A Decision Support Framework for Risk Prediction of Avian Influenza Occurrence

What is it about?

In this study, we have proposed a decision support framework for the prediction of the occurrence and spread of avian influenza events in a geographical area. The application of the proposed framework was examined in an Indonesian case study. An extensive list of historical data sources containing disease predictors and target variables was used to build spatiotemporal and transactional datasets. Given the constructed datasets, underlying patterns in the form of rules explaining the risk of occurrence and spread of avian influenza were discovered. The created rules were combined and ordered based on their importance and then stored in a knowledge base. The results suggested that the proposed framework could act as a tool to gain a broad understanding of the drivers of avian influenza epidemics and may facilitate the prediction of future disease events.

Featured Image

Photo by Artem Beliaikin on Unsplash

Photo by Artem Beliaikin on Unsplash

Why is it important?

Avian influenza viruses can cause economically devastating diseases in poultry and have the potential for zoonotic transmission. To mitigate the consequences of avian influenza, disease prediction systems have become increasingly important. This work proposes a novel decision support framework for the early prediction of the avian influenza outbreak.