The impact of liver fluke infection on steers in Ireland: A meta-analytic approach.

Post-mortem liver inspection results together with production parameters are often used to estimate the impact of liver fluke infection on farm animal populations. However, post mortem liver inspection is an imperfect method of determining the liver fluke infection status of cattle. This work estimates the difference in mean lifetime weight gain at 819 days (ΔLWG819) between steers assigned liver fluke negative (LFN) and liver fluke positive (LFP) status at post-mortem meat inspection, quantifies the potential impact of imperfect sensitivity and specificity on these results and estimates the economic impact of these differences. The study population is 32,007 steers that never moved from their birth herd in the Republic of Ireland and were slaughtered in one of two Irish meat processors in 2014. Individual animal-level data are used to generate 46 county - processor level estimates of ΔLWG819. Standard errors and confidence intervals for these estimates are derived using bootstrapping. A meta-analytic approach is then used to obtain 3 overall estimates of the effect of liver fluke status on the ΔLWG819 in all the county - processor combinations, assuming post - mortem liver inspection Se = Sp = 1, 0.99 and 0.95. A random effects model is used and 95% prediction intervals (95% PI) are calculated. Assuming Se = Sp = 1 for post - mortem liver inspection, the random effects summary estimate of ΔLWG819 (ΔLWG819(RE)) is 36 kg (95% PI: -1, 73). There is a minor change in ΔLWG819(RE) (38 kg, 95% PI: -1, 77) when Se = Sp = 0.99 is assumed but this increases to 46 kg (95% PI: -2, 94) assuming Se = Sp = 0.95. The corresponding cost in euros of these differences between the LFN and LFP steers, assuming a price per kg of €3.90, are €77.01 (95% PI: -2.57, 156.37), €80.65 (95% PI: -3.43, 164.74) and €98.67 (95% PI: -5.15, 202.27) respectively. Our results demonstrate an association between liver fluke infection and reduced weight gain. We show that the effect of liver fluke infection on weight gain in cattle is underestimated due to misclassification resulting from imperfection in post mortem meat inspection. These findings will aid researchers, farmers and veterinary practitioners to make informed decisions on the control of liver fluke on farms.

Genetic correlations between endo-parasite phenotypes and economically important traits in dairy and beef cattle.

Parasitic diseases have economic consequences in cattle production systems. Although breeding for parasite resistance can complement current control practices to reduce the prevalence globally, there is little knowledge of the implications of such a strategy on other performance traits. Records on individual animal antibody responses to Fasciola hepatica, Ostertagia ostertagi, and Neospora caninum were available from cows in 68 dairy herds (study herds); national abattoir data on F. hepatica-damaged livers were also available from dairy and beef cattle. After data edits, 9,271 dairy cows remained in the study herd dataset, whereas 19,542 dairy cows and 68,048 young dairy and beef animals had a record for the presence or absence of F. hepatica-damaged liver in the national dataset. Milk, reproductive, and carcass phenotypes were also available for a proportion of these animals as well as their contemporaries. Linear mixed models were used to estimate variance components of antibody responses to the three parasites; covariance components were estimated between the parasite phenotypes and economically important traits. Heritability of antibody responses to the different parasites, when treated as a continuous trait, ranged from 0.07 (O. ostertagi) to 0.13 (F. hepatica), whereas the coefficient of genetic variation ranged from 4% (O. ostertagi) to 20% (F. hepatica). The antibody response to N. caninum was genetically correlated with the antibody response to both F. hepatica (-0.29) and O. ostertagi (-0.67); a moderately positive genetic correlation existed between the antibody response to F. hepatica and O. ostertagi (0.66). Genetic correlations between the parasite phenotypes and the milk production traits were all close to zero (-0.14 to 0.10), as were the genetic correlations between F. hepatica-damaged livers and the carcass traits of carcass weight, conformation, and fat score evaluated in cows and young animals (0.00 to 0.16). The genetic correlation between F. hepatica-damaged livers in cows and milk somatic cell score was 0.32 (SE = 0.20). Antibody responses to F. hepatica and O. ostertagi had favorable genetic correlations with fertility traits, but conversely, antibody response to N. caninum and F. hepatica-damaged livers were unfavorably genetically correlated with fertility. This study provides the necessary information to undertake national multitrait genetic evaluations for parasite phenotypes.

A protocol to identify and minimise selection and information bias in abattoir surveys estimating prevalence, using Fasciola hepatica as an example.

Abattoir surveys and findings from post-mortem meat inspection are commonly used to estimate infection or disease prevalence in farm animal populations. However, the function of an abattoir is to slaughter animals for human consumption, and the collection of information on animal health for research purposes is a secondary objective. This can result in methodological shortcomings leading to biased prevalence estimates. Selection bias can occur when the study population as obtained from the abattoir is not an accurate representation of the target population. Virtually all of the tests used in abattoir surveys to detect infections or diseases that impact animal health are imperfect, leading to errors in identifying the outcome of interest and consequently, information bias. Examination of abattoir surveys estimating prevalence in the literature reveals shortcomings in the methods used in these studies. While the STROBE-Vet statement provides clear guidance on the reporting of observational research, we have not found any guidelines in the literature advising researchers on how to conduct abattoir surveys. This paper presents a protocol in two flowcharts to help researchers (regardless of their background in epidemiology) to first identify, and, where possible, minimise biases in abattoir surveys estimating prevalence. Flowchart 1 examines the identification of the target population and the appropriate study population while Flowchart 2 guides the researcher in identifying, and, where possible, correcting potential sources of outcome misclassification. Examples of simple sensitivity analyses are also presented which approximate the likely uncertainty in prevalence estimates due to systematic errors. Finally, the researcher is directed to outline any limitations of the study in the discussion section of the paper. This protocol makes it easier to conduct an abattoir survey using sound methods, identifying and, where possible, minimizing biases.