Introduction
Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with epidemics. Sentinel networks in combination with information technology infrastructures in public health \cite{heffernan2004syndromic} provide data for the detection of spatial and temporal aberrations in the expected number of cases for groups of clinical signs and symptoms\cite{Brett2020}. Several modelling frameworks exist for the analysis of such data. For example, the moving epidemic method, an approach used to monitor, among others, the start of the flu epidemic \cite{vega2013influenza}. Further, methods based on seasonality patterns, the link between pathogens and meteorological parameters \cite{abeku2004malaria} and/or the measurement of vector indices for vector-borne pathogens \cite{chang2015re} are also available.