The elbow method can be applied in epidemiological studies to determine the optimal number of clusters when analyzing health data. For instance, when dealing with large datasets concerning disease outbreaks, clustering can help in identifying the regions most affected. By plotting the within-cluster sum of squares (WCSS) against the number of clusters, epidemiologists can identify the point where adding an additional cluster does not significantly improve the model. This optimal point helps in simplifying the data while retaining meaningful insights.
