W B McNab

Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada

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Publications (43)86.25 Total impact

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    ABSTRACT: Sentinel surveillance has previously been used to monitor and identify disease outbreaks in both human and animal contexts. Three approaches for the selection of sentinel sites are proposed and evaluated regarding their ability to capture overall respiratory disease trends using provincial abattoir condemnation data from all abattoirs open throughout the study for use in a sentinel syndromic surveillance system. All three sentinel selection criteria approaches resulted in the identification of sentinel abattoirs that captured overall temporal trends in condemnation rates similar to those reported by the full set of abattoirs. However, all selection approaches tended to overestimate the condemnation rates of the full dataset by 1.4 to as high as 3.8 times for cows, heifers and steers. Given the results, the selection approach using abattoirs open all weeks had the closest approximation of temporal trends when compared to the full set of abattoirs. Sentinel abattoirs show promise for integration into a food animal syndromic surveillance system using Ontario provincial abattoir condemnation data. While all selection approaches tended to overestimate the condemnation rates of the full dataset to some degree, the abattoirs open all weeks selection approach appeared to best capture the overall seasonal and temporal trends of the full dataset and would be the most suitable approach for sentinel abattoir selection.
    BMC Veterinary Research 12/2015; 11(1). DOI:10.1186/s12917-015-0349-1 · 1.74 Impact Factor
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    ABSTRACT: Simulation models implemented using a range of parameters offer a useful approach to identifying effective disease intervention strategies. The objective of this study was to investigate the effects of key control strategies to mitigate the simultaneous spread of influenza among and between swine and human populations. We used the pandemic H1N1 2009 virus as a case study. The study population included swine herds (488 herds) and households-of-people (29 707 households) within a county in Ontario, Canada. Households were categorized as: (i) rural households with swine workers, (ii) rural households without swine workers and (iii) urban households without swine workers. Seventy-two scenarios were investigated based on a combination of the parameters of speed of detection and control strategies, such as quarantine strategy, effectiveness of movement restriction and ring vaccination strategy, all assessed at three levels of transmissibility of the virus at the swine–human interface. Results showed that the speed of detection of the infected units combined with the quarantine strategy had the largest impact on the duration and size of outbreaks. A combination of fast to moderate speed of the detection (where infected units were detected within 5–10 days since first infection) and quarantine of the detected units alone contained the outbreak within the swine population in most of the simulated outbreaks. Ring vaccination had no added beneficial effect. In conclusion, our study suggests that the early detection (and therefore effective surveillance) and effective quarantine had the largest impact in the control of the influenza spread, consistent with earlier studies. To our knowledge, no study had previously assessed the impact of the combination of different intervention strategies involving the simultaneous spread of influenza between swine and human populations.
    Transboundary and Emerging Diseases 09/2014; DOI:10.1111/tbed.12260 · 3.12 Impact Factor
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    ABSTRACT: The circulation of zoonotic influenza A viruses including pH1N1 2009 and H5N1 continue to present a constant threat to animal and human populations. Recently, an H3N2 variant spread from pigs to humans and between humans in limited numbers. Accordingly, this research investigated a range of scenarios of the transmission dynamics of pH1N1 2009 virus at the swine–human interface while accounting for different percentages of swine workers initially immune. Furthermore, the feasibility of using NAADSM (North American Animal Disease Spread Model) applied as a one-health simulation model was assessed. The study population included 488 swine herds and 29, 707 households of people within a county in Ontario, Canada. Households were categorized as follows: (i) rural households with swine workers, (ii) rural households without swine workers, and (iii) urban households without swine workers. Forty-eight scenarios were investigated, based on the combination of six scenarios around the transmissibility of the virus at the interface and four vaccination coverage levels of swine workers (0–60%), all under two settings of either swine or human origin of the virus. Outcomes were assessed in terms of stochastic ‘die-out’ fraction, size and time to peak epidemic day, overall size and duration of the outbreaks. The modelled outcomes indicated that minimizing influenza transmissibility at the interface and targeted vaccination of swine workers had significant beneficial effects. Our results indicate that NAADSM can be used as a framework to model the spread and control of contagious zoonotic diseases among animal and human populations, under certain simplifying assumptions. Further evaluation of the model is required. In addition to these specific findings, this study serves as a benchmark that can provide useful input to a future one-health influenza modelling studies. Some pertinent information gaps were also identified. Enhanced surveillance and the collection of high-quality information for more accurate parameterization of such models are encouraged.
    Transboundary and Emerging Diseases 03/2014; DOI:10.1111/tbed.12215 · 3.12 Impact Factor
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    ABSTRACT: SYNDROMIC SURVEILLANCE RESEARCH HAS FOCUSED ON TWO MAIN THEMES: the search for data sources that can provide early disease detection; and the development of efficient algorithms that can detect potential outbreak signals. This work combines three algorithms that have demonstrated solid performance in detecting simulated outbreak signals of varying shapes in time series of laboratory submissions counts. These are: the Shewhart control charts designed to detect sudden spikes in counts; the EWMA control charts developed to detect slow increasing outbreaks; and the Holt-Winters exponential smoothing, which can explicitly account for temporal effects in the data stream monitored. A scoring system to detect and report alarms using these algorithms in a complementary way is proposed. The use of multiple algorithms in parallel resulted in increased system sensitivity. Specificity was decreased in simulated data, but the number of false alarms per year when the approach was applied to real data was considered manageable (between 1 and 3 per year for each of ten syndromic groups monitored). The automated implementation of this approach, including a method for on-line filtering of potential outbreak signals is described. The developed system provides high sensitivity for detection of potential outbreak signals while also providing robustness and flexibility in establishing what signals constitute an alarm. This flexibility allows an analyst to customize the system for different syndromes.
    PLoS ONE 12/2013; 8(12):e82183. DOI:10.1371/journal.pone.0082183 · 3.53 Impact Factor
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    ABSTRACT: Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada.
    Preventive Veterinary Medicine 07/2013; 112(1-2). DOI:10.1016/j.prevetmed.2013.06.008 · 2.51 Impact Factor
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    ABSTRACT: Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.
    Journal of The Royal Society Interface 03/2013; 10(83):20130114. DOI:10.1098/rsif.2013.0114 · 3.86 Impact Factor
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    ABSTRACT: Background Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users. Methods This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory. Results High performance (F1-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F1-macro), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F1-micro score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F1-micro = 0.994 and F1-macro = .955), however the classification process is not transparent to the domain experts.
    PLoS ONE 03/2013; 8(3):57334. DOI:10.1371/journal.pone.0057334 · 3.53 Impact Factor
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    ABSTRACT: The practice of disease surveillance has shifted in the last two decades towards the introduction of systems capable of early detection of disease. Modern biosurveillance systems explore different sources of pre-diagnostic data, such as patient's chief complaint upon emergency visit or laboratory test orders. These sources of data can provide more rapid detection than traditional surveillance based on case confirmation, but are less specific, and therefore their use poses challenges related to the presence of background noise and unlabelled temporal aberrations in historical data. The overall goal of this study was to carry out retrospective analysis using three years of laboratory test submissions to the Animal Health Laboratory in the province of Ontario, Canada, in order to prepare the data for use in syndromic surveillance. Daily cases were grouped into syndromes and counts for each syndrome were monitored on a daily basis when medians were higher than one case per day, and weekly otherwise. Poisson regression accounting for day-of-week and month was able to capture the day-of-week effect with minimal influence from temporal aberrations. Applying Poisson regression in an iterative manner, that removed data points above the predicted 95th percentile of daily counts, allowed for the removal of these aberrations in the absence of labelled outbreaks, while maintaining the day-of-week effect that was present in the original data. This resulted in the construction of time series that represent the baseline patterns over the past three years, free of temporal aberrations. The final method was thus able to remove temporal aberrations while keeping the original explainable effects in the data, did not need a training period free of aberrations, had minimal adjustment to the aberrations present in the raw data, and did not require labelled outbreaks. Moreover, it was readily applicable to the weekly data by substituting Poisson regression with moving 95th percentiles.
    Preventive Veterinary Medicine 11/2012; 109(3-4). DOI:10.1016/j.prevetmed.2012.10.010 · 2.51 Impact Factor
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    ABSTRACT: Background Abattoir condemnations may play an important role in a food animal syndromic surveillance system. Portion condemnation data may be particularly useful, as these data can provide more specific information on health outcomes than whole carcass condemnation data. Various seasonal, secular, disease, and non-disease factors have been previously identified to be associated with whole carcass condemnation rates in Ontario provincial abattoirs; and if ignored, may bias the results of quantitative disease surveillance methods. The objective of this study was to identify various seasonal, secular, and abattoir characteristic factors that may be associated with bovine portion condemnation rates and compare how these variables may differ from previously identified factors associated with bovine whole carcass condemnation rates. Results Data were collected from the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) and the Ontario Cattlemen’s Association regarding “parasitic liver” and pneumonic lung condemnation rates for different cattle classes, abattoir compliance ratings, and the monthly sales-yard price for commodity classes from 2001-2007. To control for clustering by abattoirs, multi-level Poisson modeling was used to investigate the association between the following variables and “parasitic liver” as well as pneumonic lung condemnation rates: year, season, annual abattoir audit rating, geographic region, annual abattoir operating time, annual total number of animals processed, animal class, and commodity sales price. Conclusions In this study, “parasitic liver” condemnation rates were associated with year, season, animal class, audit rating, and region. Pneumonic lung condemnation rates were associated with year, season, animal class, region, audit rating, number of cattle processed per year, and number of weeks abattoirs processed cattle. Unlike previous models based on whole carcass condemnations, commodity price was not associated with partial condemnations in this study. The results identified material-specific predictor variables for condemnation rates. This is important for syndromic surveillance based on abattoir data and should be modeled and controlled for during quantitative surveillance analysis on a portion specific basis.
    BMC Veterinary Research 06/2012; 8(1):88. DOI:10.1186/1746-6148-8-88 · 1.74 Impact Factor
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    ABSTRACT: Practicing veterinarians play an important role in detecting the initial outbreak of disease in animal populations. A pilot study was conducted to determine the feasibility of a veterinary-based surveillance system for the Ontario swine industry. A total of 7 practitioners from 5 clinics agreed to submit information from July 1, 2007 to June 30, 2008. The surveillance program was evaluated in terms of timeliness, compliance, geographic coverage, and data quality. Our study showed that the veterinary-based surveillance system was acceptable to practitioners and produced useful data. The program obtained information from 25% of pig farms in Ontario during this time period. However, better communication with practitioners, more user-friendly recording systems that can be adapted to each clinic's management system, active involvement of the clinics' technical personnel, and the use of financial incentives may help to improve compliance and timeliness.
    Canadian journal of veterinary research = Revue canadienne de recherche vétérinaire 10/2010; 74(4):241-51. · 0.85 Impact Factor
  • Annals of Epidemiology 09/2010; 20(9):715-715. DOI:10.1016/j.annepidem.2010.07.070 · 2.15 Impact Factor
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    ABSTRACT: Ontario provincial abattoirs have the potential to be important sources of syndromic surveillance data for emerging diseases of concern to animal health, public health and food safety. The objectives of this study were to: (1) describe provincially inspected abattoirs processing cattle in Ontario in terms of the number of abattoirs, the number of weeks abattoirs process cattle, geographical distribution, types of whole carcass condemnations reported, and the distance animals are shipped for slaughter; and (2) identify various seasonal, secular, disease and non-disease factors that might bias the results of quantitative methods, such as cluster detection methods, used for food animal syndromic surveillance. Data were collected from the Ontario Ministry of Agriculture, Food and Rural Affairs and the Ontario Cattlemen's Association regarding whole carcass condemnation rates for cattle animal classes, abattoir compliance ratings, and the monthly sales-yard price for various cattle classes from 2001-2007. To analyze the association between condemnation rates and potential explanatory variables including abattoir characteristics, season, year and commodity price, as well as animal class, negative binomial regression models were fit using generalized estimating equations (GEE) to account for autocorrelation among observations from the same abattoir. Results of the fitted model found animal class, year, season, price, and audit rating are associated with condemnation rates in Ontario abattoirs. In addition, a subset of data was used to estimate the average distance cattle are shipped to Ontario provincial abattoirs. The median distance from the farm to the abattoir was approximately 82 km, and 75% of cattle were shipped less than 100 km. The results suggest that secular and seasonal trends, as well as some non-disease factors will need to be corrected for when applying quantitative methods for syndromic surveillance involving these data. This study also demonstrated that animals shipped to Ontario provincial abattoirs come from relatively local farms, which is important when considering the use of spatial surveillance methods for these data.
    BMC Veterinary Research 08/2010; 6(1):42. DOI:10.1186/1746-6148-6-42 · 1.74 Impact Factor
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    ABSTRACT: The epidemiology of influenza in the North American swine population has changed since the emergence of a triple-reassortant H3N2 influenza virus. Although seen previously in North America, the Ontario swine population had likely been free of viruses of the reassortant H3N2 lineage until 2005. The objective of this study was to investigate the frequency and distribution of exposure to H1N1 and H3N2 subtypes in the Ontario finisher pig population prior to and after the H3N2 outbreak that occurred in 2005. This included investigating prevalence and spatial distribution of positive herds, assessing proportion of random variation at different hierarchical levels, and evaluating selected demographic factors and management procedures as potential risk factors. In total, 919 and 978 sera collected in cross-sectional studies from 46 and 49 finisher herds in 2004 and 2005 were tested by a H1N1 subtype-specific and a H3N2 subtype-specific commercial ELISA. For the H1N1 subtype, the point prevalence of positive herds (>3 reactors) was 19.5% and 30.6% in 2004 and 2005, respectively. For the H3N2 subtype the point prevalence of positive herds (>3 reactors) was 6.5% and 40.8% in 2004 and 2005, respectively. Sera from 2004 that were positive on H3N2 ELISA did not cross-react with any of the H3N2 variants used as antigen on a sequential HI test. Only herds positive for H3N2 subtype in 2005 clustered in space (P<0.01). The H1N1 status in 2005 was associated with the H1N1 status in 2004, and with reported distance to the nearest herd. The H3N2 status in 2005 was associated with reported distance to the nearest herd and a type of replacement gilt source. For H3N2, distance seemed to be important even after controlling for type of gilt source. Most variability in seropositivity was between herds with little variability between pens. This study confirms that in 2005, the epidemic H3N2 subtype co-circulated with endemic H1N1 subtype in the Ontario finisher herds. We concluded that in Ontario, the endemic H1N1 subtype was likely maintained through circulation within herds and sites with common flow. Whereas the transmission of epidemic H3N2 subtype was attributed to local spread, which could include different modes of direct, indirect, and airborne transmission. We emphasize the importance of establishing routine monitoring systems that would allow using molecular tools, and maintaining serum banks as a useful resource for retrospective comparisons.
    Preventive Veterinary Medicine 01/2008; 83(1):24-40. DOI:10.1016/j.prevetmed.2007.05.025 · 2.51 Impact Factor
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    ABSTRACT: The North American Animal Disease Spread Model is a stochastic, spatial, state-transition simulation model for the spread of highly contagious diseases of animals. It was developed with broad international support to assist policy development and decision making involving disease incursions. User-established parameters define model behavior in terms of disease progression; disease spread by animal-to-animal contact, contact with contaminated personnel or equipment, and airborne dissemination; and the implementation of control measures such as destruction and vaccination. Resources available to implement disease control strategies, as well as the direct costs associated with these strategies, are taken into consideration. The model records a wide variety of measures of the extent of simulated outbreaks and other characteristics. The graphical interface and output visualization features also make it a useful tool for training and preparedness exercises. This model is now being used to evaluate outbreak scenarios and potential control strategies for several economically important exotic animal diseases in the United States, Canada, and elsewhere. NAADSM is freely available via the Internet at http://www.naadsm.org.
    Preventive Veterinary Medicine 01/2008; 82(3-4):176-97. DOI:10.1016/j.prevetmed.2007.05.019 · 2.51 Impact Factor
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    ABSTRACT: This study estimated the health burden and costs associated with gastroenteritis in the City of Hamilton (Ontario, Canada). The number of cases, number of different resource units used, and cost per resource unit were represented by probability distributions and point estimates. These were subsequently integrated in a stochastic model to estimate the overall burden and cost in the population and to depict the uncertainty of the estimates. The estimated mean annual cost per capita was Can dollar 115. The estimated mean annual cost per case was Can dollar 1,089 and was similar to other published figures. Gastroenteritis represented a significant burden in the study population, with costs high enough to justify prevention efforts. These results, currently the most accurate available estimates for a Canadian population, can inform future economic evaluations to determine the most cost effective measures for reducing the burden and cost of gastroenteritis in the community.
    Journal of food protection 04/2006; 69(3):651-9. · 1.80 Impact Factor
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    ABSTRACT: In Ontario, infectious gastrointestinal illness (IGI) reporting can be represented by a linear model of several sequential steps required for a case to be captured in the provincial reportable disease surveillance system. Since reportable enteric data are known to represent only a small fraction of the total IGI in the community, the objective of this study was to estimate the under-reporting rate for IGI in Ontario. A distribution of plausible values for the under-reporting rate was estimated by specifying input distributions for the proportions reported at each step in the reporting chain, and multiplying these distributions together using simulation methods. Input distributions (type of distribution and parameters) for the proportion of cases reported at each step of the reporting chain were determined using data from the Public Health Agency of Canada's National Studies on Acute Gastrointestinal Illness (NSAGI) initiative. For each case of enteric illness reported to the province of Ontario, the estimated number of cases of IGI in the community ranged from 105 to 1,389, with a median of 285, and a mean and standard deviation of 313 and 128, respectively. Each case of enteric illness reported to the province of Ontario represents an estimated several hundred cases of IGI in the community. Thus, reportable disease data should be used with caution when estimating the burden of such illness. Program planners and public health personnel may want to consider this fact when developing population-based interventions.
    Canadian journal of public health. Revue canadienne de santé publique 12/2004; 96(3):178-81. · 1.02 Impact Factor
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    ABSTRACT: To estimate the magnitude and distribution of self-reported, acute gastrointestinal illness in a Canadian-based population, we conducted a retrospective, cross-sectional telephone survey of approximately 3500 randomly selected residents of the city of Hamilton (Ontario, Canada) from February 2001 to February 2002. The observed monthly prevalence was 10% (95 % CI 9.94-10.14) and the incidence rate was 1.3 (95 % CI 1.1-1.4) episodes per person-year; this is within the range of estimates from other developed countries. The prevalence was higher in females and in those aged < 10 years and 20-24 years. Overall, prevalence peaked in April and October, but a different temporal distribution was observed for those aged < 10 years. Although these data were derived from one community, they demonstrate that the epidemiology of acute gastrointestinal illness in a Canadian-based population is similar to that reported for other developed countries.
    Epidemiology and Infection 09/2004; 132(4):607-17. DOI:10.1017/S0950268804002353 · 2.49 Impact Factor
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    ABSTRACT: The Reveal (Neogen Corp., Lansing, Mich.) and SafePath (SafePath Laboratories LLC, St. Paul, Minn.) tests were evaluated for their performance as beef fecal and beef carcass Escherichia coli O157:H7 monitoring tests. Agreement between these tests and a reference test system was determined using naturally contaminated bovine feces and beef carcasses. The reference system utilized immunomagnetic separation with plating onto cefixime, tellurite, sorbitol MacConkey agar, followed by colony testing using a serum agglutination test for the O157 antigen. Relative to this reference method, the Reveal test showed a sensitivity of 46% and a specificity of 82% on bovine feces and a specificity of 99% on carcass samples. The SafePath test, demonstrated a significantly higher sensitivity at 79% and a similar specificity of 79%. On carcass samples the SafePath test performed similarly to the Reveal test, demonstrating a specificity of 100% relative to the reference system. There was an insufficient number of E. coli O157-positive carcass samples to estimate precisely the sensitivity of these two methods. Both methods show promise as rapid carcass monitoring tests, but further field testing to estimate sensitivity is needed to complete their evaluation. The proportion of positive fecal samples for E. coli O157:H7 by the reference method ranged from 10.2% to 36% in 10 lots of cattle with an overall mean of 17.3% (39/225). Quarter carcass sponging of 125 carcasses revealed 1.6% positive for the pathogen (2/125).
    Journal of food protection 08/2000; 63(7):860-6. · 1.80 Impact Factor
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    ABSTRACT: High pressure liquid chromatographic methods were used for measurement of the concentration of vitamin C and β-carotene in broccoli and green pepper. The effects of processing, packaging and storage on the levels of these nutrients in both unprocessed and processed ready-to-use (RTU) vegetables were determined. Systems investigated included: (a) unpacked and pillow packaged broccoli, and (b) unpacked, pillow, partial vacuum, and total vacuum packaged green pepper. There was a statistically significant decrease in vitamin C over a 10 day storage period of unpacked and packaged vegetables including all four packaging systems (P<0.001, overall average decrease of 11%). The overall loss of β-carotene during the 10 day storage period was not statistically significant (P=0.14). Although there was a significant loss in vitamin C during storage, in most cases there was no difference in loss of vitamin C or β-carotene between the processed and unprocessed vegetables, and the packaging systems.
    Food Research International 03/2000; DOI:10.1016/S0963-9969(00)00027-2 · 3.05 Impact Factor
  • Ocean & Coastal Management 12/1999; 43(1):123-135. · 1.77 Impact Factor

Publication Stats

788 Citations
86.25 Total Impact Points

Institutions

  • 2008–2013
    • Agriculture and Agri-Food Canada
      Ottawa, Ontario, Canada
  • 2012
    • Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación - SAGARPA
      Benito Juarez, The Federal District, Mexico
  • 2010
    • Government of Ontario, Canada
      XIA, Ontario, Canada
  • 1997–2010
    • University of Guelph
      • Department of Population Medicine
      Guelph, Ontario, Canada