An analysis of AIDS incidence data by clustering trends.
AIDS incidence trends vary greatly among geographic areas in the United States. We define clusters of areas within which AIDS incidence trends are similar, as areas within a cluster may have similar human immunodeficiency virus epidemic patterns and thus may lead to similar prevention/intervention strategies. Methods of exploratory data analysis are used to define such clusters from reported quarterly AIDS incidence to December 1990 (adjusted for estimated reporting delays) in homosexual and bisexual men not using intravenous drugs in 39 metropolitan statistical areas (MSAs) in the United States. After smoothing AIDS incidence in each MSA, we define groups from cluster analysis based on a measure of similarity between pairs of MSAs. A log-linear model gives estimates of the scale factors and the common trend for the MSAs in each group. Alternative metrics and simulated data suggest that the clustering is fairly robust to variations in AIDS incidence data. The resulting clusters separate MSAs with different trends, for example, MSAs in which AIDS incidence shows signs of reaching a plateau are separated from MSAs in which incidence continues to increase rapidly.
Kafadar
K
K
Biometry Branch, National Cancer Institute, Bethesda, Maryland 20892.
Karon
J M
JM
D000163:Acquired Immunodeficiency Syndrome / Q000453:epidemiology* / Q000517:prevention & control; D000465:Algorithms; D015982:Bias; D001727:Bisexuality; D016000:Cluster Analysis; D003663:Decision Trees; D006716:Homosexuality; D006801:Humans; D015994:Incidence; D016014:Linear Models; D008297:Male; D011159:Population Surveillance; D011635:Public Health Administration; D012111:Residence Characteristics; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014481:United States / Q000453:epidemiology; D014505:Urban Population