Attributing human foodborne illness to food sources and water in Latin America and the Caribbean using data from outbreak investigations

Foodborne pathogens are responsible for an increasing burden of disease worldwide. Knowledge on the contribution of different food sources and water for disease is essential to prioritize food safety interventions and implement appropriate control measures. Source attribution using outbreak data utilizes readily available data from outbreak surveillance to estimate the contribution of different sources to human disease. We developed a probabilistic model based on outbreak data that attributes human foodborne disease by various bacterial pathogens to sources in Latin America and the Caribbean (LA&C). Foods implicated in outbreaks were classified by their ingredients as simple foods (i.e. belonging to one single food category), or complex foods (i.e. belonging to multiple food categories). For each agent, the data from simple-food outbreaks were summarized, and the proportion of outbreaks caused by each category was used to define the probability that an outbreak was caused by a source. For the calculation of the number of outbreaks attributed to each source, simple-food outbreaks were attributed to the single food category in question, and complex-food outbreaks were partitioned to each category proportionally to the estimated probability. We analysed all bacterial pathogens together, focused on important bacterial pathogens separately, and, when data were sufficient, performed analyses by country, decade and location. Between 1993 and 2010, 6313 bacterial outbreaks were reported by 20 countries. In general, the most important sources of bacterial disease were meat, dairy products, water and vegetables in the 1990s, and eggs, vegetables, and grains and beans in the 2000s. We observed fluctuations of the most important sources of disease for each pathogen between decades and countries, which may be a consequence of changes in the control of zoonotic disease over the years, of changes in food consumption habits, or of changes in public health focus and availability of data of different pathogens. This study identified data gaps in the region and highlighted the importance of effective surveillance systems to identify sources of disease. Still, the application of this method for source attribution in the LA&C region was successful, and we concluded that this approach can be used to attribute disease to food sources and water in other regions, including developing regions with limited data on the public health impact of foodborne diseases. (C) 2011 Elsevier B.V. All rights reserved.