Dataset Information

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

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).

SUBMITTER: Young SG

PROVIDER: S-EPMC5036719 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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

Young Sean G SG Young Sean G SG Carrel Margaret M Malanson George P GP Ali Mohamed A MA Kayali Ghazi G

International journal of environmental research and public health 20160906 9

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 t ...[more]

PMID: 27608035

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Project description:BACKGROUND:Efficient A(H5N1) control is unlikely to be based on epidemiological data alone. Such control depends on a thorough understanding and appreciation of the interconnectedness of epidemiological, social, and economic factors that contribute to A(H5N1) vulnerability. To date, the control of A(H5N1) in Egypt has been challenging. The disease has been endemic for more than 10 years with a dramatic increase in human cases between December 2014 and March 2015. Part of the problem has been a lack of understanding of the inter-play of drivers, conditions and motives that influence preventive behaviours at the household level. METHODS:To address this issue, the authors developed a Composite Risk Index (CRI) to inform decision-makers of critical epidemiological, livelihood, food security and risk perception factors that were found to contribute to A(H5N1) vulnerability at the community level. The CRI consists of seven constructs that were individually scored for each community. The seven constructs included poultry sales, previous flock exposure to A(H5N1), human risk probability, sense of control over the disease, preventative actions taken, level of household food insecurity and community norms toward certain handling and disposal practices. One hundred forty female poultry keepers across four governorates were interviewed in 2010 using a mix of random and purposive sampling techniques. A mixed method approach underpinned the analysis. The study used wealth ranking in order to help decision-makers in understanding the specific constraints of different wealth groups and aid better targeting of A(H5N1) control and prevention strategies. RESULTS:Poverty, widowhood and lack of education were among the factors associated with high risk scores. CRI scores in those villages where awareness raising had taken place were not significantly different compared to those villages where awareness raising had not taken place. CONCLUSIONS:The aim of the tool is to enable targeting those communities that are likely to be highly vulnerable to A(H5N1) outbreaks and where control and awareness-raising efforts are expected to be most effective. In this manner, policy makers and practitioners will be able to better allocate limited resources to those communities most vulnerable to the negative impact of A(H5N1).

Project description:BackgroundHighly pathogenic avian influenza (HPAI) viruses of the H5N1 subtype are widely distributed within poultry populations in Egypt and have caused multiple human infections. Linking the epidemiological and sequence data is important to understand the transmission, persistence and evolution of the virus. This work describes the phylogenetic dynamics of H5N1 based on molecular characterization of the hemagglutinin (HA) gene of isolates collected from February 2006 to May 2014.MethodsFull-length HA sequences of 368 H5N1 viruses were generated and were genetically analysed to study their genetic evolution. They were collected from different poultry species, production sectors, and geographic locations in Egypt. The Bayesian Markov Chain Monte Carlo (BMCMC) method was applied to estimate the evolutionary rates among different virus clusters; additionally, an analysis of selection pressures in the HA gene was performed using the Single Likelihood Ancestor Counting (SLAC) method.ResultsThe phylogenetic analysis of the H5 gene from 2006-14 indicated the presence of one virus introduction of the classic clade (2.2.1) from which two main subgroups were originated, the variant subgroup which was further subdivided into 2 sub-divisions (2.2.1.1 and 2.2.1.1a) and the endemic subgroup (2.2.1.2). The clade 2.2.1.2 showed a high evolution rate over a period of 6 years (6.9 × 10(-3) sub/site/year) in comparison to the 2.2.1.1a variant cluster (7.2 × 10(-3) over a period of 4 years). Those two clusters are under positive selection as they possess 5 distinct positively selected sites in the HA gene. The mutations at 120, 154, and 162 HA antigenic sites and the other two mutations (129∆, I151T) that occurred from 2009-14 were found to be stable in the 2.2.1.2 clade. Additionally, 13 groups of H5N1 HPAI viruses were identified based on their amino acid sequences at the cleavage site and "EKRRKKR" became the dominant pattern beginning in 2013.ConclusionsContinuous evolution of H5N1 HPAI viruses in Egypt has been observed in all poultry farming and production systems in almost all regions of the country. The wide circulation of the 2.2.1.2 clade carrying triple mutations (120, 129∆, I151T) associated with increased binding affinity to human receptors is an alarming finding of public health importance.

Dataset Information

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

Publications

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

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