Early warning systems augmented by bacterial genomics

Abstract

The number of microbial threats -in the form of newly identified pathogens, infections crossing the species barrier to people, diseases adapting to new environments, transmissible drug-resistance genes and microbial agents appearing in more virulent forms -has multiplied to an unprecedented degree. The epidemiology of well-known infectious diseases has also been changing due to the globalisation of trade and in response to immunisation campaigns. This evolving epidemiology presents new challenges to countries' healthcare systems, in terms of both understanding and monitoring of determinants of infections, as well as in terms of service provision and the implementation of appropriate prevention measures. In this article we discuss the concepts of early warning systems and genome sequencing for public health laboratory surveillance and outbreak detection and response. The added value of these new means of surveillance can be seen when clinical and public health laboratory data is harmonised, aggregated and shared. Why early warning system are neededEvidence suggests that traditional surveillance systems are vulnerable to the incomplete and delayed reporting of public health threats, highlighted by recent outbreaks. Many outbreaks have been characterised by delayed recognition and/or public health response.

Scientific Opinion on the evaluation of molecular typing methods for major food-borne microbiological hazards and their use for attribution modelling, outbreak investigation and scanning surveillance: Part 2 (surveillance and data management activities)

“…The increased use of genome sequence-based techniques (EFSA, 2013a) will potentially widen the use of monitoring data beyond their traditional purposes (Segata et al, 2013). As an example, the collection of sequence data from food-borne bacterial genomes is likely to assist with the early identification of organisms with epidemic potential (Sintchenko and Holmes, 2014) as well as contributing to the accuracy of outbreak detection and investigation (Leopold et al, 2014).…”