740 resultados para Vidéo surveillance
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The introduction of transient elastography in clinical practice has allowed the early identification of patients with chronic liver disease (CLD) at risk of developing clinically significant portal hypertension (CSPH) (1b;A).
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After an outbreak of Yersinia enterocolitica at a NHP research facility, we performed a multispecies investigation of the prevalence of Yersinia spp. in various mammals that resided or foraged on the grounds of the facility, to better understand the epizootiology of yersiniosis. Blood samples and fecal and rectal swabs were obtained from 105 captive African green monkeys (AGM), 12 feral cats, 2 dogs, 20 mice, 12 rats, and 3 mongooses. Total DNA extracted from swab suspensions served as template for the detection of Y. enterocolitica DNA by real-time PCR. Neither Y. enterocolitica organisms nor their DNA were detected from any of these samples. However, Western blotting revealed the presence of Yersinia antibodies in plasma. The AGM samples revealed a seroprevalence of 91% for Yersinia spp. and of 61% for Y. enterocolitica specifically. The AGM that were housed in cages where at least one fatality occurred during the outbreak (clinical group) had similar seroprevalence to that of AGM housed in unaffected cages (nonclinical group). However, the nonclinical group was older than the clinical group. In addition, 25%, 100%, 33%, 10%, and 10% of the sampled local cats, dogs, mongooses, rats, and mice, respectively, were seropositive. The high seroprevalence after this outbreak suggests that Y. enterocolitica was transmitted effectively through the captive AGM population and that age was an important risk factor for disease. Knowledge regarding local environmental sources of Y. enterocolitica and the possible role of wildlife in the maintenance of yersiniosis is necessary to prevent and manage this disease.
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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.
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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.
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Clinical observations made by practitioners and reported using web- and mobile-based technologies may benefit disease surveillance by improving the timeliness of outbreak detection. Equinella is a voluntary electronic reporting and information system established for the early detection of infectious equine diseases in Switzerland. Sentinel veterinary practitioners have been able to report cases of non-notifiable diseases and clinical symptoms to an internet-based platform since November 2013. Telephone interviews were carried out during the first year to understand the motivating and constraining factors affecting voluntary reporting and the use of mobile devices in a sentinel network. We found that non-monetary incentives attract sentinel practitioners; however, insufficient understanding of the reporting system and of its relevance, as well as concerns over the electronic dissemination of health data were identified as potential challenges to sustainable reporting. Many practitioners are not yet aware of the advantages of mobile-based surveillance and may require some time to become accustomed to novel reporting methods. Finally, our study highlights the need for continued information feedback loops within voluntary sentinel networks.
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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.
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We obtained partial carcass condemnation (PCC) data for cattle (2009-2010) from a Swiss slaughterhouse. Data on whole carcass condemnations (WCC) carried out at the same slaughterhouse over those years were extracted from the national database for meat inspection. We found that given the differences observed in the WCC and PCC time series, it is likely that both indicators respond to different health events in the population and that one cannot be substituted by the other. Because PCC recordings are promising for syndromic surveillance, the meat inspection database should be capable to record both WCC and PCC data in the future. However, a standardised list of reasons for PCC needs to be defined and used nationwide in all slaughterhouses.
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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.
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Occurring for the first time in 1986 in the United Kingdom, bovine spongiform encephalopathy (BSE), the so-called “mad-cow disease”, has had unprecedented consequences in veterinary public health. The implementation of drastic measures, including the ban of meat-and-bone-meal from livestock feed and the removal of specified risk materials from the food chain has eventually resulted in a significant decline of the epidemic. The disease was long thought to be caused by a single agent, but since the introduction of immunochemical diagnostic techniques, evidence of a phenotypic variation of BSE has emerged. Reviewing the literature available on the subject, this paper briefly summarizes the current knowledge about these atypical forms of BSE and discusses the consequences of their occurrence for disease control measures.
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Current toxic tort cases have increased national awareness of health concerns and present an important avenue in which public health scientists can perform a vital function: in litigation, and in public health initiatives and promotions which may result. This review presents a systematic approach, using the paradigm of interactive public health disciplines, for the design of a matrix framework for medical surveillance of workers exposed to toxic substances. The matrix framework design addresses the required scientific bases to support the legal remedy of medical monitoring for workers injured as a result of their exposure to toxic agents. A background of recent legal developments which have a direct impact on the use of scientific expertise in litigation is examined in the context of toxic exposure litigation and the attainment of public health goals. The matrix model is applied to five different workplace exposures: dental mercury, firefighting, vinyl chloride manufacture, radon in mining and silica. An exposure matrix designed by the Department of Energy for government nuclear workers is included as a reference comparison to the design matrix. ^