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

View Article: PubMed Central - PubMed

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).

No MeSH data available.


Related in: MedlinePlus

Distribution of influenza outbreaks by subtype from (A) the systematic surveillance program; (B) the World Organization for Animal Health (OIE); and (C) the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i).
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ijerph-13-00886-f001: Distribution of influenza outbreaks by subtype from (A) the systematic surveillance program; (B) the World Organization for Animal Health (OIE); and (C) the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i).

Mentions: Three sources were used for outbreak data from 2007 to 2015: a systematic avian influenza surveillance program between the Center of Scientific Excellence for Influenza Viruses in Egypt and the St. Jude Center of Excellence for Influenza Research and Surveillance in the United States [27], the avian influenza database from the OIE [28] and the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i) from the Food and Agriculture Organization (FAO) of the United Nations [29]. Data from the systematic surveillance program, ongoing since 2009, include monthly non-random samples for individual birds from commercial and backyard farms, as well as abattoirs and live bird markets (LBM). The OIE data, covering 2007 to February 2008, include reported outbreaks for flocks from commercial farms, backyard farms, and LBMs. The EMPRES-i data, from February 2008 to 2015, include reported outbreaks for flocks, but the majority do not record the habitat. The systematic surveillance program is the only data source that tests for and reports co-infection. For consistency, records for individual birds were aggregated into outbreaks based on location and date, with duplicates between data sources removed. Outbreaks were geocoded to the scale of individual farms, except for the systematic surveillance data which were geocoded to villages (see Figure 1). The bulk of the outbreaks from all three data sources were collected in seven governorates in Northern Egypt, representing the primary foci of the poultry industry [19].


Predicting Avian Influenza Co-Infection with H5N1 and H9N2 in Northern Egypt
Distribution of influenza outbreaks by subtype from (A) the systematic surveillance program; (B) the World Organization for Animal Health (OIE); and (C) the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036719&req=5

ijerph-13-00886-f001: Distribution of influenza outbreaks by subtype from (A) the systematic surveillance program; (B) the World Organization for Animal Health (OIE); and (C) the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i).
Mentions: Three sources were used for outbreak data from 2007 to 2015: a systematic avian influenza surveillance program between the Center of Scientific Excellence for Influenza Viruses in Egypt and the St. Jude Center of Excellence for Influenza Research and Surveillance in the United States [27], the avian influenza database from the OIE [28] and the Emergency Prevention System against transboundary animal and plant pests and diseases (EMPRES) Global Animal Disease Information System (EMPRES-i) from the Food and Agriculture Organization (FAO) of the United Nations [29]. Data from the systematic surveillance program, ongoing since 2009, include monthly non-random samples for individual birds from commercial and backyard farms, as well as abattoirs and live bird markets (LBM). The OIE data, covering 2007 to February 2008, include reported outbreaks for flocks from commercial farms, backyard farms, and LBMs. The EMPRES-i data, from February 2008 to 2015, include reported outbreaks for flocks, but the majority do not record the habitat. The systematic surveillance program is the only data source that tests for and reports co-infection. For consistency, records for individual birds were aggregated into outbreaks based on location and date, with duplicates between data sources removed. Outbreaks were geocoded to the scale of individual farms, except for the systematic surveillance data which were geocoded to villages (see Figure 1). The bulk of the outbreaks from all three data sources were collected in seven governorates in Northern Egypt, representing the primary foci of the poultry industry [19].

View Article: PubMed Central - PubMed

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).

No MeSH data available.


Related in: MedlinePlus