Early detection of disease outbreaks and non-outbreaks using incidence data

arXiv:2404.08893v1 Announce Type: new
Abstract: Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management. Here, we develop a general model, with no real-world training data, that accurately forecasts outbreaks and non-outbreaks. We propose a novel framework, using a feature-based time series classification method to forecast outbreaks and non-outbreaks. We tested our methods on synthetic data from a Susceptible-Infected-Recovered model for slowly changing, noisy disease dynamics. Outbreak sequences give a transcritical bifurcation within a specified future …

abstract arxiv classification cs.lg data detection disease feature forecast forecasting framework general management math.ds novel outbreaks q-bio.pe series stat.ap time series training training data type world