The influence of liver fluke infection on production in sheep and cattle: a meta-analysis.
2021
Abstract Liver flukes (Fasciola spp.) are important parasites of ruminant livestock worldwide, causing profound damage to animal health and productivity. Many reviews have discussed the results of decades of research on the impact of fluke on livestock traits such as weight gain and milk production, but there have been no known attempts to collate previous research in a quantitative manner or to determine the factors that vary between studies that find substantial effects of fluke and others concluding that effects of fluke are negligible. Here, we use meta-analysis to provide quantitative “global” estimates of the impact of liver fluke on animal performance, and to identify elements of study design (“moderators”) that influence variation between studies in their outcome. A literature search provided 233 comparisons of performance in fluke-infected and uninfected animals. We standardized these data as log response ratios and calculated effect size variances to weight studies by the accuracy of their estimates. We performed multi-level meta-analysis to estimate effects of fluke infection on daily weight gain, live weight, carcass weight, total weight gain and milk production. There were statistically-supported negative effects of fluke infection on daily weight gain, live weight and carcass weight (9%, 6% and 0.6% reductions, respectively), but not on total weight gain or milk production. A mixed-effects meta-analysis revealed that studies of younger animals found more severe effects of fluke on weight gain and that effects on live weight increased with time since infection. Limitations to the data that could be analysed, including a lack of statistical reporting in older papers and variation in the outcome variables measured, may have explained the relatively limited influence of modifiers that we detected. Our results provide, to our knowledge, the first quantitative estimate of the impact of liver fluke on performance across studies and highlight some elements of study design that can influence conclusions.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
71
References
1
Citations
NaN
KQI