225262 Exact statistics for detecting disease outbreaks in small populations

Monday, November 8, 2010 : 11:35 AM - 11:50 AM

Jack Siegrist , Applied Biomathematics, Setauket, NY
Scott Ferson , Applied Biomathematics, Setauket, NY
Roger Grimson , Applied Biomathematics, Setauket, NY
Jimmie Goode, MS , Applied Biomathematics, Setauket, NY
Detecting outbreaks, structured clusters of events, is a common epidemiological problem, but traditional statistical tests are only valid for asymptotically large sample sizes and are therefore not applicable to rare events in small populations. Simulation studies have shown that the rate of false positives for traditional tests such as the chi-square test or the log-likelihood ratio are routinely much larger than their nominal rates when applied to small data sets. This results in declaring outbreaks more often than warranted, causing both undo alarm and economic losses from unnecessary closures and other interventions. In some cases, however, traditional cluster tests can fail to detect clusters that can be shown by other methods to be statistically significant, and it is difficult to anticipate whether the traditional test will overestimate or underestimate the probability of clustering for a particular situation. We describe statistical methods that can be used to detect outbreaks of rare events in small delimited populations. These tests use combinatorial formulations that yield exact p-values and that cannot violate their nominal Type I error rates. As a result, these tests are reliable whatever the size of the data set, and are especially useful when data sets are extremely small. Different statistics are sensitive to different types of structure, so that comparisons among these tests can provide evidence about the possible processes that generated the clustering. Use of these statistics can help decision-makers take defensible actions to prevent disease outbreaks and determine the causes of disease clusters.

Learning Areas:
Biostatistics, economics
Environmental health sciences
Protection of the public in relation to communicable diseases including prevention or control

Learning Objectives:
Compare statistical methods for determining the presence of a disease outbreak or cluster in small populations. List exact statistical tests and their properties for detection of clustering. Discuss the effective use of these tests for public health decision-making.

Keywords: Outbreaks, Epidemiology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: The material presented represents the results of my work along with the other authors on an NIH-funded project as a part of my employment at Applied Biomathematics.
Any relevant financial relationships? Yes

Name of Organization Clinical/Research Area Type of relationship
Applied Biomathematics Statistical methods Employment (includes retainer)

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 3113.0: Outbreak investigations