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Efficient national surveillance for health-care-associated infections
Authors:Bram A D van Bunnik  Mariano Ciccolini  Cheryl L Gibbons  Giles Edwards  Ross Fitzgerald  Paul R McAdam  Melissa J Ward  Ian F Laurenson  Mark E J Woolhouse
Affiliation:1. Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, UK;2. Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands;3. Microbiology Department, Scottish MRSA Reference Laboratory, Glasgow, UK;4. The Roslin Institute and Edinburgh Infectious Diseases, University of Edinburgh, Edinburgh, UK;5. Scottish Mycobacteria Reference Laboratory, Department of Laboratory Medicine, Royal Infirmary of Edinburgh, Edinburgh, UK
Abstract:BackgroundThe detection of novel health-care-associated infections as early as possible is an important public health priority. However, no evidence base exists 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.MethodsUsing hospital admission data from the year 2007, we modelled the spread of a pathogen among a network of hospitals connected by patient movements using a hospital-based susceptible-infectious model. We compared the existing surveillance system in Scotland with a gold standard (a putative optimal selection algorithm) to determine its efficiency and to see whether it is beneficial to alter the number and choice of hospitals in which to concentrate surveillance effort.FindingsWe validated our model by demonstrating that it accurately predicted the risk of meticillin-resistant cases of Staphylococcus aureus bacteraemia in hospitals in Scotland in 2007. Furthermore, the model predicted that relying solely on the 29 (out of 182) sentinel hospitals that currently contribute most of the national surveillance effort results in an average detection time (time until first appearance of the pathogen in a hospital) of 117 days. This detection time could be reduced to 87 days by optimal selection of the same number of hospitals. Alternatively, the same detection time (117 days) can be achieved with just 22 optimally selected hospitals. Increasing the number of sentinel hospitals to 38 (teaching and general hospitals) reduced detection time by 43 days; a decrease to seven sentinel hospitals (all teaching hospitals) increased detection time substantially to 268 days.InterpretationOur results show that the present surveillance system used in Scotland is not optimal in detecting novel pathogens compared with 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 health-care-associated infections for minimum effort.FundingThis research received funding from the European Union Seventh Framework Programme (FP7-HEALTH-2011-single-stage): Evolution and Transfer of Antibiotic Resistance (EvoTAR).
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