AI Use Case

Track and predict disease vector in general population

Analysing and predicting the trajectory of disease propogation in a population is critical to allow better mobilisation and targeting of scarce resources to combat the spread in a time-sensitive and high pressure situation. Using machine learning to support the process enables modelled predictions to be speedier and less resource-intensive - which can also lead to greater precision and specificity in outcomes.



Risk reduction - Predictive diagnosis,Operational Support - Situational awareness,Cost - Optimise resource allocation

Case Studies

Centers for Disease Control and Prevention~Centers for Disease Control and Prevention reduce polio report generation time to 1 hour using machine learning to automate regional mapping of the disease,Tampere University~Researchers from Tampere University apply machine learning to Instagram posts to predict the spread of influenza in Finland,"""Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow,""~University of Glasgow researchers predict virus reservoir hosts with 83.5% accuracy and provide hypotheses about unknown viral vectors",BlueDot~BlueDot identified Wuhan pneumonia outbreak from social media posts before WHO made public announcement on COVID-19


Public And Social Sector

Public Services

Data Sets

Structured / Semi-structured

AI Technologies

Machine Learning (ML),Traditional AI,ML Task - Grouping - Clustering,ML Task - Prediction - Binary Classification

Potential Vendors

MathWorks,Blue Dot