Efficient national surveillance for health-care-associated infections.

BACKGROUND: Detecting novel healthcare-associated infections (HCAI) as early as possible is an important public health priority. However, there is currently no evidence base to guide the design of efficient and reliable surveillance systems. Here we address this issue in the context of a novel pathogen spreading primarily between hospitals through the movement of patients. METHODS: Using a mathematical modelling approach we compare the current surveillance system for a HCAI that spreads primarily between hospitals due to patient movements as it is implemented in Scotland with a gold standard to determine if the current system is maximally efficient or whether it would be beneficial to alter the number and choice of hospitals in which to concentrate surveillance effort. RESULTS: We validated our model by demonstrating that it accurately predicts the risk of meticillin-resistant Staphylococcus aureus bacteraemia cases in Scotland. Using the 29 (out of 182) sentinel hospitals that currently contribute most of the national surveillance effort results in an average detection time of 117 days. A reduction in detection time to 87 days is possible by optimal selection of 29 hospitals. Alternatively, the same detection time (117 days) can be achieved using just 22 optimally selected hospitals. Increasing the number of sentinel hospitals to 38 (teaching and general hospitals) reduces detection time by 43 days; however decreasing the number to seven sentinel hospitals (teaching hospitals) increases detection time substantially to 268 days. CONCLUSIONS: Our results show that the current surveillance system as it is used in Scotland is not optimal in detecting novel pathogens when compared to a gold standard. However, efficiency gains are possible by better choice of sentinel hospitals, or by increasing the number of hospitals involved in surveillance. Similar studies could be used elsewhere to inform the design and implementation of efficient national, hospital-based surveillance systems that achieve rapid detection of novel HCAIs for minimal effort.

Time-Scaled Evolutionary Analysis of the Transmission and Antibiotic Resistance Dynamics of Staphylococcus aureus Clonal Complex 398.

Staphylococcus aureus clonal complex 398 (CC398) is associated with disease in humans and livestock, and its origins and transmission have generated considerable interest. We performed a time-scaled phylogenetic analysis of CC398, including sequenced isolates from the United Kingdom (Scotland), along with publicly available genomes. Using state-of-the-art methods for mapping traits onto phylogenies, we quantified transitions between host species to identify sink and source populations for CC398 and employed a novel approach to investigate the gain and loss of antibiotic resistance in CC398 over time. We identified distinct human- and livestock-associated CC398 clades and observed multiple transmissions of CC398 from livestock to humans and between countries, lending quantitative support to previous reports. Of note, we identified a subclade within the livestock-associated clade comprised of isolates from hospital environments and newborn babies, suggesting that livestock-associated CC398 is capable of onward transmission in hospitals. In addition, our analysis revealed significant differences in the dynamics of resistance to methicillin and tetracycline related to contrasting historical patterns of antibiotic usage between the livestock industry and human medicine. We also identified significant differences in patterns of gain and loss of different tetracycline resistance determinants, which we ascribe to epistatic interactions between the resistance genes and/or differences in the modes of inheritance of the resistance determinants.

Genome-wide single nucleotide polymorphism-based assay for high-resolution epidemiological analysis of the methicillin-resistant Staphylococcus aureus hospital clone EMRSA-15.

The EMRSA-15 clone is a major cause of nosocomial methicillin-resistant Staphylococcus aureus (MRSA) infections in the UK and elsewhere but existing typing methodologies have limited capacity to discriminate closely related strains, and are often poorly reproducible between laboratories. Here, we report the design, development and validation of a genome-wide single nucleotide polymorphism (SNP) typing method and compare it to established methods for typing of EMRSA-15. In order to identify discriminatory SNPs, the genomes of 17 EMRSA-15 strains, selected to represent the breadth of genotypic and phenotypic diversity of EMRSA-15 isolates in Scotland, were determined and phylogenetic reconstruction was carried out. In addition to 17 phylogenetically informative SNPs, five binary markers were included to form the basis of an EMRSA-15 genotyping assay. The SNP-based typing assay was as discriminatory as pulsed-field gel electrophoresis, and significantly more discriminatory than staphylococcal protein A (spa) typing for typing of a representative panel of diverse EMRSA-15 strains, isolates from two EMRSA-15 hospital outbreak investigations, and a panel of bacteraemia isolates obtained in healthcare facilities in the east of Scotland during a 12-month period. The assay is a rapid, and reproducible approach for epidemiological analysis of EMRSA-15 clinical isolates in Scotland. Unlike established methods the DNA sequence-based method is ideally suited for inter-laboratory comparison of identified genotypes, and its flexibility lends itself to supplementation with additional SNPs or markers for the identification of novel S. aureus strains in other regions of the world.