Layout 1 ISDS Annual Conference Proceedings 2012. This is an Open Access article distributed under the terms of the Creative Commons Attribution- Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ISDS 2012 Conference Abstracts Challenges and Opportunities in Routine Time Series Analysis of Surveillance Data Isabelle Devaux*1, Esther Kissling2, Gilles Desve2, Frantiska Hruba1, Francisco Luquero2, Chantal Quinten1, Joana Gomes-Diaz1, Marta Valenciano2 and Denis Coulombier1 1ECDC, Solna, Sweden; 2Epiconcept, Paris, France Objective To discuss challenges and opportunities in the introduction of an automated approach for time series analysis (TSA) regarding epi- demiological methodology for generation of hypotheses, steps to be performed and interpretation of outputs. Introduction ECDC long term strategies for surveillance include analysis of trends of communicable disease of public health importance for Eu- ropean Union countries to guide public health actions. The European Surveillance System (TESSy) holds data on 49 communicable dis- eases reported by 30 countries for at least the past five years. To sim- plify time related analysis using surveillance data, ECDC launched a project to enable descriptive and routine TSA without the need for complex programming. Methods Protocols for TESSy data were developed specifying hypotheses to be tested, types and format of variables needed for TSA for several diseases, including VTEC, and legionellosis. Stata scripts were de- veloped to comply with the basic steps of TSA, including data ag- gregation, data checking, data description, analysis of trends and seasonality, residual analysis, simple modelling and long-term fore- casting. TSA steps were presented as successive tabs in a TSA dia- logue box in Stata. Before using the Stata TSA dialogue box, experts were offered a two-day training, and provided with an in-depth man- ual supporting use and interpretation of TSA outputs using the Stata TSA dialogue box. Results For VTEC, it was possible to identify a small increase in the trend and a seasonal pattern in surveillance data with an estimate of the start of the increased risk for infection in the beginning of the sum- mer season [1]. For legionellosis, an increasing trend in the number of reported cases was observed in 2010 [2]. Feedback from the train- ing showed that using the Stata TSA dialogue box enables a quick exploratory analysis even by non-Stata users who could focus on in- terpretation of results, rather than the programme writing. However, we emphasise that statistical knowledge of TSA as well as rigorous preparation of the datasets (including data quality checks) and gen- eration of hypotheses, are essential to ensure appropriate analysis and meaningful interpretation of the results. Conclusions Using the Stata TSA dialogue box saves time when performing rapid exploratory TSA of epidemiological data, avoiding the need for complex programming which is still needed for sophisticated TSA. Results of exploratory TSA analysis can trigger new hypothesis, for more advanced and sophisticated TSA. The introduction of a new technology (Stata TSA dialogue box) does not replace multi-disci- plinary approach, knowledge and application of a methodological ap- proach to TSA to produce meaningful results that can inform public health decision making. Further testing and training will be performed to enhance simplicity before appropriate dissemination of the Stata TSA dialogue box for a wider use. Keywords surveillance; epidemiology; statistical model; data analysis; software tool Acknowledgments ECDC experts in food and water-borne diseases (Angela Lahuerta-Marin, Taina Niskanen, Johanna Takkinen, Therese Westrell), and Legionnaires’ disease (Julien Beaute). References [1] Joana Gomes Dias, Franti!ka Hrubá, Chantal Quinten, Bruno Ciancio, Isabelle Devaux, Taina Niskanen, Therese Westrell, Angela Lahuerta- Marin, Johanna Takkinen. Time-series analysis of VTEC/STEC sur- veillance data, 2008–2010. Poster to be presented in ESCAIDE (www.escaide.org) 24-26 October 2012. [2] Julien Beaute, Birgita De Jong. Time series analysis of community- acquired Legionnaires’ disease in Europe. Poster to be presented in ESCAIDE (www.escaide.org) 24-26 October 2012. *Isabelle Devaux E-mail: isabelle.devaux@ecdc.europa.eu Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e182, 2013