Local factors such as seasonal temperature, the year-depfinishent water and veobtaination index, and data on animal density can be utilized to predict regional outbreaks of avian flu in Europe. This is the finding of a research team led by epidemiologist, mathematician, and statistician Prof. Dr. Joacim Rocklöv. The researchers at Heidelberg University developed a machine learning model that can predict highly pathogenic avian influenza outbreak patterns in Europe with great accuracy applying various indicators. The modeling approach and tarobtained data collection could therefore contribute to proactive prevention measures.
The highly pathogenic avian influenza virus infection – commonly known as bird flu – primarily affects birds. Mammals, however, are also increasingly infected. This, the researchers report, increases the probability that the virus will cross over to humans. To better predict bird flu outbreaks and put early prevention measures into place, Prof. Rocklöv’s team at the Interdisciplinary Center for Scientific Computing and the Heidelberg Institute for Global Health developed a model that combines various indicators for a possible outbreak and utilizes machine learning methods for modeling.
The model was trained applying data of bird flu outbreaks in Europe documented between 2006 and 2021. As potential indicators of an imminent event, the Heidelberg researchers identified local factors such as temperature and precipitation conditions, the wild bird species, poultest farm density, veobtaination composition, and water levels. By combining these complex interdepfinishent seasonal and regional variables, the researchers were able to model outbreak patterns with an accuracy of up to 94 percent.
“Combining our modeling approach and tarobtained data collection can assist us to map more precisely the high-risk areas and seasons when outbreaks of bird flu are more likely,” stresses Joacim Rocklöv, an Alexander von Humboldt Professor conducting research on the effects of climate and environmental modify on public health in a number of projects at the university and Heidelberg University Hospital. According to Prof. Rocklöv, the research results could be utilized to design regional surveillance programs throughout Europe and improve early detection.
The research work was funded by the Alexander von Humboldt Foundation within the Horizon Europe Program of the European Union. The results were published in the journal “Scientific Reports.”
Source:
Journal reference:
Opata, M. R., et al. (2025). Predictiveness and drivers of highly pathogenic avian influenza outbreaks in Europe. Scientific Reports. doi.org/10.1038/s41598-025-04624-x
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