Cluster sampling can produce estimates of disease prevalence that are more variable than those from simple random sampling. This variance inflation or "design effect" depends on the prevalence of disease, the cluster sizes, and the magnitude of disease association within clusters. Design effects from prior surveys may not be appropriate for a planned survey if these components differ. We estimated within-cluster associations using pairwise odds ratios, which are more portable than design effects because they do not depend on the cluster sizes. Within-village pairwise odds ratios and design effects were estimated for fever and cough from four studies in Africa and Asia. Odds ratio ranged from 1.04 to 1.34 and 1.03 to 1.24, respectively. Design effects ranged from 2.35 to 6.80 for fever and 1.99 to 7.39 for cough. The design effect was more affected by cluster size and odds ratio than by variation in cluster size for a given sample size.