使用跨部门数据整合过程的模型表明,减少屠宰时弯曲杆菌的交叉污染可有效降低人类弯曲杆菌病的风险

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Alessandro Foddai , Maarten Nauta , Johanne Ellis-Iversen
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引用次数: 0

摘要

对屠宰时被弯曲杆菌交叉污染的丹麦肉鸡群发生人类弯曲杆菌病的风险进行了评估。比较了国家监测数据(2018年)关于畜群弯曲杆菌状况(称为动物水平成分(AL))和准备食用的冷藏胴体污染(食品安全成分(FS))。AL部分是对3012只常规鸡群收集的粪腔拭子池的PCR检测结果,而FS部分是对(3012只中)999只随机抽样鸡群的腿皮肤进行培养检测。通过结合农场id、房屋单位和采样日期,对两个组成部分测试的鸡群进行数据集整合。CC鸡群为进入屠宰场时al阴性但fs阳性的鸡群。所有剩余的胴体阳性禽群被归类为非cc禽群。将胴体阳性群的表观流行率(AP)和每克菌落形成单位(cfu/g)(由FS分量测量)输入已发表的模拟模型,以评估三种模拟情景:2018年每次食用的平均月风险,相对于2013年(当前丹麦行动计划的参考年)。在基线场景下,维持原始AL状态和FS cfu/g。在备选方案I和II中,非CC鸡群和CC鸡群的FS cfu/g分别设为0(即负)。因此,情景1和其他两种情景之间的差异提供了CC群对AP和RR的贡献。(总体)年中位数log10 cfu/g≈2.8 (min = 1.0;max。= 4.0), 1.4 (1.0;3.9)对于CC群。基线情景和情景II的AP月中位差为7%(1月最小值为2%;8月份max = 19%),而风险差异为0.04% (0.001%;0.11%),这与情景i下的月平均风险相似。如果没有发生交叉污染(情景II),年AP将从24.3%降低到16.1%,RR将从0.92降低到0.77。因此,丹麦传统肉鸡造成的公共健康风险中约有16%似乎可归因于CC鸡群。减少交叉污染可显著降低人类弯曲杆菌病的风险。这项研究说明了如何利用跨部门监测数据整合来优化针对弯曲杆菌和其他类似食源性病原体的国家行动计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A model using an inter-sectorial data integration process indicates that reducing Campylobacter cross-contamination at slaughter mitigates the risk of human campylobacteriosis effectively

The risk of human campylobacteriosis due to Danish broiler flocks cross-contaminated (CC) at slaughter with Campylobacter spp. was assessed. National surveillance data (2018) on flock Campylobacter status (called animal level component (AL)) and on contamination of chilled carcasses ready for consumption (food safety component (FS)), were compared. The AL component consisted of PCR testing results on pools of cloacal swabs collected from 3,012 conventional flocks, while the FS component presented culture testing of leg skins from 999 (of the 3,012) randomly sampled flocks. Datasets were integrated on flocks tested in both components, by combinations of farm-ID, house-unit and sampling date. The CC flocks were those entering the slaughterhouse as AL-negative, but resulting FS-positive. All remaining carcass positive flocks were instead classified as Non-CC flocks. The apparent prevalence (AP) of carcass positive flocks and the colony forming units per gram (cfu/g), measured by the FS component, were fed into a published simulation model, to assess under three simulation scenarios: the mean monthly risk per serving during 2018, relative (RR) to that of 2013 (reference year in the current Danish Action Plan). In the baseline scenario, the original AL status and the FS cfu/g were maintained. In the alternative scenarios I and II, the FS cfu/g were set = 0 (i.e. negative) for the Non-CC and for the CC flocks, respectively. Thus, scenario I and the differences between the other two scenarios, provided the contribution of the CC flocks to the AP and to the RR. The (overall) annual median log10 cfu/g was ≈ 2.8 (min. = 1.0; max. = 4.0) for the Non-CC flocks and 1.4 (1.0; 3.9) for the CC flocks. The median monthly difference in AP, between the baseline scenario and scenario II was 7% (min = 2% in January; max = 19% in August), while the difference in risk was 0.04% (0.001%; 0.11%), which was similar to the mean monthly risk under scenario I. If cross-contamination had not occurred (scenario II), the annual AP would have reduced from 24.3% to 16.1% and the RR would have reduced from 0.92 to 0.77. Therefore, ≈16% of the public health risk posed by Danish conventional broiler meat, appeared attributable to CC flocks. Reducing cross-contamination could mitigate the risk of human campylobacteriosis notably. This study illustrates how inter-sectorial surveillance data integration, can be used to optimize National Action Plans against Campylobacter spp. and other similar foodborne pathogens.

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来源期刊
Microbial Risk Analysis
Microbial Risk Analysis Medicine-Microbiology (medical)
CiteScore
5.70
自引率
7.10%
发文量
28
审稿时长
52 days
期刊介绍: The journal Microbial Risk Analysis accepts articles dealing with the study of risk analysis applied to microbial hazards. Manuscripts should at least cover any of the components of risk assessment (risk characterization, exposure assessment, etc.), risk management and/or risk communication in any microbiology field (clinical, environmental, food, veterinary, etc.). This journal also accepts article dealing with predictive microbiology, quantitative microbial ecology, mathematical modeling, risk studies applied to microbial ecology, quantitative microbiology for epidemiological studies, statistical methods applied to microbiology, and laws and regulatory policies aimed at lessening the risk of microbial hazards. Work focusing on risk studies of viruses, parasites, microbial toxins, antimicrobial resistant organisms, genetically modified organisms (GMOs), and recombinant DNA products are also acceptable.
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