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Influenza remains a constant concern for public health agencies across the nation and worldwide. Current methods of surveillance suffice but they fall short of their true potential. Incorporation of evolutionary data and analysis through studies such as phylogeography could reveal geographic sources of variation. Identification and targeting of such sources

Influenza remains a constant concern for public health agencies across the nation and worldwide. Current methods of surveillance suffice but they fall short of their true potential. Incorporation of evolutionary data and analysis through studies such as phylogeography could reveal geographic sources of variation. Identification and targeting of such sources for public health initiatives could yield increased effectiveness of influenza treatments. As it stands there is a lack of evolutionary data available for such use, particularly in the southwest. Our study focused on the sequencing and phylogeography of southwestern Influenza A samples from the Mayo Clinic. We fully sequenced two neuraminidase genes and combined them with archived sequence data from the Influenza Research Database. Using RAxML we identified the clade containing our sequences and performed a phylogeographic analysis using ZooPhy. The resultant data were analyzed using programs such as SPREAD and Tracer. Our results show that the southwest sequences emerged from California and the ancestral root of the clade came from New York. Our Bayesian maximum clade credibility (MCC) tree data and SPREAD analysis implicates California as a source of influenza variation in the United States. This study demonstrates that phylogeography is a viable tool to incorporate evolutionary data into existing forms of influenza surveillance.
ContributorsTurnock, Adam Ryan (Author) / Scotch, Matthew (Thesis director) / Halden, Rolf (Committee member) / Pycke, Benny (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-05
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Description
The 2017-2018 Influenza season was marked by the death of 80,000 Americans: the highest flu-related death toll in a decade. Further, the yearly economic toll to the US healthcare system and society is on the order of tens of billions of dollars. It is vital that we gain a better

The 2017-2018 Influenza season was marked by the death of 80,000 Americans: the highest flu-related death toll in a decade. Further, the yearly economic toll to the US healthcare system and society is on the order of tens of billions of dollars. It is vital that we gain a better understanding of the dynamics of influenza transmission in order to prevent its spread. Viral DNA sequences examined using bioinformatics methods offer a rich framework with which to monitor the evolution and spread of influenza for public health surveillance. To better understand the influenza epidemic during the severe 2017-2018 season, we established a passive surveillance system at Arizona State University’s Tempe Campus Health Services beginning in January 2018. From this system, nasopharyngeal samples screening positive for influenza were collected. Using these samples, molecular DNA sequences will be generated using a combined multiplex RT-PCR and NGS approach. Phylogenetic analysis will be used to infer the severity and temporal course of the 2017-2018 influenza outbreak on campus as well as the 2018-2019 flu season. Through this surveillance system, we will gain knowledge of the dynamics of influenza spread in a university setting and will use this information to inform public health strategies.
ContributorsMendoza, Lydia Marie (Author) / Scotch, Matthew (Thesis director) / Hogue, Brenda (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05