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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. [ABSTRACT FROM AUTHOR]

Isogenic bacterial populations can consist of cells displaying heterogeneous physiological traits. Small regulatory RNAs (sRNAs) could affect this heterogeneity since they act by fine-tuning mRNA or protein levels to coordinate the appropriate cellular behavior. Here we show that the sRNA RnaC/S1022 from the Gram-positive bacterium Bacillus subtilis can suppress exponential growth by modulation of the transcriptional regulator AbrB. Specifically, the post-transcriptional abrB-RnaC/S1022 interaction allows B. subtilis to increase the cell-to-cell variation in AbrB protein levels, despite strong negative autoregulation of the abrB promoter. This behavior is consistent with existing mathematical models of sRNA action, thus suggesting that induction of protein expression noise could be a new general aspect of sRNA regulation. Importantly, we show that the sRNA-induced diversity in AbrB levels generates heterogeneity in growth rates during the exponential growth phase. Based on these findings, we hypothesize that the resulting subpopulations of fast- and slow-growing B. subtilis cells reflect a bet-hedging strategy for enhanced survival of unfavorable conditions.

Antibiotic resistance is a worldwide threat to health care as it impairs the effective treatment of bacterial infections. Measures against the spread of resistance are mainly focused on individual health care institutions as these are viewed as the main source of resistance. However, health care institutions are not completely independent in their control of the prevalence of resistance, as movement of patients between hospitals and care institutions can induce movement of resistant micro-organisms. In other words, antibiotic resistance follows the flow of patients. Mapping this flow of patients results in a network that includes all health care institutions, and has a distinctive modular structure. Patients are moved primarily within regions, much less so between regions. We argue that the structure of this health care network should be used to design efficient and effective control strategies. To this end, we advocate (a) regional coordination of control measures, (b) differentiation of investment in infection prevention according to the network position of the institution, and, ((c) setting up sentinel surveillance based on the health care network.)

Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort.

Results from microbiological and epidemiological investigations, as well as mathematical modelling, show that the transmission dynamics of nosocomial pathogens, especially of multiple antibiotic-resistant bacteria, is not exclusively amenable to single-hospital infection prevention measures. Crucially, their extent of spread depends on the structure of an underlying "healthcare network", as determined by inter-institutional referrals of patients. The current trend towards centralized healthcare systems favours the spread of hospital-associated pathogens, and must be addressed by coordinated regional or national approaches to infection prevention in order to maintain patient safety. Here we review recent advances that support this hypothesis, and propose a "next-generation" network-approach to hospital infection prevention and control., (Copyright © 2013 Elsevier GmbH. All rights reserved.)

Background: Hypoxemia in acute lung injury/acute respiratory distress syndrome (ALI/ARDS) patients represents a common finding in the intensive care unit (ICU) and frequently does not respond to standard ventilatory techniques., Objective: To study whether the early short-term application of high-frequency percussive ventilation (HFPV) can improve gas exchange in hypoxemic patients with ALI/ARDS or many other conditions in comparison to conventional ventilation (CV) using the same mean airway pressure (P(aw)), representing the main determinant of oxygenation and hemodynamics, irrespective of the mode of ventilation., Methods: Thirty-five patients not responding to CV were studied. During the first 12 h after admission to the ICU the patients underwent CV. Thereafter HFPV was applied for 12 h with P(aw) kept constant. They were then returned to CV. Gas exchange was measured at: 12 h after admission, every 4 h during the HFPV trial, 1 h after the end of HFPV, and 12 h after HFPV. Thirty-five matched patients ventilated with CV served as the control group (CTRL)., Results: PaO(2)/FiO(2) and the arterial alveolar ratio (a/A PO(2)) increased during HFPV treatment and a PaO(2)/FiO(2) steady state was reached during the last 12 h of CV, whereas both did not change in CTRL. PaCO(2) decreased during the first 4 h of HFPV, but thereafter it remained unaltered; PaCO(2) did not vary in CTRL. Respiratory system compliance increased after HFPV., Conclusions: HFPV improved gas exchange in patients who did not respond to conventional treatment. This improvement remained unaltered until 12 h after the end of HFPV., (Copyright © 2011 S. Karger AG, Basel.)