Surveillance of antimicrobial resistance in veterinary medicine in the United States: Current efforts, challenges, and opportunities.

Antimicrobial resistance (AMR) is a global problem facing human, animal, plant, and environmental health by threatening our ability to effectively treat bacterial infections with antimicrobials. In the United States, robust surveillance efforts exist to collect, analyze, and disseminate AMR data in human health care settings. These tools enable the development of effective infection control methods, the detection of trends, and provide the evidence needed to guide stewardship efforts to reduce the potential for emergence and further spread of AMR. However, in veterinary medicine, there are currently no known equivalent tools. This paper reviews efforts in the United States related to surveillance of AMR in veterinary medicine and discusses the challenges and opportunities of using data from veterinary diagnostic laboratories to build a comprehensive AMR surveillance program that will support stewardship efforts and help control AMR in both humans and animals.

Real-time gastrointestinal infection surveillance through a cloud-based network of clinical laboratories.

Acute gastrointestinal infection (AGI) represents a significant public health concern. To control and treat AGI, it is critical to quickly and accurately identify its causes. The use of novel multiplex molecular assays for pathogen detection and identification provides a unique opportunity to improve pathogen detection, and better understand risk factors and burden associated with AGI in the community. In this study, de-identified results from BioFire® FilmArray® Gastrointestinal (GI) Panel were obtained from January 01, 2016 to October 31, 2018 through BioFire® Syndromic Trends (Trend), a cloud database. Data was analyzed to describe the occurrence of pathogens causing AGI across United States sites and the relative rankings of pathogens monitored by FoodNet, a CDC surveillance system were compared. During the period of the study, the number of tests performed increased 10-fold and overall, 42.6% were positive for one or more pathogens. Seventy percent of the detections were bacteria, 25% viruses, and 4% parasites. Clostridium difficile, enteropathogenic Escherichia coli (EPEC) and norovirus were the most frequently detected pathogens. Seasonality was observed for several pathogens including astrovirus, rotavirus, and norovirus, EPEC, and Campylobacter. The co-detection rate was 10.2%. Enterotoxigenic E. coli (ETEC), Plesiomonas shigelloides, enteroaggregative E. coli (EAEC), and Entamoeba histolytica were detected with another pathogen over 60% of the time, while less than 30% of C. difficile and Cyclospora cayetanensis were detected with another pathogen. Positive correlations among co-detections were found between Shigella/Enteroinvasive E. coli with E. histolytica, and ETEC with EAEC. Overall, the relative ranking of detections for the eight GI pathogens monitored by FoodNet and BioFire Trend were similar for five of them. AGI data from BioFire Trend is available in near real-time and represents a rich data source for the study of disease burden and GI pathogen circulation in the community, especially for those pathogens not often targeted by surveillance.

The Public Health Impact of Implementing a Concentration-Based Microbiological Criterion for Controlling Salmonella in Ground Turkey.

Despite initiatives to improve the safety of poultry products in the United States, progress has stalled, and salmonellosis incidence is still above Healthy People 2020's goal. One strategy to manage Salmonella and verify process control in poultry establishments is to implement microbiological criteria (MC) linked to public health outcomes. Concentration-based MC have been used by the food industry; however, the public health impact of such approaches is only starting to be assessed. This study evaluated the public health impact of a concentration-based MC for Salmonella in raw ground turkey consumed in the United States using a quantitative risk assessment modeling approach. The distribution of Salmonella concentration in ground turkey was derived from USDA-FSIS monitoring surveys. Other variables and parameters were derived from public databases, literature, and expert opinion. Based on considered concentrations, implementing a MC of 1 cell/g led to an estimated 46.1% reduction (preventable fraction, PF) in the mean probability of illness when consumer cooking and cross-contamination were included. The PF was consistent across scenarios including or excluding cross-contamination and cooking, with slightly lower mean PF when cross-contamination was included. The proportion of lots not compliant with the 1 cell/g MC was 1.05% in the main scenarios and increased nonlinearly when higher Salmonella concentrations were assumed. Assumptions on concentration variability across lots and within lots had a large impact, highlighting the benefit of reducing this uncertainty. These approach and results can help inform the development of MC to monitor and control Salmonella in ground turkey products.

Food-specific attribution of selected gastrointestinal illnesses: estimates from a Canadian expert elicitation survey.

The study used a structured expert elicitation survey to derive estimates of food-specific attribution for nine illnesses caused by enteric pathogens in Canada. It was based on a similar survey conducted in the United States and focused on Campylobacter spp., Escherichia coli O157:H7, Listeria monocytogenes, nontyphoidal Salmonella enterica, Shigella spp., Vibrio spp., Yersinia enterocolitica, Cryptosporidium parvum, and Norwalk-like virus. A snowball approach was used to identify food safety experts within Canada. Survey respondents provided background information as well as self-assessments of their expertise for each pathogen and the 12 food categories. Depending on the pathogen, food source attribution estimates were based on responses from between 10 and 35 experts. For each pathogen, experts divided their estimates of total foodborne illness across 12 food categories and they provided a best estimate for each category as well as 5th and 95th percentile limits for foods considered to be vehicles. Their responses were treated as triangular probability distributions, and linear aggregation was used to combine the opinions of each group of experts for each pathogen-food source group. Across the 108 pathogen-food groups, a majority of experts agreed on 30 sources and 48 nonsources for illness. The number of food groups considered to be pathogen sources by a majority of experts varied by pathogen from a low of one food source for Vibrio spp. (seafood) and C. parvum (produce) to a high of seven food sources for Salmonella spp. Beta distributions were fitted to the aggregated opinions and were reasonable representations for most of the pathogen-food group attributions. These results will be used to quantitatively assess the burden of foodborne illness in Canada as well as to analyze the uncertainty in our estimates.

Foodborne proportion of gastrointestinal illness: estimates from a Canadian expert elicitation survey.

The study used a structured expert elicitation survey to derive estimates of the foodborne attributable proportion for nine illnesses caused by enteric pathogens in Canada. It was based on a similar study conducted in the United States and focused on Campylobacter, Escherichia coli O157:H7, Listeria monocytogenes, nontyphoidal Salmonella enterica, Shigella spp., Vibrio spp., Yersinia enterocolitica, Cryptosporidium parvum, and Norwalk-like virus. For each pathogen, experts were asked to provide their best estimate and low and high limits for the proportion of foodborne illness relative to total cases. In addition, they provided background information with regard to food safety experience, including self-evaluated expertise for each pathogen on a 5-point scale. A snowball approach was used to identify 152 experts within Canada. The experts' background details were summarized using descriptive statistics. Factor analysis was used to determine whether the variability in best estimates was related to self-assessed level of expertise or other background information. Cluster analysis followed by beta function fitting was undertaken on best estimates from experts who self-evaluated their expertise 3 or higher. In parallel, Monte Carlo resampling was run using triangular distributions based on each expert's best estimate and its limits. Sixty-six experts encompassing various academic backgrounds, fields of expertise, and experiences relevant to food safety provided usable data. Considerable variation between experts in their estimated foodborne attributable proportions was observed over all diseases, without any relationship to the expert's background. Uncertainty about their estimate (measured by the low and high limits) varied between experts and between pathogens as well. Both cluster analysis and Monte Carlo resampling clearly indicated disagreement between experts for Campylobacter, E. coli O157, L. monocytogenes, Salmonella, Vibrio, and Y. enterocolitica. In the absence of more reliable estimates, the observed discrepancy between experts must be explored and understood before one can judge which opinion is the best.

Isolation of Mycobacterium avium subsp. paratuberculosis from waste milk delivered to California calf ranches.

The objective of this study was to determine if viable Mycobacterium avium subsp. paratuberculosis (MAP) was present in waste milk delivered and fed to calves on California calf ranches. Four calf-raising facilities in the Central Valley of California that fed pasteurized waste milk to calves were enrolled. Pre- and post-pasteurization waste milk samples were cultured for MAP using liquid and solid media over a 5-day period during each of four seasons. Aerobic cultures were performed simultaneously to enumerate total bacteria count and evaluate the efficiency of pasteurization which was estimated by the log-reduction of the total number of bacteria. Viable MAP was cultured from 2% of the waste milk samples. Of the three culture-positive samples, two were from pre-pasteurized and one was from post-pasteurized milk samples. The mean total bacterial count for pre- and post-pasteurized waste milk varied from 1.8 x 10(8) to 5.5 x 10(8) colony-forming units (CFU)/mL and 4.9 x 10(5) to 1.1 x 10(8) CFU/mL, respectively, and on average ranches 1, 2, 3, and 4 had, respectively, 3.5-, 3-, 4.7-, and 2.6-log reduction in the number of total bacteria in their waste milk. This is the first study to document results from on-farm pasteurization under field conditions and it indicates the lack of uniformity and adequate controls of the process which could allow the survival of MAP and other pathogens. Calf-raising facilities could benefit from the implementation of standard operating procedures and farm worker training for pasteurization of waste milk. Dairy herds should be aware that placing calves in specialized off-site calf-raising facilities might not eliminate all possible routes of infection of calves with MAP.

Detection of Mycobacterium avium subsp. paratuberculosis in bovine manure using Whatman FTA card technology and Lightcycler real-time PCR.

A modified forensic DNA extraction and real-time fluorescent polymerase chain reaction assay has been evaluated for the detection of Mycobacterium avium subsp. paratuberculosis (MAP) in bovine fecal samples using primers and fluorescent resonance energy transfer (FRET) probes targeting the IS900 gene sequence of MAP. DNA was successfully extracted from manure samples by utilizing the Whatman FTA card technology, which allows for simple processing and storage of samples at room temperature. The FTA cards were washed and subjected to a Chelex-100 incubation to remove any remaining polymerase chain reaction (PCR) inhibitors and to elute the DNA from the FTA card. This isolated DNA was then subjected to direct real time fluorescent PCR analysis. Detection of MAP DNA from bovine fecal samples spiked with known concentrations of viable MAP cells was obtained. The detection limits of the assay was consistently found to be between 10(2) and 10(4) colony forming units [CFU]/g, with some samples containing as low as 10 CFU/g, yielding positive assay results. This cost-efficient assay allows reporting of results as early as 4 h after fecal collection, which can be particularly useful in highthroughput herd screening.

Modified culture protocol for isolation of Mycobacterium avium subsp. paratuberculosis from raw milk.

A modified culture method using C18-carboxypropylbetaine (CB-18) and microscopic screening was evaluated for time to and limit of detection of Mycobacterium avium subsp. paratuberculosis (MAP) in raw milk. Bulk-tank milk samples were spiked with six different concentrations (10(1) to 10(6) CFU/mL) of MAP. Samples were processed using two different protocols. The first protocol involved specimen processing with the zwitterionic detergent C18-carboxypropylbetaine (CB-18) and lytic enzymes followed by culture on modified Middlebrook 7H10 agar plates with microscopic screening. The second protocol used 0.75% hexadecylpyridinium chloride (HPC) for specimen processing, followed by culture on Herrold's egg yolk medium (HEYM). Both protocols were repeated eight independent times, and the detection limit and time to detection were compared. The presence of MAP in spiked milk samples was detected between 14 and 45 days (N [number of samples], 46; mean, 22.7; median, 19.5) using the CB-18 and microscopic screening method, and between 21 and 63 days (N, 47; mean, 31; median, 28) using HEYM (P < 0.001). Time to detection also varied with MAP concentration (P < 0.001). Higher concentrations of MAP were detected earlier than lower concentrations and this finding was independent of the method used (P = 0.479). The two methods had similar detection limits but the modified culture method reduced the time to detect MAP in raw milk for the majority of concentrations.