Time Series Analysis Module 2024: Enhancing skills in public health surveillance and research

The module provided participants with practical experience in time-series analysis techniques, focusing on their application to public health surveillance and research. Key topics included trend identification, seasonality, and forecasting. Participants developed skills in data preparation, addressing missing data, and performing regression models, with hands-on exercises using the statistical software R.

The programme featured a combination of interactive lectures, practical group work and discussions. Facilitators from the European Centre for Disease Prevention and Control (ECDC), RIVM, and the Robert Koch Institute of Germany guided participants through several topics, including outbreak detection and using surveillance data to assess the impact of public health interventions. Tailored sessions addressed multilevel modelling and GIS mapping. 

The module brought together a diverse group of learners, providing a collaborative atmosphere for participants to share their experiences and address challenges in applying time-series analysis to their unique geographical public health contexts. 

Participants left the module equipped with essential skills to perform and interpret time-series analysis and communicate their findings effectively. The inclusion of individual work sessions using participants’ own datasets ensured that the training was practical and relevant.