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arXiv 1307.2869stat.MEstat.AP
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模拟工作场所接触网络:组织结构、体系结构和报告错误对流行病预测的影响

Modelling workplace contact networks: the effects of organizational structure, architecture, and reporting errors on epidemic predictions

Gail E. Potter, Timo Smieszek, Kerstin Sailer

摘要:

面对面的社会接触是急性呼吸道感染的潜在重要传播途径,了解接触网络可以提高我们预测、遏制和控制流行病的能力。虽然工作场所是传染病传播的重要场所,但很少有研究收集工作场所接触数据并估计工作场所接触网络。我们使用接触日记,建筑距离的措施,和机构结构,以估计社会联系网络内的瑞士研究所。一些接触报告不一致,表明报告有误。我们用潜变量模型对此进行调整,联合估计真实的(未观察到的)联系人网络和特定持续时间的报告概率。我们发现,接触概率随着距离的增加而降低,研究小组成员,角色和共享项目对接触模式有很强的预测作用。仅0-5分钟接触的估计报告概率较低。调整报告错误改变了持续时间分布的估计,但没有改变协变量效应的估计,并且对流行病预测影响不大。我们的流行病模拟研究表明,包括基于架构和组织结构数据的网络结构,可以提高流行病预测模型的准确性。

英文摘要:

Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0-5 minute contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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