This presentation discusses using geographic information systems and spatial analysis techniques to analyze infectious disease data. It provides examples of mapping disease incidence rates to identify high-risk areas and using tools like local Moran's I statistic and multivariate clustering to detect spatial patterns and similarities between disease cases. The objectives are to spatially evaluate infectious diseases like parotitis, salmonella and campylobacteriosis in the Olomouc Region of the Czech Republic. Challenges with health data analysis are also noted, like data privacy issues, aggregation methods, and properly accounting for population and neighborhood characteristics when interpreting results.