This article presents an integrated epidemiological and economic framework for assessing zoonoses using a “one health” concept. The framework allows for an understanding of the cross-sector economic impact of zoonoses using modified risk analysis and detailing a range of analytical tools. The goal of the framework is to link the analysis outputs of animal and human disease transmission models, economic impact models and evaluation of risk management options to gain improved understanding of factors affecting the adoption of risk management strategies so that investment planning includes the most promising interventions (or sets of interventions) in an integrated fashion. A more complete understanding of the costs of the disease and the costs and benefits of control measures would promote broader implementation of the most efficient and effective control measures, contributing to improved animal and human health, better livelihood outcomes for the poor and macroeconomic growth.
Distribution of farmers by dead animal disposal methods, broiler production, 2003 (percent) 6.8 Distribution of farmers by dead animal disposal methods, egg production, 2003 (percent) 6.9 Distribution of farmers by dead animal disposal methods, swine production, 2003 (percent) 6.10 Environmental expenditures per kilogram output of liveweight broiler or eggs from poultry production, 2003 6.11 Environmental expenditures per kilogram output from swine production, 2003 6.12 Environmental expenditures per unit output from milk production, 2003 6.13 Determinants of farm expenditure on mitigation of environmental externalities from swine production, Thailand, 2002-03 6.14 Determinants of farm expenditure on mitigation of environmental externalities from broiler production, Thailand, 2003 6.15 Determinants of farm expenditure on mitigation of environmental externalities from broiler production, Philippines, 2002-03 6.16 Determinants of farm expenditure on mitigation of environmental externalities from swine production, Philippines, 2002-03 7.1 Mean relative profit efficiency of broiler farms across farm sizes by country, 2002 7.2 Mean relative profit efficiency of layer farms across farm sizes by country, 2002 7.3 Mean relative profit efficiency of swine farms across farm sizes by country, 2002 7.4 Mean relative profit efficiency of dairy farms across farm sizes by country, 2002 7.5 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Philippine broiler farms 7.6 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Thai broiler farms 7.7 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian broiler farms 7.8 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian layer farms 7.9 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian layer farms 7.10 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Philippine swine farms tables v 7.11 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian swine farms 7.12 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Indian dairy farms 7.13 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Thai dairy farms 7.14 Parameter estimates of stochastic profit frontier and determinants of profit inefficiency on Brazilian dairy farms 7.15 Summary of empirical results vi tables summary xi xii summary 3 Monogastrics are animals with one stomach compartment; examples are pigs and poultry. settled export-certified zone spend more per unit than smaller farms, and dairy farmers in Thailand, where the larger-scale farmers have more crop land per animal than do the smallerscale farmers in the sample. Results are backed up by a second, more conventional procedure that estimates mass balances of nutrients per hectar...
An assessment of the risk of illness associated with Escherichia coli O157:H7 in ground beef was drafted in 2001. The exposure assessment considers farm, slaughter, and preparation factors that influence the likelihood of humans consuming ground beef servings containing E. coli O157:H7 and the number of cells in a contaminated serving. Apparent seasonal differences in prevalence of cattle infected with E. coli O157:H7 corresponded to seasonal differences in human exposure. The model predicts that on average 0.018% of servings consumed during June through September and 0.007% of servings consumed during the remainder of the year are contaminated with one or more E. coli O157:H7 cells. This exposure risk is combined with the probability of illness given exposure (i.e., dose response) to estimate a U.S. population risk of illness of nearly one illness in each 1 million (9.6 x 10(-7)) servings of ground beef consumed. Uncertainty about this risk ranges from about 0.33 illness in every 1 million ground beef servings at the 5th percentile to about two illnesses in every 1 million ground beef servings at the 95th percentile.
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