通过食品安全认证预测食源性疾病爆发:计量经济学和机器学习分析
Yuqing Zheng1, Azucena Gracia2, Lijiao Hu3
1Department of Agricultural Economics, University of Kentucky, 313 Charles E. Barnhart Bldg., Lexington, KY 40546, United States.
Journal of food protection
|July 29, 2023
概括
美国和欧洲的食品安全认证与较少的食物传播疾病有关. 机器学习模型显示,认证数据准确地预测了疫情爆发,强调了其在食品安全方面的重要性.
科学领域:
- 农业食品系统 农业食品系统
- 食品安全法规 食品安全法规
- 公共卫生 公共卫生
背景情况:
- 自20世纪90年代末以来,食品安全认证已成为一个关键的监管工具.
- 标准保护消费者和生产者免受食物传播疾病和经济损失.
- 对认证对食源性疾病爆发的影响的实证检查至关重要.
研究的目的:
- 调查食品安全认证的采用与美国和欧洲的食品传播疾病爆发之间的关系.
- 评估食品安全认证数据对食源性疾病和死亡人数的预测能力.
- 确定认证在解释食品传播疾病爆发中的相对重要性.
主要方法:
- 使用美国各州和欧洲国家 (2015-2020) 的数据进行回归分析.
- 包含的食品安全认证 (SQF,PrimusGFS,BRC,FSSC 22000,ISO 22000) 和经济变量 (GDP).
- 应用机器学习算法 (OLS,多项式,决策树,随机森林) 用于预测建模和特征重要性分析.
主要成果:
- 在美国,认证 (SQF,PrimusGFS,BRC,FSSC 22000) 与食物传播疾病有负面关联.
- 在欧洲,证书 (ISO 22000,FSSC 22000) 显示了与食物传播疾病的负面关联.
- 机器学习模型以70%的准确度预测了美国的食源性疾病/死亡,认证数据是仅次于GDP的第二个最重要的预测指标.
结论:
- 食品安全认证在减少美国和欧洲的食源性疾病方面已被证明是有效的.
- 认证数据是食源性疾病爆发的重要预测因素,强调其在公共卫生监测中的作用.
- 政策和行业应该利用食品安全认证数据来加强食品安全管理和疫情预防.
相关概念视频
Steps in Outbreak Investigation
152
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
152
Statistical Methods for Analyzing Epidemiological Data
412
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
412
Causality in Epidemiology
477
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
477
Microorganisms in Agriculture and Food industry
88
Microorganisms play a crucial role in agriculture and the food industry, contributing to soil fertility, crop protection, and food production. Their functions range from nitrogen fixation and biopesticide production to fermentation and food preservation, making them indispensable to sustainable farming and food safety.Role in AgricultureNitrogen-fixing bacteria, such as Rhizobium (symbiotic) and Azotobacter (free-living), convert atmospheric nitrogen into ammonia through biological nitrogen...
88
Principles of Disease Surveillance
124
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
124
Statistical Software for Data Analysis and Clinical Trials
627
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
627


