Subject(s)
Cross Infection , Mycobacterium tuberculosis , Tuberculosis, Pulmonary , Antitubercular Agents , Genotype , HumansABSTRACT
Mycobacterium tuberculosis (Mtb) exhibits a structured phylogeographic distribution worldwide linked with human migrations. We sought to infer how the interactions between distinct human populations shape the global population structure of Mtb on a regional scale. We applied the recently described timescaled haplotypic density (THD) technique on 638 minisatellite-based Mtb genotypes from French tuberculosis patients. THD with a long-term (200 y) timescale indicated that Mtb population in France had been mostly influenced by interactions with Eastern and Southern Europe and, to a lesser extent, Northern and Middle Africa, consistent with historical migrations favored by geographic proximity or commercial exchanges with former French colonies. Restricting the timescale to 20 y, THD identified a sustained influence of Northern Africa, but not Europe where tuberculosis incidence decreased sharply. Evolving interactions between human populations, thus, measurably influence the local population structure of Mtb. Relevant information on such interactions can be inferred using THD from Mtb genotypes.
Subject(s)
Human Migration/statistics & numerical data , Mycobacterium tuberculosis/genetics , Phylogeography/statistics & numerical data , Tuberculosis/microbiology , Africa, Northern/epidemiology , Cross-Sectional Studies , DNA, Bacterial/genetics , DNA, Bacterial/isolation & purification , Datasets as Topic , France/epidemiology , Haplotypes , Humans , Incidence , Minisatellite Repeats/genetics , Mycobacterium tuberculosis/isolation & purification , Retrospective Studies , Tuberculosis/epidemiology , Tuberculosis/transmissionABSTRACT
The transmission dynamics of tuberculosis involves complex interactions of socio-economic and, possibly, microbiological factors. We describe an analytical framework to infer factors of epidemic success based on the joint analysis of epidemiological, clinical and pathogen genetic data. We derive isolate-specific, genetic distance-based estimates of epidemic success, and we represent success-related time-dependent concepts, namely epidemicity and endemicity, by restricting analysis to specific time scales. The method is applied to analyze a surveillance-based cohort of 1,641 tuberculosis patients with minisatellite-based isolate genotypes. Known predictors of isolate endemicity (older age, native status) and epidemicity (younger age, sputum smear positivity) were identified with high confidence (P < 0.001). Long-term epidemic success also correlated with the ability of Euro-American and Beijing MTBC lineages to cause active pulmonary infection, independent of patient age and country of origin. Our results demonstrate how important insights into the transmission dynamics of tuberculosis can be gained from active surveillance data.
