PDF(Pubmed)
Abstract：
Mathematical models have gained traction when estimating cases of foodborne illness. Model structures vary due to differences in data availability. This begs the question as to whether differences in foodborne illness rates internationally are real or due to differences in modelling approaches.Difficulties in comparing illness rates have come into focus with COVID-19 infection rates being contrasted between countries. Furthermore, with post-EU Exit trade talks ongoing, being able to understand and compare foodborne illness rates internationally is a vital part of risk assessments related to trade in food commodities.
We compared foodborne illness estimates for the United Kingdom (UK) with those from Australia, Canada and the USA. We then undertook sensitivity analysis, by recreating the mathematical models used in each country, to understand the impact of some of the key differences in approach and to enable more like-for-like comparisons.
Published estimates of overall foodborne illness rates in the UK were lower than the other countries. However, when UK estimates were adjusted to a more like-for-like approach to the other countries, differences were smaller and often had overlapping credible intervals. When comparing rates by specific pathogens, there were fewer differences between countries. The few large differences found, such as virus rates in Canada, could at least partly be traced to methodological differences.
Foodborne illness estimation models are country specific, making international comparisons problematic. Some of the disparities in estimated rates between countries can be shown to be attributed to differences in methodology rather than real differences in risk.
We compared foodborne illness estimates for the United Kingdom (UK) with those from Australia, Canada and the USA. We then undertook sensitivity analysis, by recreating the mathematical models used in each country, to understand the impact of some of the key differences in approach and to enable more like-for-like comparisons.
Published estimates of overall foodborne illness rates in the UK were lower than the other countries. However, when UK estimates were adjusted to a more like-for-like approach to the other countries, differences were smaller and often had overlapping credible intervals. When comparing rates by specific pathogens, there were fewer differences between countries. The few large differences found, such as virus rates in Canada, could at least partly be traced to methodological differences.
Foodborne illness estimation models are country specific, making international comparisons problematic. Some of the disparities in estimated rates between countries can be shown to be attributed to differences in methodology rather than real differences in risk.
摘要：
目的：在估计食源性疾病病例时，数学模型已经获得了关注。模型结构因数据可用性的差异而不同。这就引出了一个问题，即国际食源性疾病发病率的差异是真实的还是由于建模方法的差异。比较疾病发生率的困难已经成为焦点，各国之间的COVID-19感染率正在对比。此外，随着欧盟退出后贸易谈判的进行，能够了解和比较国际食源性疾病的发病率是与食品贸易有关的风险评估的重要组成部分。
方法：我们比较了英国（UK）和澳大利亚的食源性疾病估计值，加拿大和美国。然后我们进行了敏感性分析，通过重新创建每个国家使用的数学模型，了解方法中一些关键差异的影响，并进行更多的同类比较。
结果：公布的英国食源性疾病总体发病率估计低于其他国家。然而,当英国的估计被调整为对其他国家更像的方法时，差异较小，并且通常具有重叠的可信间隔。当比较特定病原体的比率时，国家之间的差异较小。发现的几个大差异，比如加拿大的病毒发病率，至少部分可以追溯到方法上的差异。
结论：食源性疾病估计模型是针对特定国家的，使国际比较有问题。可以证明，国家之间估计费率的某些差异归因于方法的差异，而不是风险的实际差异。
方法：我们比较了英国（UK）和澳大利亚的食源性疾病估计值，加拿大和美国。然后我们进行了敏感性分析，通过重新创建每个国家使用的数学模型，了解方法中一些关键差异的影响，并进行更多的同类比较。
结果：公布的英国食源性疾病总体发病率估计低于其他国家。然而,当英国的估计被调整为对其他国家更像的方法时，差异较小，并且通常具有重叠的可信间隔。当比较特定病原体的比率时，国家之间的差异较小。发现的几个大差异，比如加拿大的病毒发病率，至少部分可以追溯到方法上的差异。
结论：食源性疾病估计模型是针对特定国家的，使国际比较有问题。可以证明，国家之间估计费率的某些差异归因于方法的差异，而不是风险的实际差异。
