Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
Math Biosci. 2024 Oct;376:109264. doi: 10.1016/j.mbs.2024.109264. Epub 2024 Aug 2.
Understanding the interplay between social activities and disease dynamics is crucial for effective public health interventions. Recent studies using coupled behavior-disease models assumed homogeneous populations. However, heterogeneity in population, such as different social groups, cannot be ignored. In this study, we divided the population into social media users and non-users, and investigated the impact of homophily (the tendency for individuals to associate with others similar to themselves) and online events on disease dynamics. Our results reveal that homophily hinders the adoption of vaccinating strategies, hastening the approach to a tipping point after which the population converges to an endemic equilibrium with no vaccine uptake. Furthermore, we find that online events can significantly influence disease dynamics, with early discussions on social media platforms serving as an early warning signal of potential disease outbreaks. Our model provides insights into the mechanisms underlying these phenomena and underscores the importance of considering homophily in disease modeling and public health strategies.
理解社交活动和疾病动态之间的相互作用对于有效的公共卫生干预至关重要。最近使用耦合行为-疾病模型的研究假设人群是同质的。然而,人群中的异质性,如不同的社会群体,不容忽视。在这项研究中,我们将人群分为社交媒体用户和非用户,并研究了同质性(个人与相似的人交往的倾向)和在线事件对疾病动态的影响。我们的结果表明,同质性阻碍了接种策略的采用,加速了接近临界点的过程,之后人群会收敛到没有疫苗接种的地方病平衡点。此外,我们发现在线事件可以显著影响疾病动态,社交媒体平台上的早期讨论是潜在疾病爆发的预警信号。我们的模型深入了解了这些现象背后的机制,并强调了在疾病建模和公共卫生策略中考虑同质性的重要性。