Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown

PROBLEM: There are no specific indicators for distinguishing insurance claims related to speeding and impaired driving in the information warehouse at the Insurance Corporation of British Columbia. Contributing factors are only recorded for that part of the claim data that is also reported by the police. Most published statistics on crashes that are related to alcohol or speeding are based on police-reported data, but this represents only a fraction of all incidents. METHOD: This paper proposes surrogate models to estimate the counts and the average costs associated with speeding and impaired driving to insurance claims when contributing factors are unknown. Using police-reported data, classification rules and logistic regression models are developed to form such estimates. One approach applies classification rules to categorize insurance claims into those related to speeding, impaired driving, and other factors. The counts and the costs of insurance claims for each of these strata and overall are then estimated. A second method models the probability that an insurance claim is related to speeding or impaired driving using logistic regression and uses this to estimate the overall counts and the average costs of the claims. The two methods are compared and evaluated using simulation studies. RESULTS: The logistic regression model was found to be superior to the classification model for predicting insurance claim counts by category, but less efficient at predicting average claim costs. IMPACT: Having estimates of counts and costs of insurance claims related to impaired driving or speeding for all reported crash events provides a more accurate basis for policy-makers to plan changes and benefits of road safety programs.     

Characterization of phosphorus species in biosolids and manures using XANES spectroscopy

Identification of the chemical P species in biosolids or manures will improve our understanding of the long-term potential for P loss when these materials are land applied. The objectives of this study were to determine the P species in dairy manures, poultry litters, and biosolids using X-ray absorption near-edge structure (XANES) spectroscopy and to determine if chemical fractionation techniques can provide useful information when interpreted based on the results of more definitive P speciation studies. Our XANES fitting results indicated that the predominant forms of P in organic P sources included hydroxylapatite, PO(4) sorbed to Al hydroxides, and phytic acid in lime-stabilized biosolids and manures; hydroxylapatite, PO(4) sorbed on ferrihydrite, and phytic acid in lime- and Fe-treated biosolids; and PO(4) sorbed on ferrihydrite, hydroxylapatite, beta-tricalcium phosphate (beta-TCP), and often PO(4) sorbed to Al hydroxides in Fe-treated and digested biosolids. Strong relationships existed between the proportions of XANES PO(4) sorbed to Al hydroxides and NH(4)Cl- + NH(4)F-extractable P, XANES PO(4) sorbed to ferrihydrite + phytic acid and NaOH-extractable P, and XANES hydroxylapatite + beta-TCP and dithionite-citrate-bicarbonate (DCB)- + H(2)SO(4)-extractable P (r(2) = 0.67 [P = 0.01], 0.78 [P = 0.01], and 0.89 [P = 0.001], respectively). Our XANES fitting results can be used to make predictions about long-term solubility of P when biosolids and manures are land applied. Fractionation techniques indicate that there are differences in the forms of P in these materials but should be interpreted based on P speciation data obtained using more advanced analytical tools.     

Hydrography Change Detection: The Usefulness of Surface Channels Derived From LiDAR DEMs for Updating Mapped Hydrography1

Abstract: The 1:24,000‐scale high‐resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time‐relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR‐derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.     

Capsid and Infectivity in Virus Detection

The spectacular achievements and elegance of viral RNA analyses have somewhat obscured the importance of the capsid in transmission of viruses via food and water. The capsid’s essential roles are protection of the RNA when the virion is outside the host cell and initiation of infection when the virion contacts a receptor on an appropriate host cell. Capsids of environmentally transmitted viruses are phenomenally durable. Fortuitous properties of the capsid include antigenicity, isoelectric point(s), sometimes hemagglutination, and perhaps others. These can potentially be used to characterize capsid changes that cause or accompany loss of viral infectivity and may be valuable in distinguishing native from inactivated virus when molecular detection methods are used.     

Agricultural and recreational impacts of the conservation reserve program in rural North Dakota, USA

The Conservation Reserve Program (CRP), created in 1985, provides conservation benefits and agricultural supply control through voluntary, long-term retirement of crop land. While the effects of the CRP on the agricultural sector are well understood, the implications of its conservation benefits for rural economies remain largely undocumented. To quantify the effects on rural economies, this study addressed the net economic effects of decreased agricultural activity and increased recreational activity associated with the CRP in six rural areas of North Dakota from 1996 to 2000. Based on the level of economic activity that would have occurred in the absence of the program, net revenues from CRP land if returned to agricultural production in the six study areas were estimated at $50.2 million annually or $37 per acre of land currently enrolled in the CRP. Recreational (hunting) revenues as a result of the CRP in the study areas were estimated at $12.8 million annually or $9.45 per CRP-acre. The net economic effect of the CRP (lost agricultural revenues and gains in recreational expenditures) indicated that several areas of the state are not as economically burdened by the CRP as previous research has suggested. In addition, the net economic effects of the program would appear more favourable if revenues from all CRP-based recreation were included. The degree that recreational revenues offset agricultural losses might be further enhanced by enterprises that capitalize on the economic opportunities associated with expanded recreational activities on CRP lands.