Background: Currently, all developed countries include rubella vaccination in their immunization programs, targeting the complete elimination of congenital rubella syndrome (CRS). In the underdeveloped world, where this severely disabling condition still exists, only a few countries have implemented vaccination policies, and almost no data on their effectiveness or on prevalence rates are available. The aims of the present work were to search for the best phenotype to be used as a sentinel for CRS in a large series of malformed newborns and to propose a CRS surveillance system, based only on clinical data.
Methods: A total of 43 infants diagnosed as having CRS were obtained from 19,184 multimalformed infants, ascertained by the Latin-American Collaborative Study of Congenital Malformations, World Health Organization (WHO) Collaborating Centre for the Prevention of Birth Defects (ECLAMC), over 3,883,165 consecutive births, between 1982 and 2003. They were distributed by country and the most frequent birth defects were identified. From the 19,184 multimalformed infants, all cases presenting the birth defects identified were selected. The sensitivity, specificity, and likelihood ratio (LR) in detecting CRS were determined for these birth defects, alone and in combination. The sample size of multimalformed infants required to detect different levels of increase in the rate of CRS was determined for three sentinel phenotypes.
Results: The rate of CRS was highest in Brazil. Based on the best possible combination of sensitivity, specificity, and LR, the dyad comprising eye anomalies and congenital heart defects was shown to be the most appropriate sentinel, with the lowest sample size required, to detect CRS in neonates.
Conclusions: A surveillance system for CRS, based on clinical data in newborns, is being proposed, in an attempt to monitor ongoing vaccination policies, aimed at eliminating CRS in developing countries.