Dynamics of Escherichia coli O157:H7 outbreak detection and investigation, Minnesota 2000-2008

Population Structure of Listeria monocytogenes in Emilia-Romagna (Italy) and Implications on Whole Genome Sequencing Surveillance of Listeriosis

The population structure of human isolates of Listeria monocytogenes in Emilia-Romagna, Italy, from 2012 to 2018 was investigated with the aim of evaluating the presence of genomic clusters indicative of possible outbreaks, the proportion of cluster-associated vs. sporadic isolates and different methods and metrics of genomic analysis for use in routine surveillance. In the 2012–2018 period the notification rate of confirmed invasive cases in Emilia-Romagna was 0.91 per 100,000 population per year, more than twice the average rate of EU countries. Out of the total 283 cases, 268 (about 95%) isolates were typed through whole genome sequencing (WGS) for cluster detection with methods based on core-genome multi-locus sequence typing and single nucleotide polymorphisms. Between 66 and 72% of listeriosis cases belonged to genomic clusters which included up to 27 cases and lasted up to 5 years. This proportion of cluster-associated cases is higher than previously estimated in other European studies. Rarefaction analysis, performed by reducing both the number of consecutive years of surveillance considered and the proportion of isolates included in the analysis, suggested that the observed high proportion of cluster-associated cases can be ascribed to the long surveillance duration (7 years) and the high notification and typing rates of this study. Our findings show that a long temporal perspective and high surveillance intensity, intended as both exhaustiveness of the system to report cases and high WGS-typing rate, are critical for sensitive detection of possible outbreaks within a WGS-based surveillance of listeriosis. Furthermore, the power and complexity of WGS interpretation emerged from the integration of genomic and epidemiological information in the investigation of few past outbreaks within the study, indicating that the use of multiple approaches, including the analysis of the accessory genome, is needed to accurately elucidate the population dynamics of Listeria monocytogenes.

Methods for generating hypotheses in human enteric illness outbreak investigations: a scoping review of the evidence

Enteric illness outbreaks are complex events, therefore, outbreak investigators use many different hypothesis generation methods depending on the situation. This scoping review was conducted to describe methods used to generate a hypothesis during enteric illness outbreak investigations. The search included five databases and grey literature for articles published between 1 January 2000 and 2 May 2015. Relevance screening and article characterisation were conducted by two independent reviewers using pretested forms. There were 903 outbreaks that described hypothesis generation methods and 33 papers which focused on the evaluation of hypothesis generation methods. Common hypothesis generation methods described are analytic studies (64.8%), descriptive epidemiology (33.7%), food or environmental sampling (32.8%) and facility inspections (27.9%). The least common methods included the use of a single interviewer (0.4%) and investigation of outliers (0.4%). Most studies reported using two or more methods to generate hypotheses (81.2%), with 29.2% of studies reporting using four or more. The use of multiple different hypothesis generation methods both within and between outbreaks highlights the complexity of enteric illness outbreak investigations. Future research should examine the effectiveness of each method and the contexts for which each is most effective in efficiently leading to source identification.

Attributing sporadic and outbreak-associated infections to sources: blending epidemiological data

Common sources of shiga toxin-producing Escherichia coli (STEC) O157 infection have been identified by investigating outbreaks and by case-control studies of sporadic infections. We conducted an analysis to attribute STEC O157 infections ascertained in 1996 and 1999 by the Foodborne Diseases Active Surveillance Network (FoodNet) to sources. Multivariable models from two case-control studies conducted in FoodNet and outbreak investigations that occurred during the study years were used to calculate the annual number of infections attributable to six sources. Using the results of the outbreak investigations alone, 27% and 15% of infections were attributed to a source in 1996 and 1999, respectively. Combining information from both data sources, 65% of infections in 1996 and 34% of infections in 1999 were attributed. The results suggest that methods to incorporate data from multiple surveillance systems and over several years are needed to improve estimation of the number of illnesses attributable to exposure sources.