Listeriosis is a major public health concern associated with high hospitalization and mortality rates. The objective of this work was to summarize evidence on the associations between risk factors and sporadic cases by meta-analysing outcomes from currently published case-control studies. Suitable scientific articles were identified through systematic literature search, and subjected to a methodological quality assessment. From each study, odds-ratio (OR) measures as well as study characteristics such as population type, design, type of model and risk factor hierarchy were extracted. Mixed-effects meta-analysis models were adjusted by population type to appropriate data partitions. Twelve primary studies investigating sporadic listeriosis conducted between 1985 and 2013 passed through a quality assessment stage. These tudies provided 226 OR considered for meta-analysis. According to the meta-analysis, the main risk factor for acquiring listeriosis is suffering from an immunocompromising disease. In relation to the food exposures, this meta-analysis confirmed known risk factors such as consumption of RTE dairy, seafood and processed meat and underlined new food vehicles as fruits and vegetables, recently involved in outbreaks. There were not enough data to appraise travel, animal-contact and person-to-person as transmission pathways for listeriosis. These results will allow refining the case-control studies in the aim of improving risk factors characterisation for listeriosis in the susceptible population.

The fate of Listeria monocytogenes during ripening of artisanal Minas semi-hard cheese, as influenced by cheese intrinsic properties and by autochthonous (naturally present) or intentionally-added anti-listerial lactic acid bacteria (LAB) was modeled. Selected LAB strains with anti-listerial capacity were added or not to raw or pasteurized milk to prepare 4 cheese treatments. Counts of LAB and L. monocytogenes, pH, temperature and water activity were determined throughout cheese ripening (22 days, 22±1ᵒC). Different approaches were adopted to model the effect of LAB on L. monocytogenes: an independent approach using the Huang primary model to describe LAB growth and the linear decay model to describe pathogen inactivation; the Huang-Cardinal [pH] model using the effect of pH variation in a dynamic tertiary approach; and the Jameson-effect with Nmax tot model which simultaneously describes L. monocytogenes and LAB fate. L. monocytogenes inactivation occurred in both treatments with added LAB and inactivation was faster in raw milk cheese (−0.0260 h−1) vs. pasteurized milk cheese (−0.0182 h−1), as estimated by the linear decay model. Better goodness-of-fit was achieved for the cheeses without added LAB when the Huang primary model was used. A faster and great pH decline was detected for cheeses with added LAB, and the Huang-Cardinal [pH] model predicted higher pathogen growth rate in cheese produced with raw milk, but greater L. monocytogenes final concentration in pasteurized milk cheese. The Jameson-effect model with Nmax tot predicted that LAB suppressed pathogen growth in all treatments, except in the treatment with pasteurized milk and no LAB addition. The Huang-Cardinal [pH] model was more accurate in modeling L. monocytogenes kinetics as a function of pH changes than was the Jameson-effect model with Nmax tot as a function of LAB inhibitory effect based on the goodness-of-fit measures. The Jameson-effect model may however be a better competition model since it can more easily represent L. monocytogenes growth and death. This study presents crucial kinetic data on L. monocytogenes behavior in the presence of competing microbiota in Minas semi-hard cheese under dynamic conditions.

In order to design effective public health strategies, and, in particular, effective food safety interventions to reduce the burden of foodborne disease, the most important sources of enteric illnesses should be identified. Both case-control and cohort observational studies have for long been powerful approaches among epidemiologists to investigate the association of exposure and illness. In the literature, there are numerous case-control and cohort studies reporting results on risk factors and routes of transmission of sporadic foodborne infections. The objective of this article is to describe, in depth, the strategies implemented for systematic review and meta-analysis of the associations between multiple risk factors and eleven food and waterborne diseases, namely, non-typhoidal salmonellosis, campylobacteriosis, Shiga-toxin E. coli infection, listeriosis, yersiniosis, toxoplasmosis, norovirus infection, hepatitis A, hepatitis E, cryptosporidiosis and giardiasis. First, this article describes the procedures of systematic searches in five bibliographic engines, screening of relevance and assessment of methodological quality according to pre-set criteria. It proceeds with the explanation of a broad data categorisation scheme established to hierarchically group the risk factors into travel, host-specific factors and pathways of exposure (i.e., person-to-person, animal, environment and food routes), with views to harmonising and supporting the integration of outcomes from studies investigating a variety of potential determinants of disease. Next, the article describes the four meta-analysis models that were devised in order to calculate: (i) overall odds-ratios of acquiring the disease due to a specific risk factor by geographical region; (ii) overall odds-ratios of acquiring the disease from the different risk factors; (iii) overall risks of disease from consumption of ready-to-eat and barbecued foods; and (iv) overall effects of food handling (i.e., consuming food in raw, undercooked or unwashed state) and food preparation setting (i.e., eating food prepared outside the home) on risk of disease. The procedures for sensitivity analysis and removal of any influential and potentially-biased odds-ratio; and two methods for publication bias assessment are outlined. Finally, details are given on deviations from the standard risk categorisation scheme for specific foodborne hazards.

This study compares dynamic tertiary and competition models for L. monocytogenes growth as a function of intrinsic properties of a traditional Brazilian soft cheese and the inhibitory effect of lactic acid bacteria (LAB) during refrigerated storage. Cheeses were prepared from raw or pasteurized milk with or without the addition of selected LAB with known anti-listerial activity. Cheeses were analyzed for LAB and L. monocytogenes counts, pH and water activity (aw) throughout cold storage. Two approaches were used to describe the effect of LAB on L. monocytogenes: a Huang-Cardinal model that considers the effect of pH and aw variation in a dynamic kinetic analysis framework; and microbial competition models, including Lotka-Volterra and Jameson-effect variants, describing the simultaneous growth of L. monocytogenes and LAB. The Jameson-effect with γ and the Lotka-Volterra models produced models with statistically significant coefficients that characterized the inhibitory effect of selected LAB on L. monocytogenes in Minas fresh cheese. The Huang-Cardinal model [pH] outperformed both competition models. Taking aw change into account did not improve the fit quality of the Huang-Cardinal [pH] model. These models for Minas soft cheese should be valuable for future microbial risk assessments for this culturally important traditional cheese.

Previous research showed that meat of optimal tenderness is produced when rigor mortis temperature falls between 12-35 °C. This study aimed to classify beef carcasses quality according to the ideal window rule using pH/temperature decay descriptors and animal characteristics. Seventy-four Mirandesa breed and 52 Crossbreds, with an average age of 10.1 ± 2.32 months, were slaughtered at one abattoir located in the Northeast of Portugal. Carcass temperature and pH, logged during 24 h post-mortem, were modelled by exponential decay equations that estimated temperature (kT) and pH (kpH) decay rates. Additionally, other pH/temperature descriptors were estimated from the fitted models. From linear models adjusted to each descriptor, it was found that hot carcass weight, age, breed, gender, age class, fat cover, conformation and transport and lairage time had influence (P < 0.05) on pH and temperature decay rates. Thus, combining the variables kT and kpH, and selected animal/carcass characteristics as linear predictors, a system to classify quality of carcasses was developed.