In this course, we have often assumed that investigators have knowledge of a potentially harmful exposure coincidentally with or prior to observing the disease or illness. In other situations, the first indication of harmful exposure is a report of a potential outbreak of disease or illness. Increased numbers of cases of disease or illness may necessitate an outbreak investigation. Questions to be answered in an outbreak investigation include the following:

When an increase in the number of cases of a disease is reported, a speedy response is critical. At the same time, it is also of utmost importance to end up with an answer that will appropriately protect public health and safety. A systematic approach to outbreak investigation helps assure timely and accurate answers:

• Prepare for fieldwork
• Establish the existence of an outbreak
• Verify the diagnosis
• Define and identify cases
• Measure the frequency of adverse outcomes and describe the data in terms of time, place, and person
• Develop hypotheses
• Evaluate hypotheses
• Refine hypotheses and carry out additional studies
• Implement control and prevention measures
• Communicate findings

Characterizing by time: Constructing an Epi-Curve

An epidemic curve, frequently referred to as an 'epi-curve', is used to examine and characterize the occurrence of a possible outbreak. By constructing and examining an accurate epi-curve, an investigator can consider questions such as:

An epi-curve is a histogram with the number of cases of the adverse health outcome on the y-axis (ordinate) and dates of onset of the outcome on the x-axis (abscissa). Dates of onset may be grouped by days, weeks, or months, depending on the nature of the potential outbreak. A typical time period used is 1/4 to 1/3 the incubation period for the disease. If the incubation or lag time from exposure to outcome is unknown, it is valuable to experiment with different lengths of time.

A typical epi-curve is a simple chart with one series of data, the onset of cases. In other situations, several layers of data are displayed on the curve. For example, the investigator may want to examine the date of onset in more than one location (e.g. 2 or more cities, states or countries) or in different groups of people (e.g. stratified by age or race).

Another variation of the epi-curve is stacking the bars in order to show different characteristics of the cases. For example, you may decide to separate confirmed cases from suspect cases, using stacked bars to assess whether an outbreak is truly occurring.

Interpreting an Epi-Curve

The following shows the outbreak of COVID-19 cases in Pennsylvania:

The first consideration is the overall shape of the curve which is determined by the pattern of the outbreak (common source or person-to-person transmission). The shape also indicates the period of time over which susceptible people are exposed and the minimum, average and maximum incubation periods for the disease.
If the duration of exposure is prolonged, the epidemic is called a "continuous common source epidemic," and the epidemic curve will have a plateau instead of a peak. Person-to-person spread (a "propagated" epidemic) should have a series of progressively taller peaks one incubation period apart.

Cases that stand apart ("outliers") provide valuable information. An early case can represent a background (unrelated) case, a source of the epidemic, or a person who was exposed earlier than others. Similarly, late cases may be unrelated to the outbreak, may have especially long incubation periods, may indicate exposure later than most of the people affected, or maybe secondary cases (the person who becomes ill after being exposed to someone who was part of the initial outbreak). Examine any outliers that are part of the outbreak carefully because they may point directly to the source. For example, a prep chef could be the first case of strep in an epidemic among party-goers eating food prepared by this person.
In a point-source epidemic of a disease with a known incubation period, the epidemic curve can also identify the likely period of exposure.

Characterizing by place

A simple technique for looking at geographic patterns is to plot on a 'spot map' the locations where the affected people live, work, or may have been exposed. A map of cases in a community may show clusters or patterns that reflect water supplies, wind currents, or proximity to a restaurant or grocery store. A classic example is John Snow's detection of the Broad St. water pump as the source of a cholera epidemic. On a spot map of a hospital, nursing home, or another residential facility, clustering may indicate either a primary source or person-to-person spread. The scattering of cases throughout a facility is more consistent with a common source such as a dining hall.

If the size of the overall population varies among the areas being compared, the spot map with the number of cases can be misleading. Indicating the proportion affected or the attack rate for each area would be a better approach.

Characterizing by person

Define the populations at risk for the disease by characterizing an outbreak by personal characteristics such as age, race, sex, medical status, etc, and/or by exposures (e.g., occupation, leisure activities, use of medications, tobacco, drugs, etc.). Age and sex are characteristics often strongly related to exposure and risk; thus these factors are often assessed first. Other factors to be assessed are those possibly related to susceptibility to the disease and to opportunities for exposure to the disease being investigated and in the setting of the outbreak.