This study used numerical modelling to analyze air velocity, cough particle distribution and infection risks in an isolation room. It investigated air change rates, inlet/outlet vent positioning and assessed various ventilation rates and outlet configurations for reducing infection risks. Quantitative assessments revealed different particle escape timings. In Case 1, smaller particles (2–4 μm) took 8.2 s to escape, while in Case 2, this time extended to 22.7 s. At 48 ACH, there were significant improvements in removing particles of various sizes, particularly those sized 2–4 μm, 16–24 μm and 40–50 μm, reducing the infection risk. The use of the Wells-Riley model highlighted considerable reductions in infection probabilities with higher ACH. Specifically, infection risks were reduced to 5% in Case 1 and 17% in Case 2, underscoring the marked advantage of Case 1 in reducing infection probabilities, particularly for smaller particles. Furthermore, escalated ACH values consistently correlated with decreased infection probabilities across all particle sizes, highlighting the pivotal role of ventilation rates in mitigating infection risks. The study comprehensively investigated the distribution of air velocity, dynamics of cough particles and infection risk associated with different ventilation strategies in isolation rooms.

中文翻译：

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减轻医院隔离室咳嗽颗粒传播和感染风险的通风策略的数值模型

这项研究使用数值模型来分析隔离室中的空气流速、咳嗽颗粒分布和感染风险。它调查了换气率、入口/出口通风口位置，并评估了各种通风率和出口配置，以降低感染风险。定量评估揭示了不同的粒子逃逸时间。在案例 1 中，较小的颗粒 (2–4 μm) 需要 8.2 秒才能逃逸，而在案例 2 中，该时间延长至 22.7 秒。在 48 ACH 时，去除各种尺寸的颗粒（尤其是 2-4 μm、16-24 μm 和 40-50 μm 的颗粒）的效果显着改善，从而降低了感染风险。Wells-Riley 模型的使用凸显了 ACH 较高时感染概率的显着降低。具体而言，案例 1 的感染风险降低至 5%，案例 2 的感染风险降低至 17%，这凸显了案例 1 在降低感染概率方面的显着优势，特别是对于较小的颗粒。此外，升高的 ACH 值始终与所有颗粒尺寸的感染概率降低相关，这凸显了通风率在降低感染风险方面的关键作用。该研究全面调查了隔离室中不同通风策略相关的风速分布、咳嗽颗粒动态以及感染风险。