Genetic distances for the study of infectious disease epidemiology.

Abstract

Molecular epidemiologic studies of infectious pathogens 1) generate genetic patterns from a collection of microorganisms, 2) compare the degree of similarity among these patterns, and 3) infer from these similarities infectious disease transmission patterns. The authors propose a quantitative approach using genetic distances to study the degree of similarity between patterns. Benefits of such genetic distance calculations are illustrated by an analysis of standard DNA fingerprints of Mycobacterium tuberculosis in San Francisco collected during the period 1991-1997. Graphical representation of genetic distances can assist in determining if the disappearance of a specific pattern in a community is due to interruption of transmission or ongoing evolution of the microorganism's fingerprint. Genetic distances can also compensate for varying information content derived by DNA fingerprints of contrasting pattern complexity. To study demographic and clinical correlates of transmission, the authors calculated the smallest genetic distance from each patient sample to all other samples. With correlation of genetic distances and nearest genetic distances with previously understood notions of the epidemiology of M. tuberculosis in San Francisco, factors influencing transmission are investigated.