Chen S-C, Chang C-F, Liao C-M
Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan.
Indoor Air. 2006 Dec;16(6):469-81. doi: 10.1111/j.1600-0668.2006.00443.x.
Recently developed control measure modeling approaches for containing airborne infections, including engineering controls with respiratory protection and public health interventions, are readily amenable to an integrated-scale analysis. Here we show that such models can be derived from an integrated-scale analysis generated from three different types of functional relationship: Wells-Riley mathematical model, competing-risks model, and Von Foerster equation, both of the key epidemiological determinants involved and of the functional connections between them. We examine mathematically the impact of engineering control measures such as enhanced air exchange and air filtration rates with personal masking combined with public health interventions such as vaccination, isolation, and contact tracing in containing the spread of indoor airborne infections including influenza, chickenpox, measles, and severe acute respiratory syndrome (SARS). If enhanced engineering controls could reduce the basic reproductive number (R0) below 1.60 for chickenpox and 3 for measles, our simulations show that in such a prepared response with public health interventions would have a high probability of containing the indoor airborne infections. Combinations of engineering control measures and public health interventions could moderately contain influenza strains with an R0 as high as 4. Our analysis indicates that effective isolation of symptomatic patients with low-efficacy contact tracing is sufficient to control a SARS outbreak. We suggest that a valuable added dimension to public health inventions could be provided by systematically quantifying transmissibility and proportion of asymptomatic infection of indoor airborne infection. Practical Implications We have developed a flexible mathematical model that can help determine the best intervention strategies for containing indoor airborne infections. The approach presented here is scalable and can be extended to include additional control efficacies. If a newly emergent airborne infection should appear, the model could be quickly calibrated to data and intervention options at the early stage of the outbreak. Data could be provided from the field to estimate value of R0, the serial interval between cases, the distributions of the latent, incubation, and infectious periods, case fatality rates, and secondary spread within important mixing groups. The combination of enhanced engineering control measures and assigned effective public health interventions would have a high probability for containing airborne infection.
最近开发的用于控制空气传播感染的控制措施建模方法，包括带有呼吸防护的工程控制措施和公共卫生干预措施，很适合进行综合尺度分析。在此我们表明，此类模型可从由三种不同类型的函数关系生成的综合尺度分析中推导得出：威尔斯 - 莱利数学模型、竞争风险模型和冯·福斯特方程，涉及两个关键的流行病学决定因素及其之间的函数联系。我们从数学上研究了工程控制措施（如增强空气交换和空气过滤率并结合个人防护口罩）与公共卫生干预措施（如疫苗接种、隔离和接触者追踪）对控制包括流感、水痘、麻疹和严重急性呼吸综合征（SARS）在内的室内空气传播感染传播的影响。如果增强的工程控制措施能够将水痘的基本繁殖数（R0）降低至1.60以下，将麻疹的基本繁殖数降低至3以下，我们的模拟结果表明，在这种准备好的应对措施与公共卫生干预措施相结合的情况下，极有可能控制室内空气传播感染。工程控制措施与公共卫生干预措施的组合能够适度控制R0高达4的流感毒株。我们的分析表明，对有症状患者进行有效的隔离并辅以低效的接触者追踪就足以控制SARS疫情。我们建议，通过系统地量化室内空气传播感染的传播能力和无症状感染比例，可以为公共卫生干预措施增添一个有价值的维度。实际意义我们开发了一个灵活的数学模型，该模型有助于确定控制室内空气传播感染最佳干预策略。这里提出的方法具有可扩展性，并且可以扩展到包括其他控制效果。如果出现新出现的空气传播感染，该模型可以在疫情爆发的早期阶段快速根据数据和干预选项进行校准。可以从实地提供数据来估计R0的值、病例之间的连续间隔时间、潜伏期、发病期和传染期的分布、病死率以及在重要混合群体中的二次传播情况。增强的工程控制措施与有效的公共卫生干预措施相结合极有可能控制空气传播感染。
