RISK FACTORS ASSOCIATED WITH CULLING AGE IN DAIRY CATTLE: APPLICATIONS OF FRAILTY MODELS

Culling decisions for dairy cattle are an important component of dairy herd management. To investigate risk factors for culling, farms (clusters) constitute the sampling units. Therefore, we believe that ages-at-culling may be correlated within farms. The score test on the null hypothesis of no extra-variation in survival data was not supported by age-at-culling data collected from 72 dairy farms from the province of Ontario, Canada. To correct for the intraherd correlation, three modelling approaches were used to fit the data: Population-Averaged (PA) , cluster-specific (CS), and Random Effects Models (RAEM). The modelling approaches are described and compared using the dairy cow culling data

Levels of Evidence, Quality Assessment, and Risk of Bias: Evaluating the Internal Validity of Primary Research

Clinical decisions in human and veterinary medicine should be based on the best available evidence. The results of primary research are an important component of that evidence base. Regardless of whether assessing studies for clinical case management, developing clinical practice guidelines, or performing systematic reviews, evidence from primary research should be evaluated for internal validity i.e., whether the results are free from bias (reflect the truth). Three broad approaches to evaluating internal validity are available: evaluating the potential for bias in a body of literature based on the study designs employed (levels of evidence), evaluating whether key study design features associated with the potential for bias were employed (quality assessment), and applying a judgement as to whether design elements of a study were likely to result in biased results given the specific context of the study (risk of bias assessment). The level of evidence framework for assessing internal validity assumes that internal validity can be determined based on the study design alone, and thus makes the strongest assumptions. Risk of bias assessments involve an evaluation of the potential for bias in the context of a specific study, and thus involve the least assumptions about internal validity. Quality assessment sits somewhere between the assumptions of these two. Because risk of bias assessment involves the least assumptions, this approach should be used to assess internal validity where possible. However, risk of bias instruments are not available for all study designs, some clinical questions may be addressed using multiple study designs, and some instruments that include an evaluation of internal validity also include additional components (e.g., evaluation of comprehensiveness of reporting, assessments of feasibility or an evaluation of external validity). Therefore, it may be necessary to embed questions related to risk of bias within existing quality assessment instruments. In this article, we overview the approaches to evaluating internal validity, highlight the current complexities, and propose ideas for approaching assessments of internal validity

The Change in Prevalence of Campylobacter on Chicken Carcasses During Processing: A Systematic Review

A systematic review was conducted to evaluate the change in prevalence of Campylobacter on chicken carcasses during processing. A structured literature search of 8 electronic databases using the key words for Campylobacter, chicken, and processing identified 1,734 unique citations. Abstracts were screened for relevance by 2 independent reviewers. Thirty-two studies described prevalence at more than one stage during processing and were included in this review. Of the studies that described the prevalence of Campylobacter on carcasses before and after specific stages of processing, the chilling stage had the greatest number of studies (9), followed by washing (6), defeathering (4), scalding (2), and evisceration (1). Studies that sampled before and after scalding or chilling, or both, showed that the prevalence of Campylobacter generally decreased immediately after the stage (scalding: 20.0 to 40.0% decrease; chilling: 100.0% decrease to 26.6% increase). The prevalence of Campylobacter increased after defeathering (10.0 to 72.0%) and evisceration (15.0%). The prevalence after washing was inconsistent among studies (23.0% decrease to 13.3% increase). Eleven studies reported the concentration of Campylobacter, as well as, or instead of, the prevalence. Studies that sampled before and after specific stages of processing showed that the concentration of Campylobacter decreased after scalding (minimum decrease of 1.3 cfu/g, maximum decrease of 2.9 cfu/mL), evisceration (0.3 cfu/g), washing (minimum 0.3 cfu/mL, maximum 1.1 cfu/mL), and chilling (minimum 0.2 cfu/g, maximum 1.7 cfu/carcass) and increased after defeathering (minimum 0.4 cfu/g, maximum 2.9 cfu/mL). Available evidence is sparse and suggests more data are needed to understand the magnitude and mechanism by which the prevalence and concentration of Campylobacter changes during processing. This understanding should help researchers and program developers identify the most likely points in processing to implement effective control efforts. For example, if contamination will occur during defeathering and likely during evisceration, critical control points postevisceration are likely to have a greater effect on the end product going to the consumer

The Influence of Climate and Livestock Reservoirs on Human Cases of Giardiasis.

Giardia duodenalis is an intestinal parasite which causes diarrhoeal illness in people. Zoonotic subtypes found in livestock may contribute to human disease occurrence through runoff of manure into multi-use surface water. This study investigated temporal associations among selected environmental variables and G. duodenalis occurrence in livestock reservoirs on human giardiasis incidence using data collected in the Waterloo Health Region, Ontario, Canada. The study objectives were to: (1) evaluate associations between human cases and environmental variables between 1 June 2006 and 31 December 2013, and (2) evaluate associations between human cases, environmental variables and livestock reservoirs using a subset of this time series, with both analyses controlling for seasonal and long-term trends. Human disease incidence exhibited a seasonal trend but no annual trend. A Poisson multivariable regression model identified an inverse association with water level lagged by 1 month (IRR = 0.10, 95% CI 0.01, 0.85, P < 0.05). Case crossover analysis found varying associations between lagged variables including livestock reservoirs (1 week), mean air temperature (3 weeks), river water level (1 week) and flow rate (1 week), and precipitation (4 weeks). This study contributes to our understanding of epidemiologic relationships influencing human giardiasis cases in Ontario, Canada