Abstract

AbstractAimOur goal was to use the occurrence of the influenza A virus in wild birds in Japan to create a potential risk map for the spread of avian influenza by migratory birds. Our modelling included a consideration of the multicollinearity and spatial autocorrelation of environmental variables and an examination of the reproducibility of the model results.LocationJapan.MethodsWe used the maximum entropy approach to generate potential distribution models from presence‐only data. Independent variables in the model included environmental factors such as winter temperature and precipitation, host factors such as duck population size and habitat abundance and artificial factors such as size of urban areas and poultry density. We used eigenvector‐based spatial filters to alleviate spatial autocorrelation. To explore the reliability of the model, we compared the risk indices of localities positive in past winters for the influenza A virus in wild birds with those of all localities.ResultsThe model alleviated spatial autocorrelation with a high degree of accuracy. Dabbling duck population, size of urban area, diving duck population and altitude were the variables that were most strongly correlated with the potential distribution of avian influenza. We used the frequency of occurrence of the influenza A virus in five recent years in localities where wild birds were infected to estimate the repeatability of the high‐risk indices; the potential risk indices for avian influenza in wild birds were high in localities where wild birds were infected in past.Main conclusionsThe dabbling duck population in an area appeared to be the best indicator of high risk for the introduction of avian influenza from abroad. Priority monitoring localities for avian influenza carried by wild birds should be designated in western Japan and along the Pacific coast, which we estimated to be high‐risk areas. Poultry farms in these areas should increase their biosecurity to prevent vectors from introducing avian influenza.

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