An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters.

Assessment tools in support of epidemiological investigation of airborne dispersion of pathogens.

Human health threats posed by airborne pathogens are difficult to handle for healthcare responders due to the fact that the contaminated area is not immediately recognizable. By means of wind dispersion modeling, it is possible to estimate the extent and geographical position of hazardous areas and health impact. Contemporary modeling tools can run on standard PCs, with short processing time and with easy-to-use interfaces. This enables health professionals without modeling experience to assess consequences of dispersion incidents, for example, from accidental releases from industries, shedding of pathogens from infectious animals or humans, as well as intentional releases caused by terrorist activity. Dispersion assessments can provide response managers with a chance to get on top of events. In the absence of modeling, reliable estimates of hazard areas may not be available until no earlier than the appearance of the first cases or after time-consuming sampling and laboratory analysis. In this article, the authors describe the concept of using wind dispersion assessments in epidemiological field investigations of naturally occurring disease outbreaks, as well as for bioterror scenarios. They describe the specifications of user friendly and real-time functional wind dispersion modeling systems that can serve as decision support tools during outbreak investigations and outline some of the currently available software packages.

[Disease outbreak monitoring system based on ambulance transport data]. / Monitorering af sygdomsudbrud på basis af akutte medicinske ambulancekørsler.

INTRODUCTION: Disease outbreak monitoring is relevant not only for naturally occurring diseases but also for detecting a biological terror event. Surveillance systems are already operational in Denmark, but none of these has the high update frequencies necessary for early warning, and the majority monitor specific infectious diseases. MATERIALS AND METHODS: An early-warning system for detection of disease outbreaks in Denmark based on ambulance transport frequency was developed and tested employing a biological outbreak scenario. RESULTS: The system, termed "Bioalarm", demonstrated an ability to adapt to minor statistical variations due to, e.g., mild influenza epidemics and at the same time to elicit an early warning in the event of a outbreak consistent with a bioterrorist attack. CONCLUSION: Bioalarm not only is relevant for early warning of a disease outbreak as a result of a biological attack but also facilitates early detection of naturally occurring outbreaks.