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Predicting risk of avian influenza a(H5N1) in Egypt: the creation of a community level metric

  • Geerlings, Ellen C. L.1, 2
  • Heffernan, Claire3, 4
  • 1 University of Reading, Department of Agriculture, Reading, UK , Reading (United Kingdom)
  • 2 Research & International Development Consultancy Services (EGRID), Deventer, The Netherlands , Deventer (Netherlands)
  • 3 University of Bristol, School of Veterinary Sciences, Bristol, UK , Bristol (United Kingdom)
  • 4 London International Development Centre (LIDC), London, UK , London (United Kingdom)
Published Article
BMC Public Health
Springer (Biomed Central Ltd.)
Publication Date
Mar 21, 2018
DOI: 10.1186/s12889-018-5288-x
Springer Nature


BackgroundEfficient 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.MethodsTo 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.ResultsPoverty, 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.ConclusionsThe 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).

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