title: Detecting early-warning signals for influenza A pandemic based on protein dynamical network biomarkers.
abstract: The outbreak of influenza A comes from a relatively stable state is a critical phenomenon on epidemic. In this paper, influenza A varying from different states is studied in the method of dynamical network biomarkers (DNB). Through studying DNB of influenza A virus protein, we can detect the warning signals of outbreak for influenza A and obtain a composite index. The composite index varies along with the state of pandemic influenza, which gives a clue showing the turn point of outbreak. The low value (<1) steady state of the composite index means influenza A is normally in the relatively steady stage. Meanwhile, if the composite index of a certain year increases by more than 0.8 relative to the previous year and it is less than 1 and it increases sharply and reaches a peak being larger than 1 in next year, it means the year is normal in the critical state before outbreak and the next year is normally in the outbreak state. Therefore, we can predict the outbreak of influenza A and identify the critical state before influenza A outbreak or outbreak state by observing the variation of index value.
authors.affiliation: School of Science, Jiangnan University, Wuxi 214122, China; Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Gao
authors.affiliation: School of Science, Jiangnan University, Wuxi 214122, China.
authors.forename: Kang
authors.initials: K
authors.lastname: Wang
authors.affiliation: School of Science, Jiangnan University, Wuxi 214122, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Ding
keywords: Dynamical network biomarker (DNB); Early-warning signal; Influenza A virus; The critical state; The outbreak state