Estimating impact of white spot disease on economic risk in semi-intensive shrimp farms in Mexico: the case of the State of Sinaloa

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• 作者：Alfredo Hernandez-Llamas ; Julio Cabanillas-Ramos and Francisco J. Magallon-Barajas
• 刊名：Reviews in Aquaculture
• 出版年：2016
• 出版时间：June 2016
• 年：2016
• 卷：8
• 期：2
• 页码：111-120
• 全文大小：740K
• ISSN：1753-5131

文摘

We estimated the impact on economic risk associated with the prevalence of white spot disease in shrimp farms in the State of Sinaloa, Mexico. Farms located in the jurisdiction of Local Aquaculture Health Boards (LAHBs) were used for preparing estimates during 2008–2010. Probability distributions of economic losses were calculated by comparing net revenues obtained under normal operations and operations affected by the disease, using Monte Carlo simulation, to estimate the impact of prevalence on losses in absolute and relative terms, probability of losing and loss per unit risk at USD$484.27/ha, 28.9%, 72.9% and 0.20. Regression analysis allowed estimating that, by an increases of 1% in prevalence, there were increases in the estimators of risk of USD$11.49/ha, 0.96%, 0.47% and 0.005. Correlation analysis showed that there were significant differences in prevalence among LAHBs districts and years. The higher prevalence coincided with the districts and years that exhibited higher risk. The source of water and use of nursery systems were the main differences in operating conditions among the districts, possibly determining to a large extent the differences in economic risk calculated for the districts. Sensitivity analysis indicated that prevalence was the main factor determining risk. A significant inverse relationship was found between shrimp prices and prevalence, as a consequence of speculative market conditions. The possibility of using this relationship for syndromic surveillance is considered. We propose the use of the estimators employed in this study for assessment of economic risk associated with white spot disease (and possibly others) and standardization of results for future research.