Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model.

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food-pathogen pairs to provide insights for foodborne outbreak investigations.

A Series of Papaya-Associated Salmonella Illness Outbreak Investigations in 2017 and 2019: A Focus on Traceback, Laboratory, and Collaborative Efforts.

ABSTRACT: In 2017 and 2019, five outbreaks of infections from multiple strains of Salmonella linked to the consumption of whole, fresh Maradol papayas were reported in the United States, resulting in 325 ill persons. Traceback, laboratory, and epidemiologic evidence indicated papayas as the likely vehicle for each of these outbreaks and identified the source of papayas. State and U.S. Food and Drug Administration (FDA) laboratories recovered Salmonella from papaya samples from various points of distribution, including at import entry, and conducted serotyping, pulsed-field gel electrophoresis, and phylogenetic analyses of whole genome sequencing data. Federal and state partners led traceback investigations to determine the source of papayas. Four different suppliers of papayas were linked by traceback and laboratory results to five separate outbreaks of Salmonella infections associated with papayas. In 2017, multiple states tested papaya samples collected at retail, and Maryland and Virginia investigators recovered strains of Salmonella associated with one outbreak. FDA collected 183 papaya samples in 2017, and 11 samples yielded 62 isolates of Salmonella. Eleven serotypes of Salmonella were recovered from FDA papaya samples, and nine serotypes were closely related genetically by pulsed-field gel electrophoresis and whole genome sequencing to clinical isolates of four outbreaks, including the outbreak associated with positive state sample results. Four farms in Mexico were identified, and their names were released to the general public, retailers, and foreign authorities. In 2019, FDA collected 119 papaya samples, three of which yielded Salmonella; none yielded the 2019 outbreak strain. Investigators determined that papayas of interest had been sourced from a single farm in Campeche, Mexico, through traceback. This information was used to protect public health through public guidance, recalls, and import alerts and helped FDA collaborate with Mexican regulatory partners to enhance the food safety requirements for papayas imported from Mexico.

Geospatial Mapping of Early Cases in Multistate Foodborne Disease Outbreaks: A Strategy To Expedite Identification of Contaminated Imported Produce, United States, 2006 to 2013.

From 1998 to 2008, produce-related illness outbreaks accounted for roughly one-half of reported foodborne outbreaks in the United States. In 2013, Mexico accounted for approximately 50 and 30% of the monetary value of all vegetables and fruits, respectively, imported into the United States. We used historical import data to examine the correlation between the port of entry for five implicated produce vehicles from five multistate outbreaks and the geospatial and temporal distribution of illnesses in the corresponding outbreaks in the United States. For comparison, we analyzed the geospatial and temporal distribution of cases from two U.S. multistate outbreaks associated with domestically grown produce. The geospatial distribution of illnesses in the two outbreaks linked to domestic produce differed from that of the import-related produce outbreaks. The results of our pilot study suggest that geospatial distribution of early-onset cases may be used to identify ports of entry for produce likely to be responsible for causing multistate outbreaks in the United States and that targeted sampling of produce items from these ports of entry may expedite identification of an outbreak vehicle.