Abstract
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.
Highlights
The multi-scale network of social interactions [1,2] makes rapid dissemination of transmissible diseases possible, as illustrated recently by pandemic A/H1N1 2009 influenza and SARS [3,4]
Our analysis showed that commuting data determines the spread of influenza in modern populations, as evidenced by the large autocorrelation in observed Influenza like illness (ILI) incidence in regions connected by commuting
We provided an in depth study of the consequences of mobility as described by commuting in the initial spread of epidemics, showing how to identify preferential paths in a densely connected territory
Summary
The multi-scale network of social interactions [1,2] makes rapid dissemination of transmissible diseases possible, as illustrated recently by pandemic A/H1N1 2009 influenza and SARS [3,4]. Influenza like illness (ILI) incidence time series, as monitored by the Sentinelles network since 1984 in France, provide data at a high spatial resolution (NUTS3) that can be used in this respect (http://www.sentiweb.org). These data, unique in duration and spatial resolution, helped elucidate long sought questions like the impact of school closure during epidemics [11] and to validate model predictions for pandemic flu [12]. Commuting data based on the census of the population is available at an even finer scale
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