Statistical Measure for Disease Case Tracking
Use the mean (average) to calculate the number of disease cases over different time periods.
Rationale for Mean in Epidemiological Surveillance
When tracking disease cases across multiple time periods, the mean provides the most appropriate measure of central tendency for calculating average case counts. The epidemiologist has 14 different numbers representing cases over different periods, and needs to determine the typical or average number of cases occurring.
Why Mean is the Correct Choice
The mean calculates the arithmetic average by summing all case counts and dividing by the number of time periods, providing the expected average number of cases per period 1.
Epidemiological surveillance data typically uses mean values for comparing current disease occurrence against historical averages, as demonstrated in the CDC's notifiable disease reporting where "mean of 15 4-week totals" serves as the baseline comparison 1.
The mean is the standard measure for incidence calculations in epidemiology, representing the average occurrence of new cases during specified time periods 2, 3.
Why Other Options Are Incorrect
Mode (Option B) identifies the most frequently occurring value, which is inappropriate when you need to calculate total or average case burden across time periods 4.
Median (Option C) represents the middle value when data are ordered, which is more appropriate for skewed distributions or when describing incubation periods, not for calculating average case counts 4.
Range (Option D) only describes the spread between minimum and maximum values, providing no information about the average or typical number of cases 4.
Practical Application
The CDC's surveillance tables consistently report median values for weekly case counts alongside maximum values, then use the mean for calculating ratios comparing current totals to historical averages 1. This demonstrates that while median may describe weekly variation, the mean remains the standard for calculating expected case numbers over time.
For disease surveillance and public health planning, knowing the average (mean) number of cases allows epidemiologists to allocate resources, detect outbreaks (when current cases exceed the mean), and establish baseline disease occurrence 2, 3.