Abstract

BackgroundFor infectious diseases, the probability that an animal gets infected depends on its own susceptibility, and on the number of infectious herd mates and their infectivity. Together with the duration of the infectious period, susceptibility and infectivity determine the basic reproduction ratio of the disease ( R_{0} ). R_{0} is the average number of secondary cases caused by a typical infectious individual in an otherwise uninfected population. An infectious disease dies out when R_{0} is lower than 1. Thus, breeding strategies that aim at reducing disease prevalence should focus on reducing R_{0} , preferably to a value lower than 1. In animal breeding, however, R_{0} has received little attention. Here, we estimate the additive genetic variance in host susceptibility, host infectivity, and R_{0} for the endemic claw disease digital dermatitis (DD) in Holstein Friesian dairy cattle, and estimate genomic breeding values (GEBV) for these traits. We recorded DD disease status of both hind claws of 1513 cows from 12 Dutch dairy farms, every 2 weeks, 11 times. The genotype data consisted of 75,904 single nucleotide polymorphisms (SNPs) for 1401 of the cows. We modelled the probability that a cow got infected between recordings, and compared four generalized linear mixed models. All models included a genetic effect for susceptibility; Models 2 and 4 also included a genetic effect for infectivity, while Models 1 and 2 included a farm*period interaction. We corrected for variation in exposure to infectious herd mates via an offset.ResultsGEBV for R_{0} from the model that included genetic effects for susceptibility only had an accuracy of ~ 0.39 based on cross-validation between farms, which is very high given the limited amount of data and the complexity of the trait. Models with a genetic effect for infectivity showed a larger bias, but also a slightly higher accuracy of GEBV. Additive genetic standard deviation for R_{0} was large, i.e. ~ 1.17, while the mean R_{0} was 2.36.ConclusionsGEBV for R_{0} showed substantial variation. The mean R_{0} was only about one genetic standard deviation greater than 1. These results suggest that lowering DD prevalence by selective breeding is promising.

Highlights

  • For infectious diseases, the probability that an animal gets infected depends on its own susceptibility, and on the number of infectious herd mates and their infectivity

  • The mean R0 was only about one genetic standard deviation greater than 1. These results suggest that lowering digital dermatitis (DD) prevalence by selective breeding is promising

  • We focused on the endemic infectious disease digital dermatitis (DD)

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Summary

Introduction

The probability that an animal gets infected depends on its own susceptibility, and on the number of infectious herd mates and their infectivity. Genetic inference on infectious diseases can probably be improved by using quantitative genetic models that are founded on epidemiological theory Such models would give estimates of genetic variation and breeding values for fundamental epidemiological parameters, such as the basic reproduction number R0 (see below). Such knowledge would facilitate the prediction of response to selection while accounting for the non-linear nature of infectious diseases, including phenomena such as positive feedback and the eradication of a disease when R0 falls below 1 [9]

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