[Cases at the very beginning or end of an outbreak are the most obvious outliers. The first thing that investigator should do when considering outlier is to make sure they are not mistakes due to data collection, coding, or entry error. For example, if there is only one 1-year-old patient or one 95-year-old patient, and the remain case patients range in age from 10 to 60 years old, investigators should confirm that the outlying values for age have been accurately recorded or calculated and entered into the database. ]
If an outlier is not an error, it may provide important information about the outbreak. For example, an early case may not be part of the outbreak; it may represent the baseline level of illness. However, it may also represent the source of the outbreak, such as an infected food handler, or a case exposed earlier than the others. A late case may not be part of the outbreak; but alternatively, a late case may represent an individual who had a long incubation period, and who was exposed later than the other cases. Correctly determining which outliers are important trends in the outbreak.