Can foodborne illness estimates from different countries be legitimately compared?: case study of rates in the UK compared with Australia, Canada and USA

OBJECTIVE: 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. DESIGN: 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. RESULTS: 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. CONCLUSION: 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.