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.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2009.5.2 | Award Amount: 2.59M | Year: 2010
Many factors in todays changing societies contribute towards the continuous emergence of infectious diseases. Demographic change, globalization, bioterrorism, compounded with the resilient nature of viruses and diseases such as SARS and avian influenza have raised awareness for European societys increasing vulnerability.\nTraditional Epidemic Intelligence systems are designed to identify potential health threats, and rely upon data transmissions from laboratories or hospitals. They can be used to recognise long-term trends, but are limited in several ways. Threats, such as SARS, can go unrecognised since the signals indicating its existence may originate from sources other than the traditional ones. Second, a critical strategy for circumventing devastating public health events is early detection and early response. Conflictingly, the time with which information propagates through the traditional channels, can undermine time-sensitive strategies. Finally, traditional systems are well suited for recognising indicators for known diseases, but are not well designed for detecting those that are emerging. Faced with these limitations, traditional systems need to be complemented with additional approaches which are better targeted for the early detection of emerging threats.\nThe Medical EcoSystem (M-Eco) project, will address these limitations by using Open Access Media and User Generated Content, as unofficial information sources for Epidemic Intelligence. This type of content has transformed the manner in which information propagates across the globe. Based on this, M-Eco will develop an Event-Based Epidemic Intelligence System which integrates unofficial and traditional sources for the early detection of emerging health threats. M-Eco will emphasize adaptivity and personalized filtering so that relevant signals can be detected for targeting the needs of public health officials who have to synthesize facts, assess risks and react to public health threats.
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.
Dreesman J.,Niedersachsisches Landesgesundheitsamt |
Denecke K.,Niedersachsisches Landesgesundheitsamt |
Denecke K.,search Center
Studies in Health Technology and Informatics | Year: 2011
Early detection of disease outbreaks is crucial for public health officials to react and report in time. Currently, novel approaches and sources of information are investigated to address this challenge. For example, data sources such as blogs or Twitter messages become increasingly important for epidemiologic surveillance. In traditional surveillance, statistical methods are used to interpret reported number of cases or other indicators to potential disease outbreaks. For analyzing data collected from other data sources, in particular for data extracted from unstructured text, it is still unclear whether these methods can be applied. This paper surveys existing methods for interpreting data for signal generation in public health. In particular, problems to be addressed when applying them to social media data will be summarized and future steps will be highlighted. © 2011 European Federation for Medical Informatics. All rights reserved.
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.
Luther S.,University of Bonn |
Schweikart J.,Berlin Technical University of Applied Sciences |
Scharlach H.,Niedersachsisches Landesgesundheitsamt
Public Health Forum | Year: 2016
Differences in Health Care Delivery are the result of diverse effects, which often have spatial reference. These effects include differences of the socio economic status and limited access to health care services. Medical Geography offers several methods and theoretical frameworks to analyze these effects and to develop different solutions. Basic tools for these tasks are maps and geographical information systems (GIS). © 2016 by De Gruyter.
Rissland J.,Universitatsklinikum des Saarlandes |
Kielstein J.T.,Klinik fur Nieren und Hochdruckerkrankungen |
Stark K.,Robert Koch Institute |
Wichmann-Schauer H.,Fachgruppe Pravention und Aufklarung Lebensmittelbedingter Ausbruche |
And 2 more authors.
Gesundheitswesen | Year: 2013
The EHEC O104:H4 outbreak 2011 in Germany provided numerous insights into the recognition and control of such epidemic situations. Food-borne outbreaks and their related dynamics may lead to a critical burden of disease and an eventual capacity overload of the medical care system. Possible difficulties in the microbiological diagnostics of new or significantly altered infectious agents may result in a delayed detection of the outbreak as well as the launching of interventional measures. Besides an early notification of the local public health office by the affected institutions, in which a complete electronic procedure and additional sentinel or surveillance instruments (e. g., in emergency departments of hospitals) may be of great help, an interdisciplinary cooperation of the local public health and food safety agencies is the key to an effective outbreak control. Corresponding organizations on the state and federal level should support the investigation process by microbiological diagnostics and advanced epidemiological analysis as well as examination of the food chains. Finally, successful crisis communication relies on "speaking with one voiceo" (not necessarily one person). Immediate, transparent, appropriate and honest information of the general public concerning the reasons, consequences and (counter-) measures of a crisis are the best means to keep the trust of the population and to counteract the otherwise inevitable speculations. © Georg Thieme Verlag KG Stuttgart · New York.
Active surveillance of small-scale spatial cancer clusters: Presentation of a new monitoring approach for the Epidemiological Cancer Registry of Lower Saxony [Aktives Monitoring kleinräumiger Krebshäufungen: Vorstellung eines neuen Monitoringkonzeptes für das Epidemiologische Krebsregister Niedersachsen]
Kieschke J.,Epidemiologisches Krebsregister Niedersachsen |
Hoopmann M.,Niedersachsisches Landesgesundheitsamt
Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz | Year: 2014
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.
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.
Adaptation to health impacts of climate change: Investigation of a heat warning system in a case study from Lower Saxony [Anpassung an die gesundheitlichen Folgen des Klimawandels: Untersuchung eines Hitzewarnsystems am Fallbeispiel Niedersachsen]
Augustin J.,Umweltbundesamt FG II 1.5 |
Paesel H.K.,University of Gottingen |
Mucke H.-G.,Umweltbundesamt FG II 1.5 |
Grams H.,Niedersachsisches Landesgesundheitsamt
Pravention und Gesundheitsforderung | Year: 2011
Background: The effectiveness of heat wave warning systems is so far rather unclear. Taking the heat warning system of Lower Saxony as an example, an investigation was performed to determine if the available information reaches the relevant people and if, as a consequence, it leads to changes in their behaviour. Method: Nursing homes (n=213) were interviewed with standardised questionnaires, and additional interviews of elderly persons (n=52) who live on their own were conducted. Results: The majority of the interviewed homes reported that they take note of heat warnings. It seems that less than half of the interviewed homes use the information of heat warning systems to initiate necessary actions and measures. Heat warnings do not - in most cases - reach elderly persons who live on their own and are especially affected by climate changes like extreme heat. Consequences: Even if heat warnings could initiate measures necessary with respect to extreme heat, the information of heat wave warning systems could only be regarded as additional information. There is need for a fast and secure distribution of information generated by heat warning systems as well as for a standardised catalogue of necessary measures. In particular, the integration of elderly people who live on their own has to be taken into consideration. © 2011 Springer Medizin Verlag.