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Clostridium difficile surveillance allows outbreaks of cases clustered in time and space to be identified and further transmission prevented. Traditionally, manual detection of groups of cases diagnosed in the same ward or hospital, often followed by retrospective reference laboratory genotyping, has been used to identify outbreaks. However, integrated healthcare databases offer the prospect of automated real-time outbreak detection based on statistically robust methods, and accounting for contacts between cases, including those distant to the ward of diagnosis. Complementary to this, rapid benchtop whole genome sequencing, and other highly discriminatory genotyping, has the potential to distinguish which cases are part of an outbreak with high precision and in clinically relevant timescales. These new technologies are likely to shape future surveillance.

Original publication

DOI

10.1586/14787210.2013.845987

Type

Journal article

Journal

Expert review of anti-infective therapy

Publication Date

11/2013

Volume

11

Pages

1193 - 1205

Addresses

NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, UK.

Keywords

Humans, Clostridium difficile, Clostridium Infections, Disease Outbreaks, Genotype, Genome, Bacterial, Electronic Health Records, Genotyping Techniques, Epidemiological Monitoring