Methods for Quantification of Soil-Transmitted Helminths in Environmental Media: Current Techniques and Recent Advances.

Limiting the environmental transmission of soil-transmitted helminths (STHs), which infect 1.5 billion people worldwide, will require sensitive, reliable, and cost-effective methods to detect and quantify STHs in the environment. We review the state-of-the-art of STH quantification in soil, biosolids, water, produce, and vegetation with regard to four major methodological issues: environmental sampling; recovery of STHs from environmental matrices; quantification of recovered STHs; and viability assessment of STH ova. We conclude that methods for sampling and recovering STHs require substantial advances to provide reliable measurements for STH control. Recent innovations in the use of automated image identification and developments in molecular genetic assays offer considerable promise for improving quantification and viability assessment

Mean-Gini analysis of stochastic externalities: The case of groundwater contamination

The mean-Gini approach is used to analyze stochastic externalities generated by agricultural production. The model addresses the problem of groundwater pollution caused by excessive fertilizer application. Inherent in the mean-Gini approach to expected utility maximization is a two-fold value: the simplicity of the two-parameter mean-variance model and satisfaction of necessary and sufficient conditions for stochastic dominance. Price and quantity policy recommendations to control externalities are formulated based upon the relative assessment of uncertainty by the regulatory authority and the farmers. Using the Gini as a measure of risk allows for the quantification of control policy measures under differentiated risk aversion and multiple sources of pollution. The model shows that when producers underestimate uncertainty, quota policies restricting fertilizer are more efficient than tax policies in reducing groundwater contamination. Copyright Kluwer Academic Publishers 1995Stochastic externalities, water pollution policies, stochastic dominance,