819 resultados para Regional population forecasting, service provision, box-Jenkins model
Resumo:
Escherichia coli is commonly involved in infections with a heavy bacterial burden. Piperacillin-tazobactam and carbapenems are among the recommended empirical treatments for health care-associated complicated intra-abdominal infections. In contrast to amoxicillin-clavulanate, both have reduced in vitro activity in the presence of high concentrations of extended-spectrum β-lactamase (ESBL)-producing and non-ESBL-producing E. coli bacteria. Our goal was to compare the efficacy of these antimicrobials against different concentrations of two clinical E. coli strains, one an ESBL-producer and the other a non-ESBL-producer, in a murine sepsis model. An experimental sepsis model {~5.5 log10 CFU/g [low inoculum concentration (LI)] or ~7.5 log(10) CFU/g [high inoculum concentration (HI)]} using E. coli strains ATCC 25922 (non-ESBL producer) and Ec1062 (CTX-M-14 producer), which are susceptible to the three antimicrobials, was used. Amoxicillin-clavulanate (50/12.5 mg/kg given intramuscularly [i.m.]), piperacillin-tazobactam (25/3.125 mg/kg given intraperitoneally [i.p.]), and imipenem (30 mg/kg i.m.) were used. Piperacillin-tazobactam and imipenem reduced spleen ATCC 25922 strain concentrations (-2.53 and -2.14 log10 CFU/g [P < 0.05, respectively]) in the HI versus LI groups, while amoxicillin-clavulanate maintained its efficacy (-1.01 log10 CFU/g [no statistically significant difference]). Regarding the Ec1062 strain, the antimicrobials showed lower efficacy in the HI than in the LI groups: -0.73, -1.89, and -1.62 log10 CFU/g (P < 0.05, for piperacillin-tazobactam, imipenem, and amoxicillin-clavulanate, respectively, although imipenem and amoxicillin-clavulanate were more efficacious than piperacillin-tazobactam). An adapted imipenem treatment (based on the time for which the serum drug concentration remained above the MIC obtained with a HI of the ATCC 25922 strain) improved its efficacy to -1.67 log10 CFU/g (P < 0.05). These results suggest that amoxicillin-clavulanate could be an alternative to imipenem treatment of infections caused by ESBL- and non-ESBL-producing E. coli strains in patients with therapeutic failure with piperacillin-tazobactam.
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BACKGROUND The demographic structure has a significant influence on the use of healthcare services, as does the size of the population denominators. Very few studies have been published on methods for estimating the real population such as tourist resorts. The lack of information about these problems means there is a corresponding lack of information about the behaviour of populational denominators (the floating population or tourist load) and the effect of this on the use of healthcare services. The objectives of the study were: a) To determine the Municipal Solid Waste (MSW) ratio, per person per day, among populations of known size; b) to estimate, by means of this ratio, the real population in an area where tourist numbers are very significant; and c) to determine the impact on the utilisation of hospital emergency healthcare services of the registered population, in comparison to the non-resident population, in two areas where tourist numbers are very significant. METHODS An ecological study design was employed. We analysed the Healthcare Districts of the Costa del Sol and the island of Menorca. Both are Spanish territories in the Mediterranean region. RESULTS In the two areas analysed, the correlation coefficient between the MSW ratio and admissions to hospital emergency departments exceeded 0.9, with p < 0.001. On the basis of MSW generation ratios, obtained for a control zone and also measured in neighbouring countries, we estimated the real population. For the summer months, when tourist activity is greatest and demand for emergency healthcare at hospitals is highest, this value was found to be double that of the registered population. CONCLUSION The MSW indicator, which is both ecological and indirect, can be used to estimate the real population in areas where population levels vary significantly during the year. This parameter is of interest in planning and dimensioning the provision of healthcare services.
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Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.
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Background: Understanding the true prevalence of lymphangioleiomyomatosis (LAM) is important in estimating disease burden and targeting specific interventions. As with all rare diseases, obtaining reliable epidemiological data is difficult and requires innovative approaches.Aim: To determine the prevalence and incidence of LAM using data from patient organizations in seven countries, and to use the extent to which the prevalence of LAM varies regionally and nationally to determine whether prevalence estimates are related to health-care provision.Methods: Numbers of women with LAM were obtained from patient groups and national databases from seven countries (n = 1001). Prevalence was calculated for regions within countries using female population figures from census data. Incidence estimates were calculated for the USA, UK and Switzerland. Regional variation in prevalence and changes in incidence over time were analysed using Poisson regression and linear regression.Results: Prevalence of LAM in the seven countries ranged from 3.4 to 7.8/million women with significant variation, both between countries and between states in the USA. This variation did not relate to the number of pulmonary specialists in the region nor the percentage of population with health insurance, but suggests a large number of patients remain undiagnosed. The incidence of LAM from 2004 to 2008 ranged from 0.23 to 0.31/million women/per year in the USA, UK and Switzerland.Conclusions: Using this method, we have found that the prevalence of LAM is higher than that previously recorded and that many patients with LAM are undiagnosed.
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In South America, yellow fever (YF) is an established infectious disease that has been identified outside of its traditional endemic areas, affecting human and nonhuman primate (NHP) populations. In the epidemics that occurred in Argentina between 2007-2009, several outbreaks affecting humans and howler monkeys (Alouatta spp) were reported, highlighting the importance of this disease in the context of conservation medicine and public health policies. Considering the lack of information about YF dynamics in New World NHP, our main goal was to apply modelling tools to better understand YF transmission dynamics among endangered brown howler monkey (Alouatta guariba clamitans) populations in northeastern Argentina. Two complementary modelling tools were used to evaluate brown howler population dynamics in the presence of the disease: Vortex, a stochastic demographic simulation model, and Outbreak, a stochastic disease epidemiology simulation. The baseline model of YF disease epidemiology predicted a very high probability of population decline over the next 100 years. We believe the modelling approach discussed here is a reasonable description of the disease and its effects on the howler monkey population and can be useful to support evidence-based decision-making to guide actions at a regional level.
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Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.
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Habitat restoration measures may result in artificially high breeding density, for instance when nest-boxes saturate the environment, which can negatively impact species' demography. Potential risks include changes in mating and reproductive behaviour such as increased extra-pair paternity, conspecific brood parasitism, and polygyny. Under particular cicumstances, these mechanisms may disrupt reproduction, with populations dragged into an extinction vortex. With the use of nuclear microsatellite markers, we investigated the occurrence of these potentially negative effects in a recovered population of a rare secondary cavity-nesting farmland bird of Central Europe, the hoopoe (Upupa epops). High intensity farming in the study area has resulted in a total eradication of cavity trees, depriving hoopoes from breeding sites. An intensive nest-box campaign rectified this problem, resulting in a spectacular population recovery within a few years only. There was some concern, however, that the new, high artificially-induced breeding density might alter hoopoe mating and reproductive behaviour. As the species underwent a serious demographic bottleneck in the 1970-1990s, we also used the microsatellite markers to reconstitute the demo-genetic history of the population, looking in particular for signs of genetic erosion. We found i) a low occurrence of extra-pair paternity, polygyny and conspecific brood parasitism, ii) a high level of neutral genetic diversity (mean number of alleles and expected heterozygosity per locus: 13.8 and 83%, respectively) and, iii) evidence for genetic connectivity through recent immigration of individuals from well differentiated populations. The recent increase in breeding density did thus not induce so far any noticeable detrimental changes in mating and reproductive behaviour. The demographic bottleneck undergone by the population in the 1970s-1990s was furthermore not accompanied by any significant drop in neutral genetic diversity. Finally, genetic data converged with a concomitant demographic study to evidence that immigration strongly contributed to local population recovery.
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BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.
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In this paper we examine some of the economic forces that underlie economic growth at the county level. In an effort to describe a much more comprehensive regional economic growth model, we address a variety of different growth hypotheses by introducing a large number of growth related variables. When formulating our hypotheses and specifying our growth model we make liberal use of GIS (geographical information systems) mapping software to “paint” a picture of where growth spots exist. Our empirical estimation indicates that amenities, state and local tax burdens, population, amount of primary agriculture activity, and demographics have important impacts on economic growth.
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The data of the 1981-83 Swiss National Health Survey "SOMIPOPS", based on a randomly selected sample of 4,235 individuals aged 20 or over representative of the whole Swiss population, were used to investigate the relation between smoking, prevalence of disease and frequency of health care utilization. The risks of several conditions, including hypertension, myocardial infarction and other heart diseases, asthma, tuberculosis and kidney disease were elevated among ex-smokers. The diseases showing elevated risks among current smokers and significantly positive dose-risk trends included acute bronchitis (relative risk, RR = 3.2 for heavy cigarette smokers vs never smokers), chronic bronchitis or lung emphysema (RR = 2.0), gastro-duodenal ulcer (RR = 1.8) and bone fractures (RR = 1.6). For respiratory conditions, the risk of pipe or cigar smokers was comparable to that of moderate cigarette smokers, whereas for ulcer (RR = 4.1) or fractures (RR = 2.0) the point estimates were even higher than for heavy cigarette smokers. Smokers tended to consult more frequently general practitioners, used more other outpatients services, and were more frequently admitted to hospital during the year preceding the interview. These effects were consistent across strata of age, socio-economic indicators, and persisted after allowance for major identified potential distorting factors. Thus, the results of this survey confirm that smoking is an important cause of morbidity and a major contributory factor to the use of health services.
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A complete life cycle model for northern corn rootworm, Diabrotica barberi Smith and Lawrence, is developed using a published single-season model of adult population dynamics and data from field experiments. Temperature-dependent development and age-dependent advancement determine adult population dynamics and oviposition, while a simple stochastic hatch and density-dependent larval survival model determine adult emergence. Dispersal is not modeled. To evaluate the long-run performance of the model, stochastically generated daily air and soil temperatures are used for 100-year simulations for a variety of corn planting and flowering dates in Ithaca, NY, and Brookings, SD. Once the model is corrected for a bias in oviposition, model predictions for both locations are consistent with anecdotal field data. Extinctions still occur, but these may be consistent with northern corn rootworm metapopulation dynamics.
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Coherent regulation of landscape as a resource is a major challenge. How can the development interests of some actors (eg cable car operators and property developers) be reconciled with those of others (agriculture, forestry) and with conservation of biodiversity and scenic value? To help understand how the newly introduced Regional Nature Parks (RNPs) can improve the coherence of the regulation regime in Switzerland, we highlight current direct mechanisms for regulation of landscape as a resource (bans, inventories, subsidies) as well as indirect mechanisms (taking place through the regulation of the physical basis of landscapes, eg forest, land, and water planning policies). We show that RNPs are fundamentally innovative because they make it possible to manage and coordinate indirect strategies for appropriate regulation of resources at a landscape scale. In other words, RNPs enable organization of governance of landscape as a resource in a perimeter that is not necessarily restricted to administrative boundaries.
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This is an article about the theoretical model for assessing quality in health services proposed by Parasuraman, Zheitaml and Berry, in order to measure the degree of satisfaction of users. This model is based on the analysis of expectations and perceptions of users of health services, by means of five dimensions: tangibility, reliability, responsiveness, assurance and empathy. From the difference between what is expected by the user and the service offered, gaps or shortcomings are derived that may be the main obstacle for users to perceive the provision of such services with quality. It was observed that the use of the psychometric scale called Service Quality (SERVQUAL) in some studies about satisfaction, obtained very favorable results in the institutions in which it was employed. The analysis revealed the need to improve the existing models of evaluation, as well as the importance of measuring user satisfaction in health institutions.