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日本牛海绵状脑病的定量风险评估。

A quantitative risk assessment for bovine spongiform encephalopathy in Japan.

机构信息

Field Center of Animal Science and Agriculture, Obihiro University of Agriculture and Veterinary Medicine,W2 - 11, Inada-cho, Obihiro, 080-8555, Japan.

出版信息

Risk Anal. 2012 Dec;32(12):2198-208. doi: 10.1111/j.1539-6924.2012.01846.x. Epub 2012 May 29.

Abstract

A predictive case-cohort model was applied to Japanese data to analyze the interaction between challenge and stability factors for bovine spongiform encephalopathy (BSE) for the period 1985-2020. BSE risk in cattle was estimated as the expected number of detectable cases per year. The model was comprised of a stochastic spreadsheet calculation model with the following inputs: (1) the origin and quantity of live cattle and meat and bone meal imported into Japan, (2) the age distribution of native cattle, and (3) the estimated annual basic reproduction ratio (R(0) ) for BSE. The estimated probability of having zero detectable cases in Japan in 2015 was 0.90 (95% CI 0.83-0.95). The corresponding value for 2020 was 0.99 (95% CI 0.98-0.99). The model predicted that detectable cases may occur in Japan beyond 2015 because of the assumption that continued transmission was permitted to occur (albeit at a very low level) after the 2001 ban on the importation and domestic use of all processed animal proteins for the production of animal feed and for fertilizer. These results reinforce the need for animal health authorities to monitor the efficacy of control measures so that the future course of the BSE epidemic in Japan can be predicted with greater certainty.

摘要

应用预测病例-队列模型分析了日本 1985-2020 年期间牛海绵状脑病(BSE)挑战和稳定因素之间的相互作用。通过估计每年每头可检测到的牛的数量来评估牛的 BSE 风险。该模型由一个具有以下输入的随机电子表格计算模型组成:(1)输入活牛和肉骨粉的进口来源和数量,(2)本国牛的年龄分布,以及(3)BSE 的估计年基本繁殖率(R(0))。该模型预测,由于假设在 2001 年禁止进口和国内使用所有用于动物饲料和肥料生产的加工动物蛋白后,仍允许继续发生(尽管处于极低水平)传播,因此日本在 2015 年后可能会出现可检测到的病例。模型预测,日本在 2015 年后可能会出现可检测到的病例,因为假设在 2001 年禁止进口和国内使用所有用于生产动物饲料和肥料的加工动物蛋白后,仍允许继续发生(尽管处于极低水平)传播。这些结果强调了动物卫生当局需要监测控制措施的效果,以便更有把握地预测日本 BSE 疫情的未来发展。

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