988 resultados para SURVEILLANCE NETWORK TRANSNET


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Contact surveillance is an important strategy to ensure effective early diagnosis and control of leprosy; passive detection may not be as efficient because it is directly tied to the ready availability of heath care services and health education campaigns. The aim of this study was to reinforce that contact surveillance is the most effective strategy for the control of leprosy. The analysed data were obtained from a cohort of contacts and cases diagnosed through a national referral service for leprosy. We analysed data from patients diagnosed between 1987-2010 at the Souza Araújo Ambulatory in Rio de Janeiro. Epidemiological characteristics of leprosy cases diagnosed through contact surveillance and characteristics of passively detected index cases were compared using a conditional logistic regression model. Cases diagnosed by contact surveillance were found earlier in the progression of the disease, resulting in less severe clinical presentations, lower levels of initial and final disability grades, lower initial and final bacterial indices and a lower prevalence of disease reaction. In this respect, contact surveillance proved to be an effective tertiary prevention strategy, indicating that active surveillance is especially important in areas of high endemicity, such as Brazil.

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Con este proyecto se pretende implementar en un entorno real la herramienta Zabbix de monitoring de red. La idea es realizar un estudio de las necesidades, instalar la plataforma base, comprobar con ejemplos reales que la plataforma cumple con las necesidades corporativas y por último diseñar el plan de acción para el despliegue final a la organización.

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Epidemiological surveillance systems are essential and require efficient collaborations between family doctors and public health services. Such a system has to take into account the increase in the number of health problems to be studied. Information gathered at an individual level should imply decisions at a population level which in turn should impact on the individual patient. Epidemiological surveillance requires a well organized, representative and constantly revised system led by motivated, adequately trained doctors.

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In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

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In Brazil, the entomological surveillance of Aedes (Stegomyia) aegypti is performed by government-mandated larval surveys. In this study, the sensitivities of an adult sticky trap and traditional surveillance methodologies were compared. The study was performed over a 12-week period in a residential neighbourhood of the municipality of Pedro Leopoldo, state of Minas Gerais, Brazil. An ovitrap and a MosquiTRAP were placed at opposite ends of each neighbourhood block (60 traps in total) and inspections were performed weekly. The study revealed significant correlations of moderate strength between the larval survey, ovitrap and MosquiTRAP measurements. A positive relationship was observed between temperature, adult capture measurements and egg collections, whereas precipitation and frequency of rainy days exhibited a negative relationship.

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Several parasitological studies carried out in El Salvador between 2000-2012 showed a higher frequency of acute cases of Chagas disease than that in other Central American countries. There is an urgent need for improved Chagas disease surveillance and vector control programs in the provinces where acute Chagas disease occurs and throughout El Salvador as a whole.

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Countries could use the monitoring of drug resistance in malaria parasites as an effective early warning system to develop the timely response mechanisms that are required to avert the further spread of malaria. Drug resistance surveillance is essential in areas where no drug resistance has been reported, especially if neighbouring countries have previously reported resistance. Here, we present the results of a four-year surveillance program based on the sequencing of the pfcrt gene of Plasmodium falciparum populations from endemic areas of Honduras. All isolates were susceptible to chloroquine, as revealed by the pfcrt “CVMNK” genotype in codons 72-76.

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The lethality of malaria in the extra-Amazonian region is more than 70 times higher than in Amazonia itself. Recently, several studies have shown that autochthonous malaria is not a rare event in the Brazilian southeastern states in the Atlantic Forest biome. Information about autochthonous malaria in the state of Rio de Janeiro (RJ) is scarce. This study aims to assess malaria cases reported to the Health Surveillance System of the State of Rio de Janeiro between 2000-2010. An average of 90 cases per year had parasitological malaria confirmation by thick smear. The number of malaria notifications due to Plasmodium falciparum increased over time. Imported cases reported during the period studied were spread among 51% of the municipalities (counties) of the state. Only 35 cases (4.3%) were autochthonous, which represents an average of 3.8 new cases per year. Eleven municipalities reported autochthonous cases; within these, six could be characterised as areas of residual or new foci of malaria from the Atlantic Forest system. The other 28 municipalities could become receptive for transmission reintroduction. Cases occurred during all periods of the year, but 62.9% of cases were in the first semester of each year. Assessing vulnerability and receptivity conditions and vector ecology is imperative to establish the real risk of malaria reintroduction in RJ.

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Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

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Glial cells are active partners of neurons in processing information and synaptic integration. They receive coded signals from synapses and elaborate modulatory responses. The active properties of glia, including long-range signalling and regulated transmitter release, are beginning to be elucidated. Recent insights suggest that the active brain should no longer be regarded as a circuitry of neuronal contacts, but as an integrated network of interactive neurons and glia.

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HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

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BACKGROUND Combination antiretroviral therapy (cART) has produced significant changes in mortality of HIV-infected persons. Our objective was to estimate mortality rates, standardized mortality ratios and excess mortality rates of cohorts of the AIDS Research Network (RIS) (CoRIS-MD and CoRIS) compared to the general population. METHODS We analysed data of CoRIS-MD and CoRIS cohorts from 1997 to 2010. We calculated: (i) all-cause mortality rates, (ii) standardized mortality ratio (SMR) and (iii) excess mortality rates for both cohort for 100 person-years (py) of follow-up, comparing all-cause mortality with that of the general population of similar age and gender. RESULTS Between 1997 and 2010, 8,214 HIV positive subjects were included, 2,453 (29.9%) in CoRIS-MD and 5,761 (70.1%) in CoRIS and 294 deaths were registered. All-cause mortality rate was 1.02 (95% CI 0.91-1.15) per 100 py, SMR was 6.8 (95% CI 5.9-7.9) and excess mortality rate was 0.8 (95% CI 0.7-0.9) per 100 py. Mortality was higher in patients with AIDS, hepatitis C virus (HCV) co-infection, and those from CoRIS-MD cohort (1997-2003). CONCLUSION Mortality among HIV-positive persons remains higher than that of the general population of similar age and sex, with significant differences depending on the history of AIDS or HCV coinfection.

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BACKGROUND The possible differences in the disease spectrum and prognosis of HIV infection in women and men is a major point of concern. Women are under-represented in randomized clinical trials and in some cohorts. Discordant results have often been obtained depending on the setting. METHODS We assessed gender differences in clinical and epidemiological features, antiretroviral treatment (ART) exposure and survival in two multicentre cohorts of HIV-positive subjects in Spain: CoRIS-MD and CoRIS. Competing risk regression models were used to assess gender effect on time to start ART and time to first ART change, and a Cox regression model to estimate gender effect on time to death. RESULTS Between January 1996 and December 2008, 1,953 women and 6,072 men naive to ART at study entry were included. The trend analysis over time showed the percentage of women in the younger (<20 years) and older (>50 years) strata increased significantly (P<0.001) from 0.5% and 1.8% in 1996 to 4.9% and 4.2% in 2008, respectively. By competing risk analysis women started ART earlier than men (adjusted subhazard ratio [ASHR] 1.21, 95% CI 1.11, 1.31) in CoRIS cohort, while in CoRIS-MD none of these differences were observed. In both cohorts women showed a shorter time to the first ART change (ASHR 1.10, 95% CI 1.01, 1.19). Pregnancy and patient's/physician's decisions as reasons for changing were more frequent in women than in men in CoRIS. In the Cox regression model, gender was not associated with differences in survival. CONCLUSIONS In two large cohorts in Spain, we observed relevant gender differences in epidemiological characteristics and antiretroviral exposure outcomes, while survival differences were not attributable to gender.