采用微观马尔可夫链方法，提出了一个“知情-易感-感染”模型（ASI），以探究信息素养在这种多重网络传播过程中的作用。我们首先引入一个参数来调整知情个体的自我保护相关执行能力，以强调在降低感染概率方面，保护行为相较于认知的重要性。该模型还捕捉了个体在信息素养方面的异质性。模拟实验发现，高信息素养个体对信息采纳更为敏感。此外，只有当个体将认知转化为实际保护行为的能力达到一个阈值时，疫情信息才能有助于抑制疫情扩散。在高素养个体占主导的社区中，较大的信息素养差距可以提高认知获取，从而有助于在整个群体中抑制疫情。相比之下，在低信息素养个体占主导的社区中，较小的信息素养差距能更好地防止疫情扩散。本研究通过揭示个体信息素养异质性在不同社区疫情传播中的重要性，为相关文献做出了贡献，并对新疫情出现时如何向人们提供信息具有启示意义。
