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Int. J. Environ. Res. Public Health 2016, 13(9), 886; doi:10.3390/ijerph13090886

Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt

1
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52242, USA
2
Department of Epidemiology, University of Iowa, Iowa City, IA 52242, USA
3
Center of Scientific Excellence for Influenza Viruses, National Research Centre, Giza 12311, Egypt
4
Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center, Houston, TX 77030, USA
5
Department of Scientific Research, Human Link, Hazmieh 1107-2090, Lebanon
*
Author to whom correspondence should be addressed.
Academic Editor: Jamal Jokar Arsanjani
Received: 18 July 2016 / Revised: 22 August 2016 / Accepted: 1 September 2016 / Published: 6 September 2016
View Full-Text   |   Download PDF [8833 KB, uploaded 6 September 2016]   |  

Abstract

Human outbreaks with avian influenza have been, so far, constrained by poor viral adaptation to non-avian hosts. This could be overcome via co-infection, whereby two strains share genetic material, allowing new hybrid strains to emerge. Identifying areas where co-infection is most likely can help target spaces for increased surveillance. Ecological niche modeling using remotely-sensed data can be used for this purpose. H5N1 and H9N2 influenza subtypes are endemic in Egyptian poultry. From 2006 to 2015, over 20,000 poultry and wild birds were tested at farms and live bird markets. Using ecological niche modeling we identified environmental, behavioral, and population characteristics of H5N1 and H9N2 niches within Egypt. Niches differed markedly by subtype. The subtype niches were combined to model co-infection potential with known occurrences used for validation. The distance to live bird markets was a strong predictor of co-infection. Using only single-subtype influenza outbreaks and publicly available ecological data, we identified areas of co-infection potential with high accuracy (area under the receiver operating characteristic (ROC) curve (AUC) 0.991). View Full-Text
Keywords: coinfection; Egypt; influenza; remote sensing; ecological niche modeling; geography; medical; influenza A virus; H5N1 subtype; influenza A virus; H9N2 subtype coinfection; Egypt; influenza; remote sensing; ecological niche modeling; geography; medical; influenza A virus; H5N1 subtype; influenza A virus; H9N2 subtype
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Young, S.G.; Carrel, M.; Malanson, G.P.; Ali, M.A.; Kayali, G. Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt. Int. J. Environ. Res. Public Health 2016, 13, 886.

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