Salmonella enterica serovar Enteritidis phage type 4 outbreak associated with eggs in a large prison, London 2009: an investigation using cohort and case/non-case study methodology

Diagnostic accuracy of symptoms for an underlying disease: a simulation study

Symptoms have been used to diagnose conditions such as frailty and mental illnesses. However, the diagnostic accuracy of the numbers of symptoms has not been well studied. This study aims to use equations and simulations to demonstrate how the factors that determine symptom incidence influence symptoms' diagnostic accuracy for disease diagnosis. Assuming a disease causing symptoms and correlated with the other disease in 10,000 simulated subjects, 40 symptoms occurred based on 3 epidemiological measures: proportions diseased, baseline symptom incidence (among those not diseased), and risk ratios. Symptoms occurred with similar correlation coefficients. The sensitivities and specificities of single symptoms for disease diagnosis were exhibited as equations using the three epidemiological measures and approximated using linear regression in simulated populations. The areas under curves (AUCs) of the receiver operating characteristic (ROC) curves was the measure to determine the diagnostic accuracy of multiple symptoms, derived by using 2 to 40 symptoms for disease diagnosis. With respect to each AUC, the best set of sensitivity and specificity, whose difference with 1 in the absolute value was maximal, was chosen. The results showed sensitivities and specificities of single symptoms for disease diagnosis were fully explained with the three epidemiological measures in simulated subjects. The AUCs increased or decreased with more symptoms used for disease diagnosis, when the risk ratios were greater or less than 1, respectively. Based on the AUCs, with risk ratios were similar to 1, symptoms did not provide diagnostic values. When risk ratios were greater or less than 1, maximal or minimal AUCs usually could be reached with less than 30 symptoms. The maximal AUCs and their best sets of sensitivities and specificities could be well approximated with the three epidemiological and interaction terms, adjusted R-squared ≥ 0.69. However, the observed overall symptom correlations, overall symptom incidence, and numbers of symptoms explained a small fraction of the AUC variances, adjusted R-squared ≤ 0.03. In conclusion, the sensitivities and specificities of single symptoms for disease diagnosis can be explained fully by the at-risk incidence and the 1 minus baseline incidence, respectively. The epidemiological measures and baseline symptom correlations can explain large fractions of the variances of the maximal AUCs and the best sets of sensitivities and specificities. These findings are important for researchers who want to assess the diagnostic accuracy of composite diagnostic criteria.

Main Groups of Microorganisms of Relevance for Food Safety and Stability

Microbiology is important to food safety, production, processing, preservation, and storage. Microbes such as bacteria, molds, and yeasts are employed for the foods production and food ingredients such as production of wine, beer, bakery, and dairy products. On the other hand, the growth and contamination of spoilage and pathogenic microorganisms is considered as one of the main causes to loss of foodstuff nowadays. Although technology, hygienic strategies, and traceability are important factors to prevent and delay microbial growth and contamination, food remains susceptible to spoilage and activity of pathogen microorganisms. Food loss by either spoilage or contaminated food affects food industry and consumers leading to economic losses and increased hospitalization costs. This chapter focuses on general aspects, characteristics, and importance of main microorganisms (bacteria, yeasts, molds, virus, and parasites) involved in food spoilage or contamination: known and recently discovered species; defects and alterations in foodstuff; most common food associated with each foodborne disease; resistance to thermal processing; occurrence in different countries; outbreaks; and associated symptoms.

What is the utility of using syndromic surveillance systems during large subnational infectious gastrointestinal disease outbreaks? An observational study using case studies from the past 5 years in England

Syndromic surveillance systems in England have demonstrated utility in the early identification of seasonal gastrointestinal illness (GI) tracking its spatio-temporal distribution and enabling early public health action. There would be additional public health utility if syndromic surveillance systems could detect or track subnational infectious disease outbreaks. To investigate using syndromic surveillance for this purpose we retrospectively identified eight large GI outbreaks between 2009 and 2014 (four randomly and four purposively sampled). We then examined syndromic surveillance information prospectively collected by the Real-time Syndromic Surveillance team within Public Health England for evidence of possible outbreak-related changes. None of the outbreaks were identified contemporaneously and no alerts were made to relevant public health teams. Retrospectively, two of the outbreaks - which happened at similar times and in proximal geographical locations - demonstrated changes in the local trends of relevant syndromic indicators and exhibited a clustering of statistical alarms, but did not warrant alerting local health protection teams. Our suite of syndromic surveillance systems may be more suited to their original purposes than as means of detecting or monitoring localized, subnational GI outbreaks. This should, however, be considered in the context of this study's limitations; further prospective work is needed to fully explore the use of syndromic surveillance for this purpose. Provided geographical coverage is sufficient, syndromic surveillance systems could be able to provide reassurance of no or minor excess healthcare systems usage during localized GI incidents.

Real-time PCR-based rapid and culture-independent detection of Salmonella in dairy milk--addressing some core issues

In this study, methodologies were developed for cost-effective, rapid and user-friendly culture-independent detection of Salmonella in milk by real-time PCR. The SYBR Green-based real-time PCR assay was standardized with primers targeting the Salmonella enterotoxin gene (stn) that have been earlier used for its detection by conventional PCR. Inclusivity tests generated the specific amplifications with a Tm corresponding to 81 ± 0·5°C. The specificity of the reaction was evaluated with a panel of 36 non-Salmonella strains. Standard curves generated, with different number of cells of this organism in milk, depicted the detection of five cells with a CT value of 37·17 (SD 0·43). To make the assays user-friendly and suitable for field applications, protocols were also established for the immobilization of the SYBR Green reaction mixes in the reaction tubes. The immobilized master mixes were stable at 25°C for 4 months and at 8°C for over 6 months. Total DNA was prepared from 150 samples of full-fat dairy milk and subjected to real-time PCR detection wherein 31 samples tested positive for Salmonella. The time of analysis was <5 h.