Interpretation of Epidemic (Epi) Curves during Ongoing Outbreak Investigations
An epidemic curve (epi curve) shows progression of illnesses in an outbreak over time. Epi curves depict when people became ill by day, week, or month. In foodborne outbreak investigations, this information is often shown by the week people became ill. The horizontal axis (x-axis) is the week when a person became ill, also called the week of illness onset. The vertical axis (y-axis) is the number of persons with illness onset each week. During ongoing outbreak investigations, the epi curve is updated as new data become available. There are several important issues in understanding and interpreting epi curves during ongoing outbreak investigations.
- There is an inherent delay between the date that an illness starts and the date that the case is reported to public health authorities. This delay typically takes 2-3 weeks for Salmonella infections. Thus, for example, someone who got sick with a Salmonella infection last week is very unlikely to have their infection reported to public health authorities by now, and someone who got sick 3 weeks ago may just be reported now.
- Some background cases of illness are likely to occur that would have happened even without an outbreak. This makes it difficult to say exactly which case is the first in an outbreak. Epidemiologists typically focus on the first recognized cluster (group) of illnesses rather than the very first case. Due to the inherent reporting delay described above, the cluster is sometimes not detected until several weeks after the persons became ill.
- For some cases, the date of illness onset is not known because it takes time before someone from the health department can do an interview to ask for this information. Sometimes, this interview never occurs. If investigators know the date that a specimen from an ill person arrived in the laboratory for testing, they may estimate the date of illness onset as 3 days before the specimen submission date.
- It can be difficult to determine when cases start to decline because of the reporting delay. This information can become clearer as time passes.
It can be difficult to say when the outbreak is over because of the reporting delay. The delay means that the curve for the most recent 3 weeks always looks like the outbreak could be ending even during an active outbreak. The full shape of the curve is clear only after the outbreak is over.
Example of an epidemic (epi) curve during a multistate outbreak investigation of Salmonella Heidelberg infections, 2013-2014.
Review the progression of the epi curves: Multistate Outbreak of Multidrug-Resistant Salmonella Heidelberg Infections Linked to Foster Farms Brand Chicken