Description Infectious disease surveillance is the action of monitoring the health status of a population in order to predict, observe, and mitigate the harm caused by infectious diseases to a population. It traditionally relies upon mandatory or voluntary declaration of diagnosed cases by networks of health professionals, such as the Sentinella network in Switzerland. Modern approaches based on internet data (e.g., search queries) and machine learning are increasingly used to complement classical approaches in monitoring infections. In all cases, advanced statistical techniques are continuously developed to better assess risks and obtain more reliable predictions and improve the preparedness of public health authorities in case of epidemics. This workshop will provide an overview of the current state in the field of infectious disease surveillance, from the perspective of both data collection and data analysis.