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应用“本地传播区”方法分析社区中流感和 RSV 的动态。

Analysis of Influenza and RSV dynamics in the community using a 'Local Transmission Zone' approach.

机构信息

Flurensics Inc., Tel Aviv, 64101 Israel.

School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, Australia.

出版信息

Sci Rep. 2017 Feb 9;7:42012. doi: 10.1038/srep42012.

Abstract

Understanding the dynamics of pathogen spread within urban areas is critical for the effective prevention and containment of communicable diseases. At these relatively small geographic scales, short-distance interactions and tightly knit sub-networks dominate the dynamics of pathogen transmission; yet, the effective boundaries of these micro-scale groups are generally not known and often ignored. Using clinical test results from hospital admitted patients we analyze the spatio-temporal distribution of Influenza Like Illness (ILI) in the city of Jerusalem over a period of three winter seasons. We demonstrate that this urban area is not a single, perfectly mixed ecology, but is in fact comprised of a set of more basic, relatively independent pathogen transmission units, which we term here Local Transmission Zones, LTZs. By identifying these LTZs, and using the dynamic pathogen-content information contained within them, we are able to differentiate between disease-causes at the individual patient level often with near-perfect predictive accuracy.

摘要

了解城市地区病原体传播的动态对于传染病的有效预防和控制至关重要。在这些相对较小的地理尺度上,短距离的相互作用和紧密结合的子网主导了病原体传播的动态;然而,这些微观尺度群体的有效边界通常是未知的,并且经常被忽略。我们利用医院住院患者的临床检测结果,分析了耶路撒冷市三个冬季期间流感样疾病(ILI)的时空分布。我们证明,这个城市区域不是一个单一的、完全混合的生态系统,而是实际上由一组更基本的、相对独立的病原体传播单元组成,我们在这里称之为局部传播区(LTZ)。通过识别这些 LTZ,并利用它们内部包含的动态病原体信息,我们能够在个体患者层面上区分疾病的病因,通常具有近乎完美的预测准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30b3/5299452/df398cd0ff2e/srep42012-f1.jpg

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