支持学校感染控制策略的基于主体的模型

Daniele Baccega, S. Pernice, P. Terna, P. Castagno, G. Moirano, L. Richiardi, M. Sereno, S. Rabellino, M. Maule, M. Beccuti
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引用次数: 3

摘要

在2019冠状病毒病大流行期间,许多政府实施了保持身体距离的措施,以避免往往脆弱和超负荷的卫生保健系统崩溃。在采取物理距离措施之后,鉴于这些环境的潜在高风险,学校关闭似乎是不可避免的,以控制病原体的传播。然而,关闭学校被认为是极端的做法,也是政府的最后手段,因此在学校实施了各种非药物干预措施,以减少传播风险。通过基于主体的模型,我们研究了主动监控策略在学校环境中的有效性。模拟设置提供了假设性的,尽管是现实的场景,使我们能够确定最合适的控制策略,以避免大规模学校关闭,同时适应传染动态。通过我们研究中探索的公共政策来降低风险对卫生当局和学校管理者都是至关重要的。©2022,萨里大学。版权所有。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Agent-Based Model to Support Infection Control Strategies at School
Many governments enforced physical distancing measures during the COVID-19 pandemic to avoid the collapse of often fragile and overloaded health care systems. Following the physical distancing measures, school closures seemed unavoidable to keep the transmission of the pathogen under control, given the potentially high-risk of these environments. Nevertheless, closing schools was considered an extreme and the last resort of governments, and so various non-pharmaceutical interventions in schools were implemented to reduce the risk of transmission. By means of an agent-based model, we studied the efficacy of active surveillance strategies in the school environment. Simulations settings provided hypothetical although realistic scenarios which allowed us to identify the most suitable control strategy to avoid massive school closures while adapting to contagion dynamics. Reducing risk by means of public policies explored in our study is essential for both health authorities and school administrators. © 2022, University of Surrey. All rights reserved.
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