Data on the distribution of mallards, mute swans and brent geese can help predict the risk of an avian flu outbreak on poultry farms. This is the result of research by Janneke Schreuder of Wageningen University & Research in collaboration with Utrecht University and Sovon Vogelonderzoek.
Schreuder examined the environmental factors of 26 outbreaks with highly pathogenic bird flu on Dutch poultry farms and compared these with factors around 104 uninfected control farms. She analyzed predictive indicators for bird flu outbreaks using ‘machine learning’.
Wild bird densities proved to be the best predictive indicators; 19 of the 20 highest scoring indicators concerned wild birds. Of these, 17 were water birds and 2 birds of prey. In addition to wild birds, one of the landscape features, agricultural use, also contributed to the prediction of bird flu on poultry farms. Of the waterfowl, the mallard appeared to be the most important contributor to risk prediction, followed by mute swan, brent goose and widgeon.
Previously, landscape features such as open water were mainly looked at as a predictive factor. Landscape features play a role in the presence of wild birds and the numbers in which they occur in a particular place. The new research shows that the presence and numbers of wild birds are better indicators for predicting an avian flu outbreak on poultry farms than the landscape features themselves.
Despite the limited number of bird flu cases analysed, the model appears to provide an accurate prediction of the risk of an outbreak. According to Schreuder, these analyzes and the resulting bird flu risk map are good tools for prioritizing bird flu monitoring. This knowledge also contributes to the targeted use of preventive measures to prevent the introduction of bird flu on farms. The maps can also help determine the best locations for poultry farms to minimize the risk of an avian flu outbreak.
According to Schreuder’s model, the presence and numbers of the mallard and the mute swan are of the utmost importance, followed by some geese species. The highly pathogenic virus variants have been found in many of these waterfowl in several recent bird flu outbreaks, as have several other species on the list of best predictive bird species. The study does not clarify the role of these birds in transmitting the bird flu virus to poultry farms. Further research into these bird species may provide new leads.
More information can be found in the publication ‘Wild bird densities and landscape variables predict spatial patterns in HPAI outbreak risk across The Netherlands‘ in MDPI.
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