A number of high-resolution molecular typing systems have been developed in recent years. Their availability raises the new issues of selecting the method (s) best suited for a particular purpose and interpreting and communicating typing results. Most of the currently available methods are comparative only: they allow testing of a sample of isolates for delineation of those closely related from those markedly different in genomic backgrounds. This approach is adequate for outbreak investigation, allowing determination of clonal spread in a microenvironment and identification of the source of infection. Comparative methods with sufficient resolution for most pathogens include restriction fragment-length polymorphism (RFLP), pulsed-field gel electrophoresis (PFGE), and arbitrarily primed and randomly amplified polymorphic DNA-polymerase chain reaction (PCR) analysis. For surveillance systems, monitoring clonal spread and prevalence in populations over extended periods of time requires library typing systems. These must be standardized, must have a high throughput, and must use a uniform nomenclature. Promising or validated methods include serotyping, insertion sequence fingerprinting, ribotyping, PFGE, amplified fragment-length polymorphism (AFLP), infrequent-restriction-site amplification PCR, interrepetitive element PCR typing (rep-PCR) and PCR-RFLP of polymorphic loci. PCR methods generating arrays of size-specific amplicons (AFLP, rep-PCR) can be more reproducibly analyzed by using denaturing polyacrylamide gel or capillary electrophoresis with automated laser detection. Binary probe typing systems appear optimal and should be enhanced further through use of DNA chip technology. In these systems, amplification of polymorphic regions is followed by solid-phase hybridization with a reference panel of sequence-variant specific probes. The resulting binary type results allow determination of reproducible, numeric profiles. However, interpretation and nomenclature of typing results for large-scale surveillance purposes still require a better understanding of population structure and microevolution of most microbial pathogens.