Computational Biology Lab (DLab), Fundación Ciencia & Vida, Santiago, Chile.
Centro Interdisciplinario de Neurociencia de Valparaíso, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile.
PLoS One. 2021 Oct 29;16(10):e0257995. doi: 10.1371/journal.pone.0257995. eCollection 2021.
When pharmaceutical interventions are unavailable to deal with an epidemic outbreak, adequate management of communication strategies can be key to reduce the contagion risks. On the one hand, accessibility to trustworthy and timely information, whilst on the other, the adoption of preventive behaviors may be both crucial. However, despite the abundance of communication strategies, their effectiveness has been scarcely evaluated or merely circumscribed to the scrutiny of public affairs. To study the influence of communication strategies on the spreading dynamics of an infectious disease, we implemented a susceptible-exposed-infected-removed-dead (SEIRD) epidemiological model, using an agent-based approach. Agents in our systems can obtain information modulating their behavior from two sources: (i) through the local interaction with other neighboring agents and, (ii) from a central entity delivering information with a certain periodicity. In doing so, we highlight how global information delivered from a central entity can reduce the impact of an infectious disease and how informing even a small fraction of the population has a remarkable impact, when compared to not informing the population at all. Moreover, having a scheme of delivering daily messages makes a stark difference on the reduction of cases, compared to the other evaluated strategies, denoting that daily delivery of information produces the largest decrease in the number of cases. Furthermore, when the information spreading relies only on local interactions between agents, and no central entity takes actions along the dynamics, then the epidemic spreading is virtually independent of the initial amount of informed agents. On top of that, we found that local communication plays an important role in an intermediate regime where information coming from a central entity is scarce. As a whole, our results highlight the importance of proper communication strategies, both accurate and daily, to tackle epidemic outbreaks.
当无法通过药物干预来应对疫情爆发时，充分管理传播策略可能是降低传染风险的关键。一方面，获取可靠和及时的信息至关重要，另一方面，采取预防措施也同样重要。然而，尽管存在大量的传播策略，但它们的有效性很少得到评估，或者仅仅局限于公共事务的审查。为了研究传播策略对传染病传播动态的影响，我们采用基于代理的方法实现了一个易感-暴露-感染-移除-死亡（SEIRD）的流行病学模型。我们的系统中的代理可以从两个来源获取信息，从而调整其行为：（i）通过与其他邻近代理的本地交互，以及（ii）通过定期向代理发送信息的中央实体。通过这种方式，我们强调了中央实体提供的全局信息如何能够减少传染病的影响，以及即使只向一小部分人群提供信息，与不向人群提供信息相比，也会产生显著的影响。此外，与其他评估策略相比，每天发送消息的方案在减少病例方面产生了显著的差异，这表明每天发送信息会产生最大程度的病例减少。此外，当信息传播仅依赖于代理之间的本地交互，且没有中央实体在动态中采取行动时，那么传染病的传播实际上与初始数量的知情代理无关。最重要的是，我们发现，在中央实体信息稀缺的中间阶段，本地交流起着重要作用。总的来说，我们的研究结果强调了正确的传播策略的重要性，无论是准确的还是日常的，都有助于应对疫情爆发。
