14 resultados para surveillance systems
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
BACKGROUND: In Switzerland (population 7.4 million), 3 different systems contribute to surveillance for sexually transmitted infections. GOAL: The goal of this study was to compare time trends from surveillance systems for chlamydia, gonorrhea, and syphilis. STUDY DESIGN: We studied surveillance data (1997-2003) from laboratory reports in women and men, men attending dermatology clinics, and women attending gynecologists. RESULTS: Laboratory reports of episodes of Chlamydia trachomatis and Neisseria gonorrhoeae increased by 31% (from 2573 to 3449 cases) and 104% (from 259 to 528 cases), respectively. Over the same period, chlamydia reports from men attending dermatology clinics and women attending gynecologists did not change and dermatology clinic-based reports of gonorrhea in men increased only slightly. Syphilis reports from dermatology clinics increased by 127% (from 22 to 50 cases). CONCLUSIONS: Increases in laboratory reports of chlamydia and gonorrhea were not consistently detected in sentinel populations. Numbers of cases reported to all 3 systems were low. The performance of surveillance systems for sexually transmitted infections should be evaluated regularly.
Resumo:
A sensitive, specific and timely surveillance is necessary to monitor progress towards measles elimination. We evaluated the performance of sentinel and mandatory-based surveillance systems for measles in Switzerland during a 5-year period by comparing 145 sentinel and 740 mandatory notified cases. The higher proportion of physicians who reported at least one case per year in the sentinel system suggests underreporting in the recently introduced mandatory surveillance for measles. Accordingly, the latter reported 2-36-fold lower estimates for incidence rates than the sentinel surveillance. However, these estimates were only 0.6-12-fold lower when we considered confirmed cases alone, which indicates a higher specificity of the mandatory surveillance system. In contrast, the sentinel network, which covers 3.5% of all outpatient consultations, detected only weakly and late a major national measles epidemic in 2003 and completely missed 2 of 10 cantonal outbreaks. Despite its better timeliness and greater sensitivity in case detection, the sentinel system, in the current situation of low incidence, is insufficient to perform measles control and to monitor progress towards elimination.
Resumo:
The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).
Resumo:
Within the current context that favours the emergence of new diseases, syndromic surveillance (SyS) appears increasingly more relevant tool for the early detection of unexpected health events. The Triple-S project (Syndromic Surveillance Systems in Europe), co-financed by the European Commission, was launched in September 2010 for a three year period to promote both human and animal health SyS in European countries. Objectives of the project included performing an inventory of current and planned European animal health SyS systems and promoting knowledge transfer between SyS experts. This study presents and discusses the results of the Triple-S inventory of European veterinary SyS initiatives. European SyS systems were identified through an active process based on a questionnaire sent to animal health experts involved in SyS in Europe. Results were analyzed through a descriptive analysis and a multiple factor analysis (MFA) in order to establish a typology of the European SyS initiatives. Twenty seven European SyS systems were identified from twelve countries, at different levels of development, from project phase to active systems. Results of this inventory showed a real interest of European countries for SyS but also highlighted the novelty of this field. This survey highlighted the diversity of SyS systems in Europe in terms of objectives, population targeted, data providers, indicators monitored. For most SyS initiatives, statistical analysis of surveillance results was identified as a limitation in using the data. MFA results distinguished two types of systems. The first one belonged to the private sector, focused on companion animals and had reached a higher degree of achievement. The second one was based on mandatory collected data, targeted livestock species and is still in an early project phase. The exchange of knowledge between human and animal health sectors was considered useful to enhance SyS. In the same way that SyS is complementary to traditional surveillance, synergies between human and animal health SyS could be an added value, most notably to enhance timeliness, sensitivity and help interpreting non-specific signals.
Resumo:
BACKGROUND: This study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway. METHODS: A framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013. RESULTS: A cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99%, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey. CONCLUSIONS: The seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.
Resumo:
The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.
Resumo:
Systems for the identification and registration of cattle have gradually been receiving attention for use in syndromic surveillance, a relatively recent approach for the early detection of infectious disease outbreaks. Real or near real-time monitoring of deaths or stillbirths reported to these systems offer an opportunity to detect temporal or spatial clusters of increased mortality that could be caused by an infectious disease epidemic. In Switzerland, such data are recorded in the "Tierverkehrsdatenbank" (TVD). To investigate the potential of the Swiss TVD for syndromic surveillance, 3 years of data (2009-2011) were assessed in terms of data quality, including timeliness of reporting and completeness of geographic data. Two time-series consisting of reported on-farm deaths and stillbirths were retrospectively analysed to define and quantify the temporal patterns that result from non-health related factors. Geographic data were almost always present in the TVD data; often at different spatial scales. On-farm deaths were reported to the database by farmers in a timely fashion; stillbirths were less timely. Timeliness and geographic coverage are two important features of disease surveillance systems, highlighting the suitability of the TVD for use in a syndromic surveillance system. Both time series exhibited different temporal patterns that were associated with non-health related factors. To avoid false positive signals, these patterns need to be removed from the data or accounted for in some way before applying aberration detection algorithms in real-time. Evaluating mortality data reported to systems for the identification and registration of cattle is of value for comparing national data systems and as a first step towards a European-wide early detection system for emerging and re-emerging cattle diseases.
Resumo:
High-quality data are essential for veterinary surveillance systems, and their quality can be affected by the source and the method of collection. Data recorded on farms could provide detailed information about the health of a population of animals, but the accuracy of the data recorded by farmers is uncertain. The aims of this study were to evaluate the quality of the data on animal health recorded on 97 Swiss dairy farms, to compare the quality of the data obtained by different recording systems, and to obtain baseline data on the health of the animals on the 97 farms. Data on animal health were collected from the farms for a year. Their quality was evaluated by assessing the completeness and accuracy of the recorded information, and by comparing farmers' and veterinarians' records. The quality of the data provided by the farmers was satisfactory, although electronic recording systems made it easier to trace the animals treated. The farmers tended to record more health-related events than the veterinarians, although this varied with the event considered, and some events were recorded only by the veterinarians. The farmers' attitude towards data collection was positive. Factors such as motivation, feedback, training, and simplicity and standardisation of data collection were important because they influenced the quality of the data.
Resumo:
The capacity to perceive and respond is integral to biological immune systems, but to what extent can plants specifically recognize and respond to insects? Recent findings suggest that plants possess surveillance systems that are able to detect general patterns of cellular damage as well as highly specific herbivore-associated cues. The jasmonate (JA) pathway has emerged as the major signaling cassette that integrates information perceived at the plant–insect interface into broad-spectrum defense responses. Specificity can be achieved via JA-independent processes and spatio-temporal changes of JA-modulating hormones, including ethylene (ET), salicylic acid (SA), abscisic acid (ABA), auxin, cytokinins (CK), brassinosteroids (BR) and gibberellins (GB). The identification of receptors and ligands and an integrative view of hormone-mediated response systems are crucial to understand specificity in plant immunity to herbivores.
Resumo:
The objectives of this study were to describe the spatio-temporal pattern of an epidemic of highly pathogenic avian influenza (HPAI) in Vietnam and to identify potential risk factors for the introduction and maintenance of infection within the poultry population. The results indicate that during the time period 2004–early 2006 a sequence of three epidemic waves occurred in Vietnam as distinct spatial and temporal clusters. The risk of outbreak occurrence increased with a greater percentage of rice paddy fields, increasing domestic water bird and chicken density. It increased with reducing distance to higher population density aggregations, and in the third epidemic wave with increasing percentage of aquaculture. The findings indicate that agri-livestock farming systems involving domestic water birds and rice production in river delta areas are important for the maintenance and spread of infection. While the government’s control measures appear to have been effective in the South and Central parts of Vietnam, it is likely that in the North of Vietnam the vaccination campaign led to transmission of infection which was subsequently brought under control.
Resumo:
Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.
Resumo:
In this paper we present the results from the coverage and the orbit determination accuracy simulations performed within the recently completed ESA study “Assessment Study for Space Based Space Surveillance (SBSS) Demonstration System” (Airbus Defence and Space consortium). This study consisted in investigating the capability of a space based optical sensor (SBSS) orbiting in low Earth orbit (LEO) to detect and track objects in GEO (geosynchronous orbit), MEO (medium Earth orbit) and LEO and to determinate and improve initial orbits from such observations. Space based systems may achieve better observation conditions than ground based sensors in terms of astrometric accuracy, detection coverage, and timeliness. The primary observation mode of the proposed SBSS demonstrator is GEO surveillance, i.e. the systematic search and detection of unknown and known objects. GEO orbits are specific and unique orbits from dynamical point of view. A space-based sensor may scan the whole GEO ring within one sidereal day if the orbit and pointing directions are chosen properly. For an efficient survey, our goal was to develop a leak-proof GEO fence strategy. Collaterally, we show that also MEO, LEO and other (GTO,Molniya, etc.) objects would be possible to observe by the system and for a considerable number of LEO objects to down to size of 1 cm we can obtain meaningful statistical data for improvement and validation of space debris environment models
Resumo:
This paper presents the capabilities of a Space-Based Space Surveillance (SBSS) demonstration mission for Space Surveillance and Tracking (SST) based on a micro- satellite platform. The results have been produced in the frame of ESA’s "As sessment Study for Space Based Space Surveillance Demonstration Mission (Phase A) " performed by the Airbus DS consortium. Space Surveillance and Tracking is part of Space Situational Awareness (SSA) and covers the detection, tracking and cataloguing of spa ce debris and satellites. Derived SST services comprise a catalogue of these man-made objects, collision warning, detection and characterisation of in-orbit fragmentations, sub-catalogue debris characterisation, etc. The assessment of SBSS in an SST system architecture has shown that both an operational SBSS and also already a well - designed space-based demonstrator can provide substantial performance in terms of surveillance and tracking of beyond - LEO objects. Especially the early deployment of a demonstrator, possible by using standard equipment, could boost initial operating capability and create a self-maintained object catalogue. Unlike classical technology demonstration missions, the primary goal is the demonstration and optimisation of the functional elements in a complex end-to-end chain (mission planning, observation strategies, data acquisition, processing and fusion, etc.) until the final products can be offered to the users. The presented SBSS system concept takes the ESA SST System Requirements (derived within the ESA SSA Preparatory Program) into account and aims at fulfilling some of the SST core requirements in a stand-alone manner. The evaluation of the concept has shown that an according solution can be implemented with low technological effort and risk. The paper presents details of the system concept, candidate micro - satellite platforms, the observation strategy and the results of performance simulations for GEO coverage and cataloguing accuracy
Resumo:
Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.