The purpose of this study is to determine insofar as possible the role of perinatal infections in the production of fetal damage. To accomplish this, clinical data and a large number of serial serum specimens have been obtained from the 58,000 women and their children in the Collaborative Perinatal Project. Now that the project is complete, the "core" study of perinatal infections involves three main approaches: l) clinical infections; 2) subclinical infections detected serologically using abnormals and matched controls; and 3) high risk children with elevated IgM levels. Special supplemental investigations included the epidemiology of infections and the frequency of congenital toxoplasmosis. Serum antibody titers, IgM values, plus clinical findings are being used to identify infected infants at risk for perinatal damage. Specific tests are then applied for identification of the infection. The data indicate that congenital toxoplasmosis is rare. Special studies of specific infections are also in progress including: hepatitis, infectious mononucleosis, pneumonia, varicella-zoster, and condylomata. The frequency of clinically recognizing infections during pregnancy was determined and geographic variation was demonstrated. Serological tests were used to document certain diseases. The frequency of confirmed clinical cases per l0,000 were: rubella, 8; rubeola, 0.6; mumps, 10; varicella-zoster, 5. The epidemiology and clinical findings associated with infections were studied using serological methods. This has provided data on the frequencies of infections such as cytomegalovirus, herpes simplex, mumps, rubeola, respiratory syncytial virus, and others. The study of abnormal pregnancies and matched controls is in progress using serological methods. A number of specific studies have been reported on infections including rubella, neonatal meningitis, cytomegalovirus, maternal urinary tract infections, and toxoplasmosis. Further testing is now being completed employing more sophisticated laboratory methods and more complete data analysis.