Open access journal
A Bayesian-weighted Adaptive Ensemble for Early Multi-disease Outbreak Classification from Multi-modal Big Data Streams
By Rejoice E. Ogini and F. O. Okorodudu.
Abstract
Background
Across much of sub-Saharan Africa, disease-surveillance systems remain largely reactive: health authorities are often notified only after an outbreak has already been under way for days or weeks.
Aim
this study develops and evaluates a Bayesian-weighted ensemble classifier that determines, from a 47-dimensional multi-modal feature vector spanning epidemiological, environmental, and digital signals, whether a weekly state–disease record represents an outbreak.