OBJECTIVES: Impact studies evaluate the benefit of vaccination on specific outcome measures in real live conditions. Those studies collect raw data that do not allow for making general assessments because sometimes the numbers are too low. Modelling techniques can fine-tune the raw data into more harmonised (= parametric) data presentation. But what do we learn after this transformation? METHODS: We collected data over 5 years on hospitalisation due to rotavirus infection in children < 5 years old before (2y) and after (3y) the introduction of vaccination in 9 Belgian hospitals. We split the annual data by age-group of 2 to 3 months when < 1-year-old and by year thereafter over the period of the epidemic spread. We harmonised the data using Riskview software in Excel®. The hypotheses tested are that the age-groups most vulnerable to the disease have the largest epidemic spread (highest number of weeks/y of cases reported) and that the less vulnerable age-groups have their spread during the peak weeks of the most vulnerable ones. The latter should indicate a way of disease transmission between age-groups that could be confirmed with vaccination. RESULTS: Pre-vaccination data analysis indicates the widest spread of the disease in the age-group of 9 to 11 months (39 wks/52) and the smallest ones in the very young (33 wks/52) and the oldest ones (8 wks/52). The data confirms the spread of the disease in the less vulnerable ones (younger and older ones) occurring during the peak moment of the season of the most vulnerable ones. Post-vaccination analysis shows the same pattern of dependency between the age-groups. CONCLUSIONS: Preferential spread of the disease starting from the 9 to 11 months old age-group to younger and older ones can be deduced from the data analysis. This could give an explanation for the annual self-limiting spread of rotavirus disease.