Charaudeau Segolene, Pakdaman Khashayar, Boëlle Pierre-Yves
INSERM, UMR S 707, Paris, France ; Université Pierre et Marie Curie - Paris 6, Paris, France ; Institut Jacques Monod, Paris, France ; Université Denis Diderot, Paris, France.
Institut Jacques Monod, Paris, France ; Université Denis Diderot, Paris, France.
PLoS One. 2014 Jan 9;9(1):e83002. doi: 10.1371/journal.pone.0083002. eCollection 2014.
Commuting data is increasingly used to describe population mobility in epidemic models. However, there is little evidence that the spatial spread of observed epidemics agrees with commuting. Here, using data from 25 epidemics for influenza-like illness in France (ILI) as seen by the Sentinelles network, we show that commuting volume is highly correlated with the spread of ILI. Next, we provide a systematic analysis of the spread of epidemics using commuting data in a mathematical model. We extract typical paths in the initial spread, related to the organization of the commuting network. These findings suggest that an alternative geographic distribution of GP accross France to the current one could be proposed. Finally, we show that change in commuting according to age (school or work commuting) impacts epidemic spread, and should be taken into account in realistic models.
通勤数据越来越多地被用于描述流行病模型中的人口流动性。然而,几乎没有证据表明观察到的流行病的空间传播与通勤情况相符。在这里,我们利用法国哨兵网络所观察到的25起类似流感疾病(ILI)疫情的数据,表明通勤量与ILI的传播高度相关。接下来,我们在一个数学模型中使用通勤数据对疫情传播进行了系统分析。我们提取了初始传播中的典型路径,这些路径与通勤网络的结构有关。这些发现表明,可以提出一种与当前不同的法国全科医生地理分布方案。最后,我们表明,根据年龄的通勤变化(上学或上班通勤)会影响疫情传播,在实际模型中应予以考虑。