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Infect Genet Evol. 2006 Nov 30; [Epub ahead of print]

Perez-Losada M, Crandall KA, Zenilman J, Viscidi RP

Department of Integrative Biology, Brigham Young University, Provo, UT, United States


Molecular evolutionary studies can provide insights into the spread of infectious diseases and inform infection control measures. We performed a population genetic analysis of gonococcal isolates obtained over a 15-year interval in Baltimore, MD, where gonorrhea is highly prevalent. Categorical analysis of genetic differentiation revealed temporal structuring of the gonococcal population. The use of a new method to determine the historical demography of Neisseria gonorrhoeae from sequence data showed a strong correlation with trends in the number of reported cases of N. gonorrhoeae. The historical trends may also reflect the influence of social and demographic factors and the impact of antimicrobial resistance on the molecular epidemiology of gonorrhea in Baltimore over the past 2 decades. The strong correlation between the population genetic inferences over the last 20 years and the demographic data collected over the same period demonstrates the utility of these approaches for the accurate inference of complex population dynamics using multilocus sequence data. The real time application of population genetic analysis can provide sentinel data on gonococcal prevalence, antibiotic resistance patterns and changing epidemiology of gonococcal infection


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