978 resultados para NEGATIVE BINOMIAL-DISTRIBUTION


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OBJECTIVE: To assess a new impunity index and variables that have been found to predict variation in homicide rates in other geographical levels as predictive of state-level homicide rates in Brazil. METHODS: This was a cross-sectional ecological study. Data from the mortality information system relating to the 27 Brazilian states for the years 1996 to 2005 were analyzed. The outcome variables were taken to be homicide victim rates in 2005, for the entire population and for men aged 20-29 years. Measurements of economic and social development, economic inequality, demographic structure and life expectancy were analyzed as predictors. An "impunity index", calculated as the total number of homicides between 1996 and 2005 divided by the number of individuals in prison in 2007, was constructed. The data were analyzed by means of simple linear regression and negative binomial regression. RESULTS: In 2005, state-level crude total homicide rates ranged from 11 to 51 per 100,000; for young men, they ranged from 39 to 241. The impunity index ranged from 0.4 to 3.5 and was the most important predictor of this variability. From negative binomial regression, it was estimated that the homicide victim rate among young males increased by 50% for every increase of one point in this ratio. CONCLUSIONS: Classic predictive factors were not associated with homicides in this analysis of state-level variation in Brazil. However, the impunity index indicated that the greater the impunity, the higher the homicide rate.

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Hand-foot-and-mouth disease (HFMD) is becoming one of the extremely common airborne and contact transmission diseases in Guangzhou, southern China, leading public health authorities to be concerned about its increased incidence. In this study, it was used an ecological study plus the negative binomial regression to identify the epidemic status of HFMD and its relationship with meteorological variables. During 2008-2012, a total of 173,524 HFMD confirmed cases were reported, 12 cases of death, yielding a fatality rate of 0.69 per 10,000. The annual incidence rates from 2008 to 2012 were 60.56, 132.44, 311.40, 402.76, and 468.59 (per 100,000), respectively, showing a rapid increasing trend. Each 1 °C rise in temperature corresponded to an increase of 9.47% (95% CI 9.36% to 9.58%) in the weekly number of HFMD cases, while a one hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 7.53% (95% CI -7.60% to -7.45%). Similarly, each one percent rise in relative humidity corresponded to an increase of 1.48% or 3.3%, and a one meter per hour rise in wind speed corresponded to an increase of 2.18% or 4.57%, in the weekly number of HFMD cases, depending on the variables considered in the model. These findings revealed that epidemic status of HFMD in Guangzhou is characterized by high morbidity but low fatality. Weather factors had a significant influence on the incidence of HFMD.

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INTRODUCTION: The present study compares human landing catches of primary malaria vectors with two alternative methods of capture: the Shannon trap and the Mosquito magnet. METHODS: This study used regression models to adjust capture data to a negative binominal distribution. RESULTS: Capture numbers and relative percentages obtained from the three methods vary strongly between species. The highest overall captures were obtained for Anopheles triannulatus with captures for the Shannon trap and the Mosquito magnet measuring more than 330% higher than captures obtained by human landings. For Anopheles darlingi, captures by the Shannon trap and the Mosquito magnet were about 14% and 26% of human landing catches, respectively. Another species with malaria transmission potential that was not sampled by human landing captures weascaptured by the Shannon trap and the Mosquito magnet (Anopheles oswaldoi). Both alternative sampling techniques can predict the human landing of Anopheles triannulatus, but without proportionality. Models for Anopheles darlingi counts, after totaling daily captures, are significant and proportional, but prediction models are more reliable when using the Shannon trap compared with the Mosquito magnet captures. CONCLUSIONS: These alternative capture methods can be partially recommended for the substitution of human landing captures or, at least, as complementary forms of monitoring for malarial mosquitoes.

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Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.

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Introduction Since the launch of the Global Programme to Eliminate Lymphatic Filariasis, more than 70% of the endemic countries have implemented mass drug administration (MDA) to interrupt disease transmission. The monitoring of filarial infection in sentinel populations, particularly schoolchildren, is recommended to assess the impact of MDA. A key issue is choosing the appropriate tools for these initial assessments (to define the best intervention) and for monitoring transmission. Methods This study compared the pre-MDA performance of five diagnostic methods, namely, thick film test, Knott's technique, filtration, Og4C3-ELISA, and the AD12-ICT card test, in schoolchildren from Brazil. Venous and capillary blood samples were collected between 11 pm and 1 am. The microfilarial loads were analyzed with a negative binomial regression, and the prevalence and associated 95% confidence intervals were estimated for all methods. The accuracies of the AD12-ICT card and Og4C3-ELISA tests were assessed against the combination of parasitological test results. Results A total of 805 schoolchildren were examined. The overall and stratified prevalence by age group and gender detected by Og4C3-ELISA and AD12-ICT were markedly higher than the prevalence estimated by the parasitological methods. The sensitivity of the AD12-ICT card and Og4C3-ELISA tests was approximately 100%, and the positive likelihood ratios were above 6. The specificity of the Og4C3-ELISA was higher than that of the AD12-ICT at different prevalence levels. Conclusions The ICT card test should be the recommended tool for monitoring school-age populations living in areas with ongoing or completed MDA.

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Introduction The control of bacillary dysentery (BD) remains a big challenge for China. Methods Negative binomial multivariable regression was used to study relationships between meteorological variables and the occurrence of BD during the period of 2006-2012. Results Each 1°C rise of temperature corresponded to an increase of 3.60% (95%CI, 3.03% to 4.18%) in the monthly number of BD cases, whereas a 1 hPa rise in atmospheric pressure corresponded to a decrease in the number of BD cases by 2.85% (95%CI = 3.34% to 2.37% decrease). Conclusions Temperature and atmospheric pressure may be considered as predictors for the occurrence of BD in Guangzhou.

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Academics are often ranked on citation counts’, which is considered an adequate proxy for author's quality and reputation. This paper seeks to find what is behind a cited academic / a cited article. We constructed a rich dataset from Portuguese affiliated economists and use zero inflated negative binomial model. This procedure is appropriate for count outcomes, correcting for overdispersion and excess zeros. We also use a fixed effect poisson model to accomodate authors' unobserved heterogeneity. We analyze results in detail comparing with existing literature and making some theoretical considerations around.

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AbstractINTRODUCTION:Studies that generate information that may reduce the dengue death risk are essential. This study analyzed time trends and risk factors for dengue mortality and fatality in Brazil from 2001 to 2011.METHODS:Time trends for dengue mortality and fatality rates were analyzed using simple linear regression. Associations between the dengue mortality and the case fatality rates and socioeconomic, demographic, and health care indicators at the municipality level were analyzed using negative binomial regression.RESULTS:The dengue hemorrhagic fever case fatality rate increased in Brazil from 2001 to 2011 (β=0.67; p=0.036), in patients aged 0-14 years (β=0.48; p=0.030) and in those aged ≥15 years (β=1.1; p<0.01). Factors associated with the dengue case fatality rate were the average income per capita (MRR=0.99; p=0.038) and the number of basic health units per population (MRR=0.89; p<0.001). Mortality rates increased from 2001 to 2011 (β=0.350; p=0.002).Factors associated with mortality were inequality (RR=1.02; p=0.001) high income per capita (MRR=0.99; p=0.005), and higher proportions of populations living in urban areas (MRR=1.01; p<0.001).CONCLUSIONS:The increases in the dengue mortality and case fatality rates and the associated socioeconomic and health care factors, suggest the need for structural and intersectoral investments to improve living conditions and to sustainably reduce these outcomes.

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This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

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Dissertação de mestrado integrado em Engenharia Civil

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The aim of this study was to determine if mycobacterial lineages affect infection risk, clustering, and disease progression among Mycobacterium tuberculosis cases in The Netherlands. Multivariate negative binomial regression models adjusted for patient-related factors and stratified by patient ethnicity were used to determine the association between phylogenetic lineages and infectivity (mean number of positive contacts around each patient) and clustering (as defined by number of secondary cases within 2 years after diagnosis of an index case sharing the same fingerprint) indices. An estimate of progression to disease by each risk factor was calculated as a bootstrapped risk ratio of the clustering index by the infectivity index. Compared to the Euro-American reference, Mycobacterium africanum showed significantly lower infectivity and clustering indices in the foreign-born population, while Mycobacterium bovis showed significantly lower infectivity and clustering indices in the native population. Significantly lower infectivity was also observed for the East African Indian lineage in the foreign-born population. Smear positivity was a significant risk factor for increased infectivity and increased clustering. Estimates of progression to disease were significantly associated with age, sputum-smear status, and behavioral risk factors, such as alcohol and intravenous drug abuse, but not with phylogenetic lineages. In conclusion, we found evidence of a bacteriological factor influencing indicators of a strain's transmissibility, namely, a decreased ability to infect and a lower clustering index in ancient phylogenetic lineages compared to their modern counterparts. Confirmation of these findings via follow-up studies using tuberculin skin test conversion data should have important implications on M. tuberculosis control efforts.

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We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.

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This paper analyses the impact of a series of managerial and organisational factors on occupational injuries. These consist of occupational safety measures, as regards both the intensity and the orientation of risk prevention in companies, and the adoption of certain work organisation practices, quality management and the use of flexible production technologies. We estimate a negative binomial regression based on a sample of 213 Spanish industrial establishments, defining a constant random parameter to take account of non-observable heterogeneity. Our results show that occupational safety measures, the intensive use of quality management tools and the empowerment of workers all help to reduce the number of injuries. We have also confirmed the presence of synergies between the organisational factors analysed and the development of an occupational safety strategy featuring participation and the extension of prevention to all levels of the organisation.

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The Republic of Haiti is the prime international remittances recipient country in the Latin American and Caribbean (LAC) region relative to its gross domestic product (GDP). The downside of this observation may be that this country is also the first exporter of skilled workers in the world by population size. The present research uses a zero-altered negative binomial (with logit inflation) to model households' international migration decision process, and endogenous regressors' Amemiya Generalized Least Squares method (instrumental variable Tobit, IV-Tobit) to account for selectivity and endogeneity issues in assessing the impact of remittances on labor market outcomes. Results are in line with what has been found so far in this literature in terms of a decline of labor supply in the presence of remittances. However, the impact of international remittances does not seem to be important in determining recipient households' labor participation behavior, particularly for women.

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Objective: This study examines health care utilization of immigrants relative to the native-born populations aged 50 years and older in eleven European countries. Methods. We analyzed data from the Survey of Health Aging and Retirement in Europe (SHARE) from 2004 for a sample of 27,444 individuals in 11 European countries. Negative Binomial regression was conducted to examine the difference in number of doctor visits, visits to General Practitioners (GPs), and hospital stays between immigrants and the native-born individuals. Results: We find evidence those immigrants above age 50 use health services on average more than the native-born populations with the same characteristics. Our models show immigrants have between 6% and 27% more expected visits to the doctor, GP or hospital stays when compared to native-born populations in a number of European countries. Discussion: Elderly immigrant populations might be using health services more intensively due to cultural reasons.