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The global surveillance of bacterial pathogens is particularly important for bacteria with diverse and dynamic populations that cause periodic epidemics or pandemics. The isolate characterization methods employed for surveillance should: (1) generate unambiguous data; (2) be readily implemented in a variety of scenarios and be reproducible among laboratories; (3) be scalable and preferably available in a high throughput format; and (4) be cost effective. Multilocus sequence typing (MLST) was designed to meet these criteria and has been implemented effectively for a wide range of microorganisms. The 'Impact of meningococcal epidemiology and population biology on public health in Europe (EU-MenNet)' project had amongst its objectives: (1) to disseminate meningococcal MLST and sequence-based typing throughout Europe by establishing a centre for training and data generation, and (2) to produce a comprehensive Europe-wide picture of meningococcal disease epidemiology for the first time. Data produced from the project have shown the distribution of a relatively small number of STs, clonal complexes and PorA types that account for a large proportion of the disease-associated isolates in Europe. The project demonstrates how molecular typing can be combined with epidemiological data via the Internet for global disease surveillance.

Original publication

DOI

10.1111/j.1574-6976.2006.00056.x

Type

Journal article

Journal

FEMS Microbiol Rev

Publication Date

01/2007

Volume

31

Pages

15 - 26

Keywords

Computational Biology, DNA, Bacterial, Databases, Nucleic Acid, Europe, Humans, Meningococcal Infections, Neisseria meningitidis, Polymerase Chain Reaction, Population Surveillance