981 resultados para Disease Outbreaks


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In this study, we present a trilocus sequence typing (TLST) scheme based on intragenic regions of two antigenic genes, ace and salA (encoding a collagen/laminin adhesin and a cell wall-associated antigen, respectively), and a gene associated with antibiotic resistance, lsa (encoding a putative ABC transporter), for subspecies differentiation of Enterococcus faecalis. Each of the alleles was analyzed using 50 E. faecalis isolates representing 42 diverse multilocus sequence types (ST(M); based on seven housekeeping genes) and four groups of clonally linked (by pulsed-field gel electrophoresis [PFGE]) isolates. The allelic profiles and/or concatenated sequences of the three genes agreed with multilocus sequence typing (MLST) results for typing of 49 of the 50 isolates; in addition to the one exception, two isolates were found to have identical TLST types but were single-locus variants (differing by a single nucleotide) by MLST and were therefore also classified as clonally related by MLST. TLST was also comparable to PFGE for establishing short-term epidemiological relationships, typing all isolates classified as clonally related by PFGE with the same type. TLST was then applied to representative isolates (of each PFGE subtype and isolation year) of a collection of 48 hospital isolates and demonstrated the same relationships between isolates of an outbreak strain as those found by MLST and PFGE. In conclusion, the TLST scheme described here was shown to be successful for investigating short-term epidemiology in a hospital setting and may provide an alternative to MLST for discriminating isolates.

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Infectious disease outbreaks can be devastating because of their sudden occurrence, as well as the complexity of monitoring and controlling them. Outbreaks in wildlife are even more challenging to observe and describe, especially when small animals or secretive species are involved. Modeling such infectious disease events is relevant to investigating their dynamics and is critical for decision makers to accomplish outbreak management. Tularemia, caused by the bacterium Francisella tularensis, is a potentially lethal zoonosis. Of the few animal outbreaks that have been reported in the literature, only those affecting zoo animals have been closely monitored. Here, we report the first estimation of the basic reproduction number R0 of an outbreak in wildlife caused by F. tularensis using quantitative modeling based on a susceptible-infected-recovered framework. We applied that model to data collected during an extensive investigation of an outbreak of tularemia caused by F. tularensis subsp. holarctica (also designated as type B) in a closely monitored, free-roaming house mouse (Mus musculus domesticus) population in Switzerland. Based on our model and assumptions, the best estimated basic reproduction number R0 of the current outbreak is 1.33. Our results suggest that tularemia can cause severe outbreaks in small rodents. We also concluded that the outbreak self-exhausted in approximately three months without administrating antibiotics.

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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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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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Human activities are fundamentally altering the chemistry of the world's oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, 1H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.

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One hypothesis for the success of invasive species is reduced pathogen burden, resulting from a release from infections or high immunological fitness (low immunopathology) of invaders. Despite of strong selection exerted on the host, the evolutionary response of invaders to newly acquired pathogens has rarely been considered. The two independent and genetically distinct invasions of the Pacific oyster Crassostrea gigas into the North Sea represent an ideal model system to study fast evolutionary responses of invasive populations. By exposing both invasion sources to ubiquitous and phylogenetically diverse pathogens (Vibrio spp.) we demonstrate that within a few generations hosts adapted to sympatric pathogen communities. However, this local adaptation only became apparent in selective environments, i.e. at elevated temperatures reflecting patterns of disease outbreaks in natural populations. Resistance against sympatric and allopatric Vibrio spp. strains was dominantly inherited in crosses between both invasion sources, resulting in an overall higher resistance of admixed individuals than pure lines. Therefore we suggest that a simple genetic resistance mechanism of the host is matched to a common virulence mechanism shared by local Vibrio strains. This combination might have facilitated a fast evolutionary response that can explain another dimension of why invasive species can be so successful in newly invaded ranges.

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"Sponsors: National Heart, Lung, and Blood Institute, ... [et al.]"

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"Índice alfabético de las principales materias": p. [339]-346.

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Title from cover.

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Marteilia sydneyi (Paramyxea) is the causative agent of QX disease in oysters. In spite of the economic impact of this disease, its origin and the precise reason(s) for its apparent spread in Australian waters are not yet known. Given such knowledge gaps, investigating the population genetic structure(s) of M. sydneyi populations could provide insights into the epidemiology and ecology of the parasite and could assist in its prevention and control. In this study, single strand conformation polymorphism (SSCP)-based analysis of a region (195 bp) of the first internal transcribed spacer (ITS-1) of ribosomal DNA was employed to investigate genetic variation within and among five populations of M. sydneyi from oysters from five different locations in eastern Australia. The analysis showed the existence of a genetic variant of M. sydneyi common to the Great Sandy Strait, and the Richmond and Georges Rivers, as distinct from variants at the Pimpama and Clarence Rivers. Together with historical and other information relating to the QX disease outbreaks in eastern Australia, the molecular findings support the proposal that the parasite originated in the Great Sandy Strait and/or Richmond River and then extended southward along the coast. From a technical perspective, the study demonstrated the usefulness of SSCP as a tool to study the population genetics and epidemiology of M. sydneyi. (C) 2003 Elsevier Ltd. All rights reserved.

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Wildlife populations are affected by a series of emerging diseases, some of which pose a significant threat to their conservation. They can also be reservoirs of pathogens that threaten domestic animal and human health. In this paper, we review the ecology of two viruses that have caused significant disease in domestic animals and humans and are carried by wild fruit bats in Asia and Australia. The first, Hendra virus, has caused disease in horses and/or humans in Australia every five years since it first emerged in 1994. Nipah virus has caused a major outbreak of disease in pigs and humans in Malaysia in the late 1990s and has also caused human mortalities in Bangladesh annually since 2001. Increased knowledge of fruit bat population dynamics and disease ecology will help improve our understanding of processes driving the emergence of diseases from bats. For this, a transdisciplinary approach is required to develop appropriate host management strategies that both maximise the conservation of bat populations as well as minimise the risk of disease outbreaks in domestic animals and humans. (c) 2006 Elsevier Ltd. All rights reserved.

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The ornate tropical rock lobster, Panulirus ornatus has substantial potential as an aquaculture species though disease outbreaks during the animal's extended larval lifecycle are major constraints for success. In order to effectively address such disease-related issues, an improved understanding of the composition and dynamics of the microbial communities in the larval rearing tanks is required. This study used flow cytometry and molecular microbial techniques (clone libraries and denaturing gradient gel electrophoresis (DGGE)) to quantify and characterise the microbial community of the water column in the early stages (developmental stage I-II) of a P. ornatus larval rearing system. DGGE analysis of a 5000 L larval rearing trial demonstrated a dynamic microbial community with distinct changes in the community structure after initial stocking (day I to day 2) and from day 4 to day 5, after which the structure was relatively stable. Flow cytometry analysis of water samples taken over the duration of the trial demonstrated a major increase in bacterial load leading up to and peaking on the first day of the initial larval moult (day 7), before markedly decreasing prior to when > 50% of larvae moulted (day 9). A clone library of a day 10 water sample taken following a mass larval mortality event reflected high microbial diversity confirmed by statistical analysis indices. Sequences retrieved from both clone library and DGGE analyses were dominated by gamma- and alpha-Proteobacteria affiliated organisms with additional sequences affiliated with beta- and epsilon-Proteobacteria, Bacteroidetes, Cytophagales and Chlamydiales groups. Vibrio affiliated species were commonly retrieved in the clone library, though absent from DGGE analysis.

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Water remains a predominant vector for human enteric pathogens not just for developing countries but also developed nations, where numerous infectious disease outbreaks, linked to the contamination of drinking water have been documented. Private drinking water wells are a source of drinking water that is largely unstudied even though a significant percentage of the population in Ontario relies on wells as their primary water source. As there exists little to no systematic surveillance for enteric infections or outbreaks related to well water sources, these individuals may be at higher risk of waterborne infectious diseases. The relationships between various fecal indicators in the water of private drinking water wells, including E. coli, Total Coliforms (TC) and Bacteroides, and enteric pathogens, including Campylobacter jejuni, Salmonella spp., and Shiga toxin producing E. coli, were studied. Convenience private well water samples collected from various regions of interest during the summer of 2014 underwent membrane filtration and culture to determine quantities of E. coli and TC colony forming units. 289 E. coli positive and 230 TC-only waters were successfully analyzed by individual qPCR assays for the aforementioned enteric pathogens. Microbial source tracking methods targeted to specific Bacteroides were used to determine the source of fecal contamination as either human or bovine. The source of fecal contamination varied by geographic region and is thought to be due to such things as differences in septic tank density and underlying geology, among others. Fecal indicators, E. coli and Bacteroides, were significantly correlated. E. coli as measured by qPCR was more strongly correlated to both total and human-specific Bacteroides genetic markers than culturable E. coli. Lastly, 1.9% of samples showed molecular evidence of contamination with enteric pathogens. Although low, this finding is significant given the limited volume of water available for testing, and suggests a potential health risk to consumers. Knowing the extent of contamination, as well as the biologic source, can better inform risk assessment and the development of potential intervention strategies for private well water in specific regions of Ontario.

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On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.