[On the nature of destruction by the marmot and other rodents of oak seedlings in the Stalingrad region].
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This paper describes a k nearest neighbour statistic sensitive to the pattern of cases expected of space-time clusters of health events. The Knox and Mantel tests are frequently used for space-time clustering but have two disadvantages. First, the selection of critical space-time distances for the Knox test and of a data transformation for the Mantel test is subjective. Second, the Mantel statistic is the sum of the products of space and time distances, is linear in form, and is not sensitive to non-linear associations between small space and time distances expected of contagious processes. The k nearest neighbour statistic is the number of case pairs that are k nearest neighbours in both space and time, and is evaluated under the null hypothesis of independent space and time nearest neighbour relationships. The test was applied to simulated and real data and compared to the Knox and Mantel tests using statistical power comparisons. The k nearest neighbour test proved sensitive to the space-time interaction pattern expected of disease clusters, does not require parameters (such as critical distances) to be estimated from the data, and may be used to test hypotheses about the spatial and temporal scale of the cluster process. The method addresses significant weaknesses in existing space-time cluster tests and should prove useful in the quantification and evaluation of clusters of human health events. Additional research is needed to further document the power of the test under different cluster processes.
BACKGROUND: Logging is one of the most hazardous occupations and fatality rates are consistently among the highest of all industries. A review of fatalities caused by logs rolling off trucks is presented. METHODS: The Kentucky Fatality Assessment and Control Evaluation Project is a statewide surveillance system for occupational fatalities. Investigations are conducted on selected injuries with an emphasis on prevention strategy development. Logging was an area of high priority for case investigation. RESULTS: During 1994-1998, we identified seven incidents in which a worker was killed by a log rolling off a truck at a sawmill, accounting for 15% of the 45 deaths related to logging activities. These cases were reviewed to identify similar characteristics and risk factors. CONCLUSIONS: Investigations led to recommendations for behavioral, administrative, and engineering controls. Potential interventions include limiting load height on trucks, installing unloading cages at sawmills and prohibiting overloaded trucks on public roadways.
BACKGROUND: The logging industry has a high rate of both fatal and non-fatal injuries in comparison to other industries, and plays a vital role in WV's economy. METHODS: Workers' compensation (WC) injury claims and employment data were summarized to examine patterns and rates of non-fatal logging injuries in WV from 1995 through 2001. RESULTS: The average annual rate of injury claims was 16.0 per 100 workers per year with rates remaining relatively steady over the 7-year study period. The highest rates of injury were a result of being struck by an object, typically trees, snags, or logs. CONCLUSIONS: WV loggers most often file injury claims as a result of being struck by trees and tree parts, snags, and logs. Assessment of risk is a critical component in helping regulators, researchers, and the logging industry develop viable prevention strategies to reduce the incidence and severity of logging-related injuries.
BACKGROUND: No reliable statistics exist for injury rates among occasional woodcutters as opposed to professional loggers. Study objectives were to assess woodcutting injuries seen in emergency rooms and identify risk factors. METHODS: Individuals with woodcutting related injuries were identified in 14 emergency and urgent care departments in central and northern Wisconsin. A telephone survey was conducted within 3 weeks of presentation to determine number and types of injuries, causes, and characteristics of the injured. RESULTS: Three times as many woodcutting-related injuries occurred in non-logger survey participants (54 vs. 17). There was no significant difference in age or type of injury. Loggers were more likely to wear personal protective equipment. Younger individuals attributed their accidents to human errors, whereas older individuals felt their injuries were unavoidable. CONCLUSIONS: Occasional woodcutting activities result in comparable, but more frequent injuries than professional logging activities. Further data are needed to assess impact on public safety.
BACKGROUND: The risks associated with logging are well documented, however little work has been done on estimating the economic impact of injuries among loggers. METHODS: West Virginia Workers' Compensation claims data for the period 1996-2001 was used to assess the economic burden of logging injuries in the state. RESULTS: There were 1,371 claimants during this period with the highest number of claims (39%) in the 25-34 years age category. The total cost of injuries was over US dollars 14 million. The most severe injuries, traumatic brain injuries (TBI), thoracic, cervical, and lumbar, resulted in the highest medical costs, indemnity costs and permanent disability. The average medical cost for logging-related to TBI was US dollars 198,048 compared to US dollars 15,321 for other major industries. CONCLUSIONS: The magnitude of the economic costs underscores the need for active research of injury prevention among loggers and for greater attention to occupational safety and health programs.
Exposure patterns are reported for manufacturing and sprayer cohorts incorporated in the "IARC International Register of Workers exposed to Phenoxy Herbicides and Contaminants." Information was based on company questionnaires, company reports, plant visits, and serum 2, 3, 7, 8-TCDD measurements. In addition to phenoxy herbicides and chlorophenols, workers in manufacturing plants may have been exposed to raw materials, process chemicals, other agents synthesized or formulated, and impurities of all these agents. Sprayers also had a complex exposure pattern, including phenoxy herbicides and some other pesticides, their carriers and additives, and residues of chemicals formed during manufacture. Occurrence of agents, including dioxins, varied between countries. Biological monitoring and industrial hygiene data were rarely available, most since the late 1970s. Exposure of workers depended mainly on the jobs they performed, but several factors influenced level of exposure. A quantitative exposure classification is not feasible in this study. Semiquantitative exposure estimates may be derived through a critical interpretation of biological monitoring and industrial hygiene data together with individual work histories.
Wood trimmers and planing operators from two separate sawmill populations (N = 303 and 170) were studied by serology assessment and a self-administered questionnaire. IgG antibodies to Rhizopus microsporus ssp. rhizopodiformis, Paecilomyces variotii, and Aspergillus fumigatus were measured by ELISA. The questionnaire included questions about general respiratory symptoms and symptoms after handling moldy timber. Personal exposure of wood trimmers to mold spores and wood dust was measured in one part of the sawmills. R. microsporus was the most prevalent mold assessed by serology. Antibody levels were higher and symptoms suggestive of mucous membrane irritation, chronic nonspecific lung disease, allergic alveolitis, and organic dust toxic syndrome were more frequently reported by wood trimmers than by planing operators. The mean level of IgG antibodies to R. microsporus in sawmill workers working in the same work area was the best predictor of symptoms in both populations. The consistent results indicate that exposure to spores of R. microsporus may cause several respiratory symptoms in wood trimmers.
A triplet of function s for the statistical characterization of planar point patterns is introduced. They are related to the integral-geometric quantities area, boundary length and Euler number of patterns of discs centred at the given points. These functions are able to give information on the distribution of a given point pattern which the traditional summary statistics of point process theory do not offer and so can lead to an improved statistical description. The paper describes the statistical estimation of the new characteristics. Some examples illustrate their application in the exploratory analysis of point patterns of tree positions in forests, in comparison to results obtained by means of second-order and distance characteristics.
The influence potential on a quadrat (IPQ) is an index for measuring the ecological effect that trees have on understory vegetation observed in a quadrat of a plot. IPQ is defined as the sum of the effect of every trees in the plot, where the effect depends on the size of the tree and the distance between the tree and the quadrat. Since only the trees in the plot have been observed and not the trees outside the plot, the true IPQ may be underestimated. Existing edge corrections are not appropriate for this case. We propose a correction that consists of adding the expected IPQ due to effects of trees outside the plot to the observed IPQ. The expectation is obtained by applying the Campbell theorem for stationary marked point processes. Data from the 1985-86 National Forest Inventory of Finland was used to calculate IPQ for six quadrats systematically allocated to each of 1240 plots. The implementation of the correction for this data is described. The distributions of IPQ with and without the correction proved the existence of edge effects and the effectiveness of the correction to eliminate the bias. This method has the potential to be applied to other additive functions.
In this paper we present a nonparametric Bayesian approach for fitting unsmooth or highly oscillating functions in regression models with binary responses. The approach extends previous work by Lang et al. for Gaussian responses. Nonlinear functions are modelled by first or second order random walk priors with locally varying variances or smoothing parameters. Estimation is fully Bayesian and uses latent utility representations of binary regression models for efficient block sampling from the full conditionals of nonlinear functions.