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The eigenfrequencies of a bridge are influenced by the environment and by structural integrity. The task of damage identification is to conclude structural integrity from measured eigenfrequencies. Environmental frequency changes are a negative effect that hinders reliable damage identification. In this paper, it is experimentally shown how temperature and traffic load affect the eigenfrequencies, and reduction of this effect using a frequency prediction model is presented. Random variations are described using a probability density function, and a damage indicator based on this function is proposed. The paper addresses the issue of reliability of damage detection considering random and systematic errors that are present in the eigenfrequencies extracted from measurements. Various damage scenarios are presented, both with identifiable and non-identifiable damages. [ABSTRACT FROM AUTHOR]