Statistical Measure for Disease Case Tracking
The mean (A) is the most appropriate statistical measure to calculate the average number of disease cases over different periods of time. 1
Rationale for Mean in Epidemiological Surveillance
The mean provides the arithmetic average that is essential for epidemiological tracking and comparison of disease burden across time periods. 1
The CDC's Morbidity and Mortality Weekly Report consistently uses mean values when comparing current disease case totals to historical data, as demonstrated in their surveillance methodology where they calculate "the ratio of current 4-week total to mean of 15 4-week totals from previous, comparable, and subsequent 4-week periods for the past 5 years." 1
Mean calculations allow for direct comparison of disease incidence across different time periods, which is fundamental to identifying trends, outbreaks, and changes in disease patterns. 2, 3
For epidemiological surveillance purposes, the mean serves as the baseline measure against which current case counts are compared to determine if disease occurrence is within expected limits or represents an outbreak. 1
Why Other Measures Are Less Appropriate
Mode (B) is inappropriate because it only identifies the most frequently occurring value, which provides no information about the average disease burden or trends over time. 2
Median (C) would be more appropriate for skewed distributions or when describing incubation periods, but for calculating average case counts across time periods, the mean is standard practice in epidemiological surveillance. 4
Range (D) only describes the spread between minimum and maximum values and provides no information about central tendency or average case occurrence. 4, 2
Practical Application
When tracking 14 different case count values across time periods, sum all values and divide by 14 to obtain the mean, which represents the average disease burden. 1
This mean value becomes the reference point for determining if current case counts represent normal variation or a significant deviation requiring public health intervention. 1
The mean is particularly useful when calculating incidence rates and comparing disease frequency across populations or geographic areas. 2, 3, 5