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Scharlach M.,Niedersachsisches Landesgesundheitsamt | Friedrich A.W.,Universitatsklinikum Groningen
Hygiene + Medizin | Year: 2013

Since some years antimicrobial resistance and health care associated infections are among the most important health problems, and international and national strategies were developed to control them. But the euregional project EurSafety-Health-Net shows, that cross border activities on a regional level also play an important roll for prevention and surveillance. MRSA is the most prominent pathogen for health care associated infections since many years. Initially distribution of MRSA depends on the parameters exposure and disposition as well as their intensity. As a result, the probability of transmission has to be calculated by each health care institution. Because commonly patients have contact with more than one health care institution, heath care cluster have to be indentified and infection prevention has to be harmonized. But for regional health cluster, regional surveillance data is necessary. The example of the Antibiotika- Resistenz-Monitoring in Niedersachsen (ARMIN) shows, that the problem of MRSA differs even within a federal state. To understand the spread of health care associated infections and antimicrobial resistant pathogens as well as for the development of control strategies, interdisciplinary collaboration of medical science and geography is helpful. Not only national but also regional structures should be taken into account. Source

Denecke K.,Innovation Center Computer Assisted Surgery | Krieck M.,Niedersachsisches Landesgesundheitsamt | Otrusina L.,Brno University of Technology | Smrz P.,Brno University of Technology | And 3 more authors.
Methods of Information in Medicine | Year: 2013

Objectives: Detecting hints to public health threats as early as possible is crucial to prevent harm from the population. However, many disease surveillance strategies rely upon data whose collection requires explicit reporting (data transmitted from hospitals, laboratories or physicians). Collecting reports takes time so that the reaction time grows. Moreover, context information on individual cases is often lost in the collection process. This paper describes a system that tries to address these limitations by processing social media for identifying information on public health threats. The primary objective is to study the usefulness of the approach for supporting the monitoring of a population's health status. Methods: The developed system works in three main steps: Data from Twitter, blogs, and forums as well as from TV and radio channels are continuously collected and filtered by means of keyword lists. Sentences of relevant texts are classified relevant or irrelevant using a binary classifier based on support vector machines. By means of statistical methods known from biosurveillance, the relevant sentences are further analyzed and signals are generated automatically when unexpected behavior is detected. From the generated signals a subset is selected for presentation to a user by matching with user queries or profiles. In a set of evaluation experiments, public health experts assessed the generated signals with respect to correctness and relevancy. In particular, it was assessed how many relevant and irrelevant signals are generated during a specific time period. Results: The experiments show that the system provides information on health events identified in social media. Signals are mainly generated from Twitter messages posted by news agencies. Personal tweets, i.e. tweets from persons observing some symptoms, only play a minor role for signal generation given a limited volume of relevant messages. Relevant signals referring to real world outbreaks were generated by the system and monitored by epidemiologists for example during the European football championship. But, the number of relevant signals among generated signals is still very small: The different experiments yielded a proportion between 5 and 20% of signals regarded as "relevant" by the users. Vaccination or education campaigns communicated via Twitter as well as use of medical terms in other contexts than for outbreak reporting led to the generation of irrelevant signals. Conclusions: The aggregation of information into signals results in a reduction of monitoring effort compared to other existing systems. Against expectations, only few messages are of personal nature, reporting on personal symptoms. Instead, media reports are distributed over social media channels. Despite the high percentage of irrelevant signals generated by the system, the users reported that the effort in monitoring aggregated information in form of signals is less demanding than monitoring huge social-media data streams manually. It remains for the future to develop strategies for reducing false alarms. © Schattauer 2013. Source

Munoz K.,University of Koblenz-Landau | Wollin K.-M.,Niedersachsisches Landesgesundheitsamt | Kalhoff H.,Klinikum Dortmund | Degen G.H.,TU Dortmund
Gesundheitswesen | Year: 2013

Introduction: Breast milk is the best form of nutrition early in life, yet it may contain contaminants which were ingested by mothers. Ochratoxin A (OTA) is a well-known nephrotoxin with carcinogenic properties and a frequent food contaminant. Ingested OTA is partly excreted with human milk and studies conducted in different countries have shown a wide range of OTA concentrations. The aim of this study was to assess the exposure of infants to OTA by analysing breast milk samples from 2 German areas. Methods Breast milk samples were obtained from 90 mothers who had signed an informed consent sheet. The previously validated analytical method (LOD=10 ng/L, LOQ=30 ng/L) involves liquid-liquid extraction and analysis by HPLC with tandem mass spectrometric detection. A preliminary risk assessment was done using the TDI approach. Results More than 50% of the collected 90 milk samples contained detectable OTA levels. Overall, the average concentration in milk from Dortmund (24.4±21.1 ng/L (n=30), range:<10-100 ng/L) were significant higher than those measured in the Hannover cohort (14.4±15.1 ng/L (n=60), range: <10-78 ng/L). The OTA levels of 13 samples were measured with concentrations≥LOQ. The burden of breast milk in different lactation stages, differentiated by colostrum, transitional milk and mature milk, did not differ in the 2 samples collectives Dortmund and Hannover. The infants' exposure was assessed by calculating their OTA intake via human milk. These results were then compared to the recently re-evaluated Tolerable Daily Intake (TDI) of 3 ng/kg body weight/day. In 29% of the cases (with 26 milk samples), the TDI of 3 ng/kg body weight/day was exceeded. Conclusion: In summary, infant exposure to OTA with human milk in Germany is usually low compared to several other countries. Given that in some cases the TDI is exceeded, further efforts to regulate OTA levels in food with the aim of reducing the contamination should be made to minimize the exposure of lactating women to OTA. © Georg Thieme Verlag KG Stuttgart · New York. Source

Ruddat I.,University of Veterinary Medicine Hannover | Schwarz S.,Institute of Farm Animal Genetics | Tietze E.,Robert Koch Institute | Ziehm D.,Niedersachsisches Landesgesundheitsamt | Kreienbrock L.,University of Veterinary Medicine Hannover
Epidemiology and Infection | Year: 2012

This study used statistical methods to investigate linkages in phenotypic resistance profiles in a population sample of 321 Salmonella Typhimurium isolates from sporadic salmonellosis cases in Lower Saxony, Germany, collected during 2008-2010. A resistance index was applied to calculate the conditional probability of resistance to one antimicrobial agent given the resistance to one or more other antimicrobial agent(s). A susceptibility index was defined analogously. A contingency plot, which visualizes the association between resistances to two antimicrobial agents, facilitated the interpretation. Linkages between minimum inhibitory concentrations (MIC) were analysed using Spearman's rank correlation coefficient and jittered scatter plots. Applying these methods provided a compact description of multi-resistance and linkages between resistance properties in large datasets. Moreover, this approach will improve monitoring of antimicrobial resistance dynamics of bacteria in human or animal populations by identifying linked resistance to antimicrobial agents (cross- or co-resistance) with a non-molecular method. © 2011 Cambridge University Press. Source

Background: Cancer registries often receive inquiries on possible cancer clusters. In 2010, the Cancer Registry of Lower Saxony reported on a spatial leukemia accumulation in the community of Asse. As a result, the Cancer Registry was engaged in developing an approach for a regional cancer monitoring program by the federal government. The modular approach involves a two-stage process. First, all regional monitoring areas are under surveillance, and in the second phase, noticeable areas only are observed further. A positive confirmation test is regarded as an initial concern and may lead to further investigations. Methods: The standardized incidence ratio (SIR) is used in the first stage. For confirmation, the Sequential Probability Ratio Test (SPRT) is applied in the second stage. All new observations are tested at a given time. The SPRT tests the null hypothesis (no increase) and an alternative hypothesis (increase) leading to three possible conclusions: warning, all-clear, or further surveillance necessary. Results: A high false alarm rate due to clustering by chance is to be considered with multiple statistical testing. The number of false alarms depends on the number of tested areas, diagnoses, subgroup analyses, and time periods. Preliminary considerations comprise 400 spatial areas, three diagnosis groups, no subgroup analyses, and a biannual first-stage testing. Guidelines for the level of significance and for detecting an increase in incidence will be necessary for the assessment of the monitoring parameters. Discussion: Before running the monitoring program, a number of questions have to handled politically; e.g., how many false alarms can be handled, the impact on the population involved, and existing risk communication structures. © 2013 Springer-Verlag Berlin Heidelberg. Source

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