4.6 - Evaluation of Surveillance Systems

A disease surveillance system should be simple, flexible and acceptable to the population. For example, to detect hunting-related shooting injuries, the requirements for a hunter to report an episode should not be onerous or many shooting injuries will go unrecorded.. The surveillance system should also be representative of the population and provide a timely alarm. Like a smoke detector without a power source, a surveillance system that is not able to recognize a disease outbreak quickly and accurately is not very useful.

Evaluating the effectiveness of a surveillance system is easiest if there is a ‘gold standard’ that allows the researcher to compare surveillance results to the true condition. If it can be known whether or not the condition is present, a 2 × 2 table can be useful as shown below.

The count of true cases that are detected by the surveillance system is given in cell A. Similarly, cell B contains the count of non-cases that the surveillance system mistakenly considers as disease. The row totals are A + B and C + D, the numbers detected and not detected by surveillance. Given these data, sensitivity and positive predictive value can be calculated.

    Condition Present  
    Yes No
Detected by Surveillance Yes


True Positive


False Positive
A + B


False Negative


True Negative

C + D
    A + C B + D Total

Quantitative Measures

  • Sensitivity: the proportion of true positives that are detected by the surveillance system A/(A+C)
  • Positive Predictive Value: the proportion of true positives among those detected by the surveillance system A/(A+B)

You have now completed reading the course notes for Week 4....show what you have learned in answering this week's discussion question.