Zoonotic Risk Predictor Machine Learning System

Pilot machine learning solutions in the process of being developed to assess and predict locations where known drivers of zoonotic disease emergence, spillover and outbreaks are likely to occur. This solution will utilise open source environmental, epidemiology and demographic data including deforestation data, disease outbreaks reports, wildife market location evaluations and regional infrastructure developments. The ML algorithms will be tailored to extract features within defined geographical coordinates, utilizing spatial analytics to assess proximity to relevant geographical entities. The algorithm will then seek to identify the importance of geographic, demographic, environmental or other factors in predicting disease hotspots.