Abstract
The networked structure of contacts shapes the spreading of epidemic processes. Recent advances on network theory have improved our understanding of the epidemic processes at large scale. The relevance of several considerations still needs to be evaluated in the study of epidemic spreading. One of them is that of accounting for the influence of origin and destination patterns in the flow of the carriers of an epidemic. Here we compute origin-destination patterns compatible with empirical data of coarse grained flows in the air transportation network. We study the incidence of epidemic processes in a metapopulation approach considering different alternatives to the flows prior knowledge. The data-driven scenario where the estimation of origin and destination flows is considered turns out to be relevant to assess the impact of the epidemics at a microscopic level (in our scenario, which populations are infected). However, this information is irrelevant to assess its macroscopic incidence (fraction of infected populations). These results are of interest to implement even better computational platforms to forecast epidemic incidence.
Highlights
The networked structure of contacts shapes the spreading of epidemic processes
We wonder up to which point the estimation of O-D matrices are essential factors to determine the outcome of a certain epidemic process that uses the transportation network as the substrate for the carriers
The results show that, especially for the fraction of recovered individuals, the deviations observed between the O-D matrices and the Random Diffusion and Strength Proportional strategies are minimal at the macroscopic level
Summary
The networked structure of contacts shapes the spreading of epidemic processes. Recent advances on network theory have improved our understanding of the epidemic processes at large scale. The worldwide airports network has been identified as the fastest interaction mechanism between humans living very far apart In this context, metapopulation models constitute a natural approach for the analysis of epidemic spreading processes, since they combine in a single framework the local contagions in the so-called reaction phase, and the mobility of the individuals in the diffusion stage[7,8,9,10,11,12]. A common hypothesis in metapopulation simulations is that the diffusion through the links of the network is markovian, i.e., each individual willing to move to a neighboring node will choose the destination according to certain fixed probabilities assigned to each of the links[9,11,12,16] This method is complemented with memory of the origin node, making the individuals come back to their respective residences in a home-to-work travel pattern[15,17]. In the following we present the method www.nature.com/scientificreports/
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