Lean back and wait for the alarm? Testing an automated alarm system for nosocomial outbreaks to provide support for infection control professionals

INTRODUCTION: Outbreaks of communicable diseases in hospitals need to be quickly detected in order to enable immediate control. The increasing digitalization of hospital data processing offers potential solutions for automated outbreak detection systems (AODS). Our goal was to assess a newly developed AODS. METHODS: Our AODS was based on the diagnostic results of routine clinical microbiological examinations. The system prospectively counted detections per bacterial pathogen over time for the years 2016 and 2017. The baseline data covers data from 2013-2015. The comparative analysis was based on six different mathematical algorithms (normal/Poisson and score prediction intervals, the early aberration reporting system, negative binomial CUSUMs, and the Farrington algorithm). The clusters automatically detected were then compared with the results of our manual outbreak detection system. RESULTS: During the analysis period, 14 different hospital outbreaks were detected as a result of conventional manual outbreak detection. Based on the pathogens' overall incidence, outbreaks were divided into two categories: outbreaks with rarely detected pathogens (sporadic) and outbreaks with often detected pathogens (endemic). For outbreaks with sporadic pathogens, the detection rate of our AODS ranged from 83% to 100%. Every algorithm detected 6 of 7 outbreaks with a sporadic pathogen. The AODS identified outbreaks with an endemic pathogen were at a detection rate of 33% to 100%. For endemic pathogens, the results varied based on the epidemiological characteristics of each outbreak and pathogen. CONCLUSION: AODS for hospitals based on routine microbiological data is feasible and can provide relevant benefits for infection control teams. It offers in-time automated notification of suspected pathogen clusters especially for sporadically occurring pathogens. However, outbreaks of endemically detected pathogens need further individual pathogen-specific and setting-specific adjustments

Quantifying health risks in wastewater irrigation

The guidelines developed by the World Health Organization for the safe use of wastewater in agriculture are based on a tolerable additional disease burden of 10-6 disability-adjusted life year loss per person per year, equivalent to rotavirus disease and infection risks of approximately 10-4 and 10-3 per person per year, respectively. The combination of standard quantitative microbial risk analysis techniques and 10,000-trial Monte Carlo risk simulations, using ranges of parameter values that reflect real life, are then used to determine the minimum required pathogen reductions for restricted and unrestricted irrigation which ensure that the risks are not exceeded. For unrestricted irrigation the required pathogen reduction is 6- 7 log10 units and for restricted irrigation 3- 4 log10 units. For both restricted and unrestricted irrigation wastewater treatment has to achieve a 3-4-log10 unit pathogen reduction, and in the case of unrestricted irrigation this has to be supplemented by a further 3-4-log10 unit pathogen reduction provided by post-treatment, but pre-ingestion, health protection control measures, such as pathogen die-off between the last irrigation and consumption (0.5- 2 log10 unit reduction per day, depending on ambient temperature) and produce washing in clean water (1 log10 unit reduction). Wastewaters used for both restricted and unrestricted irrigation also have to contain no more than 1 human intestinal nematode egg per liter; if children under the age of 15 are exposed then additional measures are required such as regular deworming at home or at school

Enteropathogen survival in soil from different land-uses is predominantly regulated by microbial community composition

peer-reviewedMicrobial enteropathogens can enter the environment via landspreading of animal slurries and manures. Biotic interactions with the soil microbial community can contribute to their subsequent decay. This study aimed to determine the relative impact of biotic, specifically microbial community structure, and physico-chemical properties associated with soils derived from 12 contrasting land-uses on enteropathogen survival. Phenotypic profiles of microbial communities (via phospholipid fatty acid (PLFA) profiling), and total biomass (by fumigation-extraction), in the soils were determined, as well as a range of physicochemical properties. The persistence of Salmonella Dublin, Listeria monocytogenes, and Escherichia coli was measured over 110 days within soil microcosms. Physicochemical and biotic data were used in stepwise regression analysis to determine the predominant factor related to pathogen-specific death rates. Phenotypic structure, associated with a diverse range of constituent PLFAs, was identified as the most significant factor in pathogen decay for S. Dublin, L. monocytogenes, non-toxigenic E. coli O157 but not for environmentally-persistent E. coli. This demonstrates the importance of entire community-scale interactions in pathogen suppression, and that such interactions are context-specific

Pathogen-reactive T helper cell analysis in the pig

There is growing interest in studying host-pathogen interactions in human-relevant large animal models such as the pig. Despite the progress in developing immunological reagents for porcine T cell research, there is an urgent need to directly assess pathogen-specific T cells-an extremely rare population of cells, but of upmost importance in orchestrating the host immune response to a given pathogen. Here, we established that the activation marker CD154 (CD40L), known from human and mouse studies, identifies also porcine antigen-reactive CD4(+) T lymphocytes. CD154 expression was upregulated early after antigen encounter and CD4(+)CD154(+) antigen-reactive T cells coexpressed cytokines. Antigen-induced expansion and autologous restimulation enabled a time-and dose-resolved analysis of CD154 regulation and a significantly increased resolution in phenotypic profiling of antigen-responsive cells. CD154 expression identified T cells responding to staphylococcal Enterotoxin B superantigen stimulation as well as T cells responding to the fungus Candida albicans and T cells specific for a highly prevalent intestinal parasite, the nematode Ascaris suum during acute and trickle infection. Antigen-reactive T cells were further detected after immunization of pigs with a single recombinant bacterial antigen of Streptococcus suis only. Thus, our study offers new ways to study antigen-specific T lymphocytes in the pig and their contribution to host-pathogen interactions

Tracking Foodborne Pathogens from Farm to Table: Data Needs to Evaluate Control Options

Food safety policymakers and scientists came together at a conference in January 1995 to evaluate data available for analyzing control of foodborne microbial pathogens. This proceedings starts with data regarding human illnesses associated with foodborne pathogens and moves backwards in the food chain to examine pathogen data in the processing sector and at the farm level. Of special concern is the inability to link pathogen data throughout the food chain. Analytical tools to evaluate the impact of changing production and consumption practices on foodborne disease risks and their economic consequences are presented. The available data are examined to see how well they meet current analytical needs to support policy analysis. The policymaker roundtable highlights the tradeoffs involved in funding databases, the economic evaluation of USDA's Hazard Analysis Critical Control Point (HACCP) proposal and other food safety policy issues, and the necessity of a multidisciplinary approach toward improving food safety databases.food safety, cost benefit analysis, foodborne disease risk, foodborne pathogens, Hazard Analysis Critical Control Point (HACCP), probabilistic scenario analysis, fault-tree analysis, Food Consumption/Nutrition/Food Safety,

Search for alternate hosts of the coconut Cape Saint Paul Wilt Disease pathogen

Lethal Yellowing disease locally called Cape Saint Paul wilt disease (CSPWD) is the bane of the coconut industry in Ghana and is caused by a phytoplasma. In Ghana, there are areas where the disease has re-infected re-plantings long after decimating all the palms in the area. This brings to the fore the possibility of alternate hosts in the spread of the disease because the pathogen is an obligate parasite. In this work, a number of plants were screened for their host status to the CSPWD pathogen. The presence of phytoplasmas in these plants was tested by polymerase chain reaction analysis using universal phytoplasma primers P1/P7 and CSPWD-specific primers G813/GAKSR. Although Desmodium adscendens tested positive to the CSPWD-specific primers, cloning and sequencing did not confirm it as an alternate host. The identification of alternate hosts will help us to evolve sound control strategies against the spread of the disease. (Résumé d'auteur

Cronobacter, the emergent bacterial pathogen Enterobacter sakazakii comes of age; MLST and whole genome sequence analysis

Background: Following the association of Cronobacter spp. to several publicized fatal outbreaks in neonatal intensive care units of meningitis and necrotising enterocolitis, the World Health Organization (WHO) in 2004 requested the establishment of a molecular typing scheme to enable the international control of the organism. This paper presents the application of Next Generation Sequencing (NGS) to Cronobacter which has led to the establishment of the Cronobacter PubMLST genome and sequence definition database (http://pubmlst.org/ cronobacter/) containing over 1000 isolates with metadata along with the recognition of specific clonal lineages linked to neonatal meningitis and adult infections Results: Whole genome sequencing and multilocus sequence typing (MLST) has supports the formal recognition of the genus Cronobacter composed of seven species to replace the former single species Enterobacter sakazakii. Applyingthe 7-loci MLST scheme to 1007 strains revealed 298 definable sequence types, yet only C. sakazakii clonal complex 4 (CC4) was principally associated with neonatal meningitis. This clonal lineage has been confirmed using ribosomal-MLST (51-loci) and whole genome-MLST (1865 loci) to analyse 107 whole genomes via the Cronobacter PubMLST database. This database has enabled the retrospective analysis of historic cases and outbreaks following re-identification of those strains. Conclusions: The Cronobacter PubMLST database offers a central, open access, reliable sequence-based repository for researchers. It has the capacity to create new analysis schemes 'on the fly', and to integrate metadata (source, geographic distribution, clinical presentation). It is also expandable and adaptable to changes in taxonomy, and able to support the development of reliable detection methods of use to industry and regulatory authorities. Therefore it meets the WHO (2004) request for the establishment of a typing scheme for this emergent bacterial pathogen. Whole genome sequencing has additionally shown a range of potential virulence and environmental fitness traits which may account for the association of C. sakazakii CC4 pathogenicity, and propensity for neonatal CNS

Timing of Pathogen Adaptation to a Multicomponent Treatment

The sustainable use of multicomponent treatments such as combination therapies, combination vaccines/chemicals, and plants carrying multigenic resistance requires an understanding of how their population-wide deployment affects the speed of the pathogen adaptation. Here, we develop a stochastic model describing the emergence of a mutant pathogen and its dynamics in a heterogeneous host population split into various types by the management strategy. Based on a multi-type Markov birth and death process, the model can be used to provide a basic understanding of how the life-cycle parameters of the pathogen population, and the controllable parameters of a management strategy affect the speed at which a pathogen adapts to a multicomponent treatment. Our results reveal the importance of coupling stochastic mutation and migration processes, and illustrate how their stochasticity can alter our view of the principles of managing pathogen adaptive dynamics at the population level. In particular, we identify the growth and migration rates that allow pathogens to adapt to a multicomponent treatment even if it is deployed on only small proportions of the host. In contrast to the accepted view, our model suggests that treatment durability should not systematically be identified with mutation cost. We show also that associating a multicomponent treatment with defeated monocomponent treatments can be more durable than associating it with intermediate treatments including only some of the components. We conclude that the explicit modelling of stochastic processes underlying evolutionary dynamics could help to elucidate the principles of the sustainable use of multicomponent treatments in population-wide management strategies intended to impede the evolution of harmful populations.Comment: 3 figure