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Background: The pandemic of influenza A (H1N1) is a serious on-going globalpublic crisis. Understanding its spreading dynamics is of fundamentalimportance for both public health and scientific researches. Recent studieshave focused mainly on evaluation and prediction of on-going spreading, whichstrongly depends on detailed information about the structure of socialcontacts, human traveling patterns and biological activity of virus, etc.  Methodology/Principal Findings: In this work we analyzed the distributions ofconfirmed cases of influenza A (H1N1) in different levels and find the Zipf'slaw and Heaps' law. Similar scaling properties were also observed for severeacute respiratory syndrome (SARS) and bird cases of H5N1. We also found ahierarchical spreading pattern from countries with larger population and GDP tocountries with smaller ones. We proposed a model that considers generic controleffects on both the local growth and transregional transmission, without theneed of the above mentioned detailed information. We studied in detail theimpact of control effects and heterogeneity on the spreading dynamics in themodel and showed that they are responsible for the scaling and hierarchicalspreading properties observed in empirical data.  Conclusions/Significance: Our analysis and modeling showed that althoughstrict control measures for interregional travelers could delay the outbreak inthe regions without local cases, the focus should be turned to local preventionafter the outbreak of local cases. Target control on a few regions with thelargest number of active interregional travelers can efficiently prevent thespreading. This work provided not only a deeper understanding of the genericmechanisms underlying the spread of infectious diseases, but also somepractical guidelines for decision makers to adopt suitable control strategies.

Scaling in the global spreading patterns of pandemic Influenza A (H1N1) and the role of control: empirical statistics and modeling