Risk Assessment of Influenza A viruses

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Title: Risk Assessment of Influenza A Viruses Project Summary Influenza A viruses (IAVs) have caused large losses of life around the world and continue to present a great public health challenge. Risk assessment of influenza viruses is a key component in pandemic influenza preparedness (PIP), and it can help optimize resources for influenza surveillance, vaccine development and other control measurements to help minimize losses due to an emerging influenza virus. Risk assessment of influenza viruses includes emergence risk and public health impact of novel influenza viruses. Emergence risk assesses the probability for a novel influenza virus to infect and easily spread among humans; it is the first risk to be evaluated in risk assessment. Although a number of individual mutations or structural/functional motifs have been reported to be associated with influenza infection and transmission, their effects on emergence risk are difficult to predict a priori. Thus, conventional methods for assessment of the emergence risk of a novel IAV often require laboratory generation of reassortants and subsequent measurement of their infectivity, pathogenesis, and transmission, which is often done in a mammalian system. However, this strategy can lead to laboratory mutants with gain of function (i.e., mutants with new or enhanced activity on pathogenesis and/or transmissibility in mammals). Thus, an ideal system for influenza risk assessment should be able to quantify emergence risk for a novel IAV solely by using genomic sequences. Avian influenza A viruses facilitated the emergence of all four known pandemic human influenza A viruses: the hemagglutinin genes of 1918, 1957, and 1968 pandemic viruses are all of avian origin, and the polymerase PB2 and PA genes of the 2009 pandemic virus are of avian origin. Risk assessment of potential reassortants from contemporary endemic human influenza viruses and enzootic avian influenza viruses has been a key component of the pandemic influenza preparedness process. The objectives of this study are to develop and validate a machine learning method to assess the emergence risk for a novel IAV using genomic sequences. The study will focus on emergence risk from contemporary endemic human influenza viruses and enzootic avian influenza viruses. We expect to identify genetic features within and across gene segments and ascertain their synergistic effects as emergence risk determinants. We also expect to develop a computational model for estimating the probability of a possible reassortant to emerge, given the genomic sequences of one human influenza virus and one avian influenza virus. The study results should help with understanding the fundamental mechanisms for genetic reassortment and with assessing emergence risk of influenza virus; thus, the results should facilitate pandemic influenza preparedness.