The method of processing and the results of measurements of 131I content in the thyroids of Russian people performed in May-June 1986 are presented. The contribution of radiation from Cs radionuclides in the human body was taken into account in the processing of measurement data with an SRP-68-01 device. The greatest individual 131I content was found in the thyroids of inhabitants of the Bryansk region, up to 250-350 kBq, and in the Tula and Orel regions, up to 100 kBq. The average 131I thyroid activity in the middle of May 1986 reached 80 kBq for inhabitants of some settlements in the Bryansk region, 5-8 kBq in the Tula region and 5 kBq in the Orel region.
Systematic conservation plans have only recently considered the dynamic nature of ecosystems. Methods have been developed to incorporate climate change, population dynamics, and uncertainty in reserve design, but few studies have examined how to account for natural disturbance. Considering natural disturbance in reserve design may be especially important for the world's remaining intact areas, which still experience active natural disturbance regimes. We developed a spatially explicit, dynamic simulation model, CONSERV, which simulates patch dynamics and fire, and used it to evaluate the efficacy of hypothetical reserve networks in northern Canada. We designed six networks based on conventional reserve design methods, with different conservation targets for woodland caribou habitat, high-quality wetlands, vegetation, water bodies, and relative connectedness. We input the six reserve networks into CONSERV and tracked the ability of each to maintain initial conservation targets through time under an active natural disturbance regime. None of the reserve networks maintained all initial targets, and some over-represented certain features, suggesting that both effectiveness and efficiency of reserve design could be improved through use of spatially explicit dynamic simulation during the planning process. Spatial simulation models of landscape dynamics are commonly used in natural resource management, but we provide the first illustration of their potential use for reserve design. Spatial simulation models could be used iteratively to evaluate competing reserve designs and select targets that have a higher likelihood of being maintained through time. Such models could be combined with dynamic planning techniques to develop a general theory for reserve design in an uncertain world.
OBJECTIVE: Fetal urine production at different gestational ages has been evaluated using ultrasound in several previous studies. In a recent study, we investigated the accuracy when estimating the bladder volume using the conventional ultrasound technique and found a total variability of 17.3-10.9% for bladder volumes of 5-40 mL. The variability is mainly caused by: (i) inappropriate image selection (the 'freezing error') and (ii) limitations when measuring on the frozen image (the 'frozen error'). The aim of this study was to reduce the total error by reducing the 'freezing' and the 'frozen error'. To this end, we used a modified manual ultrasound technique (adding a 'rocking' motion to the conventional method) and digitized the selected image. METHODS: Two patients for each gestational week from 24 to 40 weeks were selected. The fetal urinary bladder was examined with ultrasound three times within 1 min and documented on videotape. The volume, as assessed by the longitudinal section of the recorded bladder images, stored in digitized form, was evaluated on three occasions with > 24 h in between. The mean and variability (standard deviation, SD) were estimated. RESULTS: For fetal bladder volumes between 5 and 40 mL, the 'freezing error' (SD), the 'frozen error' and the 'total error' were 11.7-5.1%, 8.0-3.0% and 14.2-5.9%, respectively. Comparing the present with a previous study, when selecting images and assessing bladder volumes repeatedly within 1 min, SD was 12.9-5.5% vs. 17.3-10.9%. CONCLUSIONS: Using a modified ultrasound technique, the variability in fetal bladder volume estimation can be reduced.
Assessment of image analysis methods and computer software used in (99m) Tc-MAG3 dynamic renography is important to ensure reliable study results and ultimately the best possible care for patients. In this work, we present a national multicentre study of the quantification accuracy in (99m) Tc-MAG3 renography, utilizing virtual dynamic scintigraphic data obtained by Monte Carlo-simulated scintillation camera imaging of digital phantoms with time-varying activity distributions. Three digital phantom studies were distributed to the participating departments, and quantitative evaluation was performed with standard clinical software according to local routines. The differential renal function (DRF) and time to maximum renal activity (Tmax ) were reported by 21 of the 28 Swedish departments performing (99m) Tc-MAG3 studies as of 2012. The reported DRF estimates showed a significantly lower precision for the phantom with impaired renal uptake than for the phantom with normal uptake. The Tmax estimates showed a similar trend, but the difference was only significant for the right kidney. There was a significant bias in the measured DRF for all phantoms caused by different positions of the left and right kidney in the anterior-posterior direction. In conclusion, this study shows that virtual scintigraphic studies are applicable for quality assurance and that there is a considerable uncertainty associated with standard quantitative parameters in dynamic (99m) Tc-MAG3 renography, especially for patients with impaired renal function.
Existing methods for estimating historical effective population size from genetic data have been unable to accurately estimate effective population size during the most recent past. We present a non-parametric method for accurately estimating recent effective population size by using inferred long segments of identity by descent (IBD). We found that inferred segments of IBD contain information about effective population size from around 4 generations to around 50 generations ago for SNP array data and to over 200 generations ago for sequence data. In human populations that we examined, the estimates of effective size were approximately one-third of the census size. We estimate the effective population size of European-ancestry individuals in the UK four generations ago to be eight million and the effective population size of Finland four generations ago to be 0.7 million. Our method is implemented in the open-source IBDNe software package.
Cites: Genetics. 1971 Aug;68(4):581-975166069
Cites: Proc Biol Sci. 2013 Oct 7;280(1768):2013133923926150
Cites: Am J Hum Genet. 2013 Nov 7;93(5):840-5124207118
This paper discusses the misclassification that occurs when relying solely on routine register data in family studies of disease clustering. A register study of familial aggregation of schizophrenia is used as an example. The familial aggregation is studied using a regression model for the disease in the child including the disease status of the parents as a risk factor. If all the information is found in the routine registers then the disease status of the parents is only known from the time when the register started and if this information is used unquestioningly the parents who have had the disease before this time are misclassified as disease-free. Two methods are presented to adjust for this misclassification: regression calibration and an EM-type algorithm. These methods are used in the schizophrenia example where the large effect of having a schizophrenic mother hardly shows any signs of bias due to misclassification. The methods are also studied in simulations showing that the misclassification problem increases with the disease frequency.
The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.
To examine the incidence, mortality and case fatality of acute coronary syndrome (ACS) in Finland during 1993-2007 and to create forecasts of the absolute numbers of ACS cases in the future, taking into account the aging of the population.
Community surveillance study and modelled forecasts of the future.
Two sets of population-based coronary event register data from Finland (FINAMI and the National Cardiovascular Disease Register (CVDR)). Bayesian age-period-cohort (APC) modelling.
24 905 observed ACS events in the FINAMI register and 364 137 in CVDR.
Observed trends of ACS events during 1993-2007, forecasted numbers of ACS cases, and the prevalence of ACS survivors until the year 2050.
In the FINAMI register, the average annual declines in age-standardised incidence of ACS were 1.6% (p
This report provides the methodology and findings from the project: Air Pollution and Health: a European and North American Approach (APHENA). The principal purpose of the project was to provide an understanding of the degree of consistency among findings of multicity time-series studies on the effects of air pollution on mortality and hospitalization in several North American and European cities. The project included parallel and combined analyses of existing data. The investigators sought to understand how methodological differences might contribute to variation in effect estimates from different studies, to characterize the extent of heterogeneity in effect estimates, and to evaluate determinants of heterogeneity. The APHENA project was based on data collected by three groups of investigators for three earlier studies: (1) Air Pollution and Health: A European Approach (APHEA), which comprised two multicity projects in Europe. (Phase 1 [APHEA1] involving 15 cities, and Phase 2 [APHEA2] involving 32 cities); (2) the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), conducted in the 90 largest U.S. cities; and (3) multicity research on the health effects of air pollution in 12 Canadian cities.
The project involved the initial development of analytic approaches for first-stage and second-stage analyses of the time-series data and the subsequent application of the resulting methods to the time-series data. With regard to the first-stage analysis, the various investigative groups had used conceptually similar approaches to the key issues of controlling for temporal confounding and temperature; however, specific methods differed. Consequently, the investigators needed to establish a standard protocol, but one that would be linked to prior approaches. Based on exploratory analyses and simulation studies, a first-stage analysis protocol was developed that used generalized linear models (GLM) with either penalized splines (PS) or natural splines (NS) to adjust for seasonality, with 3, 8, or 12 degrees of freedom (df) per year and also the number of degrees of freedom chosen by minimizing the partial autocorrelation function (PACF) of the model's residuals. For hospitalization data, the approach for model specification followed that used for mortality, accounting for seasonal patterns, but also, for weekend and vacation effects, and for epidemics of respiratory disease. The data were also analyzed to detect potential thresholds in the concentration-response relationships. The second-stage analysis used pooling approaches and assessed potential effect modification by sociodemographic characteristics and indicators of the pollution mixture across study regions. Specific quality control exercises were also undertaken. Risks were estimated for two pollutants: particulate matter - 10 pm in aerodynamic diameter (PM10) and ozone (O3).
The first-stage analysis yielded estimates that were relatively robust to the underlying smoothing approach and to the number of degrees of freedom. The first-stage APHENA results generally replicated the previous independent analyses performed by the three groups of investigators. PM10 effects on mortality risk estimates from the APHEA2 and NMMAPS databases were quite close, while estimates from the Canadian studies were substantially higher. For hospitalization, results were more variable without discernable patterns of variation among the three data sets. PM10 effect-modification patterns, explored only for cities with daily pollution data (i.e., 22 in Europe and 15 in the U.S.), were not entirely consistent across centers. Thus, the levels of pollutants modified the effects differently in Europe than in the United States. Climatic variables were important only in Europe. In both Europe and the United States, a higher proportion of older persons in the study population was associated with increased PM10 risk estimates, as was a higher rate of unemployment - the sole indicator of socioeconomic status uniformly available across the data sets. APHENA study results on the effects of O3 on mortality were less comprehensive than for PM10 because the studies from the three regions varied in whether they analyzed data for the full year or only for the summer months. The effects tended to be larger for summer in Europe and the United States. In the United States they were lower when controlled for PM10. The estimated effect of O3 varied by degrees of freedom and across the three geographic regions. The effects of O3 on mortality were larger in Canada, and there was little consistent indication of effect modification in any location.
APHENA has shown that mortality findings obtained with the new standardized analysis were generally comparable to those obtained in the earlier studies, and that they were relatively robust to the data analysis method used. For PM10, the effect-modification patterns observed were not entirely consistent between Europe and the United States. For O3, there was no indication of strong effect modification in any of the three data sets.