Super-shedding cattle and the transmission dynamics ofEscherichia coliO157
| Autor: | George J. Gunn, I.J. McKendrick, Louise Matthews, B. A. Synge, M. E. J. Woolhouse, H. E. Ternent |
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| Rok vydání: | 2005 |
| Předmět: |
Veterinary medicine
education.field_of_study Epidemiology Data Collection Population Cattle Diseases Models Theoretical Biology Escherichia coli O157 medicine.disease_cause law.invention Cross-Sectional Studies Infectious Diseases Transmission (mechanics) Scotland law Prevalence medicine Animals Cattle Animal Husbandry education Escherichia coli Escherichia coli Infections Research Article |
| Zdroj: | Epidemiology and Infection. 134:131-142 |
| ISSN: | 1469-4409 0950-2688 |
| DOI: | 10.1017/s0950268805004590 |
| Popis: | SUMMARYThe prevalence ofEscherichia coliO157 displays striking variability across the Scottish cattle population. On 78% of farms, in a cross-sectional survey of 952, no shedding ofE. coliO157 was detected, but on a small proportion, ∼2%, very high prevalences of infection were found (with 90–100% of pats sampled being positive). We ask whether this variation arises from the inherent stochasticity in transmission dynamics or whether it is a signature of underlying heterogeneities in the cattle population. A novel approach is taken whereby the cross-sectional data are viewed as providing independent snapshots of a dynamic process. Using maximum-likelihood methods to fit time-dependent epidemiological models to the data we obtain estimates for the rates of immigration and transmission ofE. coliO157 infection – parameters which have not been previously quantified in the literature. A comparison of alternative model fits reveals that the variation in the prevalence data is best explained when a proportion of the cattle are assumed to transmit infection at much higher levels than the rest – the so-called super-shedders. Analysis of a second dataset, comprising samples taken from 32 farms at monthly intervals over a period of 1 year, additionally yields an estimate for the rate of recovery from infection. The pattern of prevalence displayed in the second dataset also strongly supports the super-shedder hypothesis. |
| Databáze: | OpenAIRE |
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