Shi Congjie, Ferreira Silvio C, Maia Hugo P, Moghadas Seyed M
Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3, Canada.
Departamento de Física, Universidade Federal de Viçosa, 36570-900, Viçosa, MG, Brazil.
Infect Dis Model. 2025 Apr 16;10(3):960-978. doi: 10.1016/j.idm.2025.04.004. eCollection 2025 Sep.
Network models adeptly capture heterogeneities in individual interactions, making them well-suited for describing a wide range of real-world and virtual connections, including information diffusion, behavioural tendencies, and disease dynamic fluctuations. However, there is a notable methodological gap in existing studies examining the interplay between physical and virtual interactions and the impact of information dissemination and behavioural responses on disease propagation. We constructed a three-layer (information, cognition, and epidemic) network model to investigate the adoption of protective behaviours, such as wearing masks or practising social distancing, influenced by the diffusion and correction of misinformation. We examined five key events influencing the rate of information spread: (i) rumour transmission, (ii) information suppression, (iii) renewed interest in spreading misinformation, (iv) correction of misinformation, and (v) relapse to a stifler state after correction. We found that adopting information-based protection behaviours is more effective in mitigating disease spread than protection adoption induced by neighbourhood interactions. Specifically, our results show that warning and educating individuals to counter misinformation within the information network is a more effective strategy for curbing disease spread than suspending gossip spreaders from the network. Our study has practical implications for developing strategies to mitigate the impact of misinformation and enhance protective behavioural responses during disease outbreaks.
网络模型能够巧妙地捕捉个体互动中的异质性，使其非常适合描述广泛的现实世界和虚拟连接，包括信息传播、行为倾向和疾病动态波动。然而，在现有研究中，考察物理和虚拟互动之间的相互作用以及信息传播和行为反应对疾病传播的影响时，存在显著的方法学差距。我们构建了一个三层（信息、认知和疫情）网络模型，以研究诸如佩戴口罩或保持社交距离等保护行为的采用情况，这些行为受到错误信息传播和纠正的影响。我们考察了影响信息传播速度的五个关键事件：（i）谣言传播，（ii）信息抑制，（iii）对传播错误信息的重新关注，（iv）错误信息的纠正，以及（v）纠正后恢复到抑制状态。我们发现，采用基于信息的保护行为在减轻疾病传播方面比邻里互动引发的保护行为采用更为有效。具体而言，我们的结果表明，在信息网络中警告和教育个体以对抗错误信息，是比将谣言传播者从网络中剔除更为有效的遏制疾病传播的策略。我们的研究对于制定策略以减轻错误信息的影响并在疾病爆发期间增强保护行为反应具有实际意义。
