Dataset Information

Fasciola hepatica Control Practices on a Sample of Dairy Farms in Victoria, Australia.

ABSTRACT: In Australia, little is known about the strategies used by farmers to control Fasciola hepatica (F. hepatica) infection in dairy cattle. Triclabendazole-resistant F. hepatica have recently been found on several dairy and beef properties in Australia. It is difficult to draw conclusions about how widespread resistance is in Australian dairy cattle because we have little information about flukicide usage, drug resistance testing, and alternative flukicide usage on-farm. The study objectives were to determine how dairy farmers are currently controlling F. hepatica and to identify knowledge gaps where F. hepatica control strategies need to be communicated to farmers to improve management. The survey was distributed online or by hard copy and 36 dairy farmers completed the survey. There were 34 questions including closed, open-ended, multicheck box, demographic, and text questions. Descriptive statistics were used to quantify each response. The survey results showed high use of clorsulon, limited rotation of flukicides, and limited use of diagnostic tests to inform treatment options and timing. There was poor adherence to best management practice in determining the dose of flukicides administered to cattle, with farmers often relying on estimating body weights or average body weights, suggesting that underdosing of animals is likely to be prevalent. Most respondents in this study did not isolate and quarantine treated and newly returned or purchased animals before joining them with the main herd. The research identified four knowledge gaps where communication needs to be enhanced to improve control of F. hepatica: diagnostic testing to inform flukicide use, rotation of flukicide actives, flukicide administration, and increased testing of replacement animals.

SUBMITTER: Kelley JM

PROVIDER: S-EPMC8213206 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Fasciola hepatica is an internal parasite of both human and veterinary relevance. In order to control fasciolosis, a multitude of attempts to predict the risk of infection such as risk maps or forecasting models have been developed. These attempts mainly focused on the influence of geo-climatic and meteorological features. Predicting bovine fasciolosis on farm level taking into account farm-specific settings yet remains challenging. In the present study, a new methodology for this purpose, a data-driven machine learning approach using a random forest classification algorithm was applied to a cross-sectional data set of farm characteristics, management regimes, and farmer aspects within two structurally different dairying regions in Germany in order to identify factors relevant for the occurrence of F. hepatica that could predict farm-level bulk tank milk positivity. The resulting models identified farm-specific key aspects in regard to the presence of F. hepatica. In study region North, farm-level production parameters (farm-level milk yield, farm-level milk fat, farm-level milk protein), leg hygiene, body condition (prevalence of overconditioned and underconditioned cows, respectively) and pasture access were identified as features relevant in regard to farm-level F. hepatica positivity. In study region South, pasture access together with farm-level lameness prevalence, farm-level prevalence of hock lesions, herd size, parity, and farm-level milk fat appeared to be important covariates. The stratification of the analysis by study region allows for the extrapolation of the results to similar settings of dairy husbandry. The local, region-specific modelling of F. hepatica presence in this work contributes to the understanding of on-farm aspects of F. hepatica appearance. The applied technique represents a novel approach in this context to model epidemiological data on fasciolosis which allows for the identification of farms at risk and together with additional findings in regard to the epidemiology of fasciolosis, can facilitate risk assessment and deepen our understanding of on-farm drivers of the occurrence of F. hepatica.

Dataset Information

Fasciola hepatica Control Practices on a Sample of Dairy Farms in Victoria, Australia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets