In this paper, a simple yet interpretable, probabilistic model is proposed for the prediction of reported case counts of infectious diseases. A spatio-temporal kernel is derived from training data to
This table summarizes the performance of our estimation models. For each disease and location, we list the subjective success/failure classification as well as model r2 at nowcasting (0-day forecast)
With increasing cut-off, the sensitivity decrease is associated with a decrease in number of charts requiring manual review for confirmation of infection.Abbreviations: DRM – drain-related meningitis,