Research gaps and priorities for quantitative microbial risk assessment (QMRA).

The coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose-response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co-exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source-to-outcome continuum. Cross-cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.

LANCE: a Label-Free Live Apoptotic and Necrotic Cell Explorer Using Convolutional Neural Network Image Analysis.

Identifying and quantifying cell death is the basis for all cell death research. Current methods for obtaining these quantitative measurements rely on established biomarkers, yet the marker-based approach suffers from limited marker specificity, high cost of reagents, lengthy sample preparation, and fluorescence imaging. Based on the morphological difference, we developed a Live, Apoptotic, and Necrotic Cell Explorer (LANCE) to categorize cell death status in a label-free manner, by incorporating machine learning and image processing. The LANCE workflow includes cropping individual cells from microscopic images having hundreds of cells, formation of an image database of around 5000 events, training and validation of the convolutional neural network models using multiple cell lines, and treatment conditions. With LANCE, we precisely categorized live, apoptotic, and necrotic cells with a high accuracy of 96.3 ± 0.5%. More importantly, the nondestructive label-free LANCE method allows for tracking time dynamics of the cell death process, which enhances the understanding of subtle cell death regulation at the molecular level. Hence, LANCE is a fast, low-cost, and nondestructive label-free method to distinguish cell status, which can be applied to cell death studies as well as many other biomedical applications.

FDA-iRISK--a comparative risk assessment system for evaluating and ranking food-hazard pairs: case studies on microbial hazards.

Stakeholders in the system of food safety, in particular federal agencies, need evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions. FDA-iRISK (referred to here as iRISK), a Web-based quantitative risk assessment system, was developed to meet this need. The modeling tool enables users to assess, compare, and rank the risks posed by multiple food-hazard pairs at all stages of the food supply system, from primary production, through manufacturing and processing, to retail distribution and, ultimately, to the consumer. Using standard data entry templates, built-in mathematical functions, and Monte Carlo simulation techniques, iRISK integrates data and assumptions from seven components: the food, the hazard, the population of consumers, process models describing the introduction and fate of the hazard up to the point of consumption, consumption patterns, dose-response curves, and health effects. Beyond risk ranking, iRISK enables users to estimate and compare the impact of interventions and control measures on public health risk. iRISK provides estimates of the impact of proposed interventions in various ways, including changes in the mean risk of illness and burden of disease metrics, such as losses in disability-adjusted life years. Case studies for Listeria monocytogenes and Salmonella were developed to demonstrate the application of iRISK for the estimation of risks and the impact of interventions for microbial hazards. iRISK was made available to the public at http://irisk.foodrisk.org in October 2012.

Application of Bayesian techniques to model the burden of human salmonellosis attributable to U.S. food commodities at the point of processing: adaptation of a Danish model.

Mathematical models that estimate the proportion of foodborne illnesses attributable to food commodities at specific points in the food chain may be useful to risk managers and policy makers to formulate public health goals, prioritize interventions, and document the effectiveness of mitigations aimed at reducing illness. Using human surveillance data on laboratory-confirmed Salmonella infections from the Centers for Disease Control and Prevention and Salmonella testing data from U.S. Department of Agriculture Food Safety and Inspection Service's regulatory programs, we developed a point-of-processing foodborne illness attribution model by adapting the Hald Salmonella Bayesian source attribution model. Key model outputs include estimates of the relative proportions of domestically acquired sporadic human Salmonella infections resulting from contamination of raw meat, poultry, and egg products processed in the United States from 1998 through 2003. The current model estimates the relative contribution of chicken (48%), ground beef (28%), turkey (17%), egg products (6%), intact beef (1%), and pork (<1%) across 109 Salmonella serotypes found in food commodities at point of processing. While interpretation of the attribution estimates is constrained by data inputs, the adapted model shows promise and may serve as a basis for a common approach to attribution of human salmonellosis and food safety decision-making in more than one country.

Estimating removal rates of bacteria from poultry carcasses using two whole-carcass rinse volumes.

Rinse sampling is a common method for determining the level of microbial contamination on poultry carcasses. One of the advantages of rinse sampling, over other carcass sampling methods, is that the results can be used for both process control applications and to estimate the total microbial level on a carcass. The latter objective is possible because rinse sampling removes a portion of the bacteria from the entire carcass, whereas methods such as neck-skin sampling focus on a small area of the carcass where the level of contamination may not be representative of the entire carcass. Two recurring issues with rinse sampling are differences in sampling protocols and the difficulty of determining the proportion of bacteria removed during sampling. A situation arose where 300 rinse samples were collected using two different rinse fluid volumes (i.e., 100 and 400 ml). The original intent of the study was to demonstrate the similarity of the removal rates for the two methods, but summary statistics suggested substantial differences. A Bayesian model was constructed to estimate the removal rates for the two sampling methods as well as to estimate the parameters of distributions describing the carcass-level contamination across 3 days of processing. The results of the study suggest that approximately 11 times as many bacteria are removed from the carcass when using a 400 ml rinse sample than with a 100 ml rinse sample. While this estimate is subject to a rather large degree of uncertainty, the 95% Bayesian credible interval for the ratio of the two removal rate parameters of (7.5, and 17.0) still indicates a significant difference in the removal rates for the two sampling methods.

Modeling the public health system response to a terrorist event in the food supply.

We have developed a simulation model to quantify and characterize the response of the public health system and the impact of public health advisories in the event of an intentional contamination of the food supply. The model has three components: (1) definition of individual exposure over time and the outcomes of exposure, (2) definition of the geographical dispersal of exposures, and (3) response of the public health authorities to symptomatic individuals. The model explicitly considers the variation in the multiple interrelated facets of the response system, including differences among individuals' responses to exposure, variation between health care providers, and the subsequent processing of samples and confirmation of cases. To illustrate use of the model, case studies with Escherichia coli O157:H7 and Salmonella spp. in three categories of food vehicle were compared. The level of detail required to run the public health component of the model is not trivial. While some data may not be available for hazards of particular interest in potential bioterrorism events, the application of expert judgment permits comparisons between different agents, different system reactions, and other assumptions within the system. The model provides the capacity to study the impact of system changes, to compare scenarios and to quantify the benefits of improvement in terms of averted exposures and risk reduction, and constitutes a significant aid to understanding and managing these threats. Essentially, the model provides an explicit valuation of time saved in the identification and intervention in terrorist events in the food supply.

Economics of reducing Campylobacter at different levels within the Belgian poultry meat chain.

Campylobacter infections pose a serious public health problem in Belgium. Poultry meat is most likely responsible for 40% of human campylobacteriosis cases in Belgium. On a yearly basis, consumption of poultry meat causes at least 22,000 campylobacteriosis cases, with a cost of illness of Euro 10.9 million. Several intervention measures have been proposed in literature, aiming to reduce the contamination of poultry meat and thus lead to significant reductions of human campylobacteriosis cases. This study aimed to evaluate the cost-benefit ratio, i.e., the ratio of reduced costs of illness on intervention costs of various intervention measures. These measures were selected by representatives from the poultry meat sector and experts in the field of poultry science. The selection comprised measures at the farm level (phage therapy), at the processing plant (spraying of carcasses with lactic acid or electrolyzed oxidizing water, crust freezing, or irradiation), and at the consumer level (improving kitchen hygiene and application of home freezing). Among these measures, the decontamination of carcasses with electrolyzed oxidizing water applied in the processing plant was the most efficient (17.66), followed by the use of lactic acid (4.06). In addition, phage therapy generated a positive cost-benefit ratio (2.54). Irradiation indicated the highest efficacy, but its cost-benefit ratio was rather low (0.31). There seems to be less gain by trying to improve food handling in the kitchen. The cost to reach consumers is large, while only a very limited fraction of the consumers is willing to change its behavior. The outcome of this study poses valuable information for future risk-management decisions in Belgium.

A quantitative assessment of the risks from illegally imported meat contaminated with foot and mouth disease virus to Great Britain.

Foot and mouth disease (FMD) is considered by many as the most important animal disease in the world. FMD is highly contagious and outbreaks incur significant costs as affected countries are severely limited in their ability to trade. A number of trade commodities may be contaminated with FMD virus (FMDV) including animal products, for example, meat. As a member of the European Union, Great Britain (GB) has put in place a number of regulations to prevent the importation of pathogens in imported meat products. However, the illegal importation of meat provides a route by which safety controls may be circumvented and meat from FMD affected areas may be imported. This study assesses the FMD infection risk posed to the livestock population of GB from the illegal importation of meat, and estimates the major contributors to this overall risk, through the development of a quantitative risk assessment model. From model results, the total amount of illegal meat entering GB each year is estimated on average to be 11,875 tonnes. with 90% certainty that this is between 4,398 and 28,626 tonnes per year; of which between 64.5 and 565 kg are contaminated with FMDV. This flow of illegal meat results in an estimate of a frequency of FMD infection in GB livestock of 0.015 cases of infected animals per year, with 90% certainty it is between 0.0017 and 0.053. Imports from the region Near and Middle East account for 47% of this risk, and 68% of the risk is attributed to bone-in and dried de-boned products.