A review of methods used to adjust for cluster effects in explanatory epidemiological studies of animal populations

McDermott, John J.; Schukken, Y.H.

doi:10.1016/0167-5877(94)90073-6

Cited by 120 publications

(47 citation statements)

References 82 publications

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“…The study presented here tried to identify the factors and processing steps that contribute most to the overall contamination of carcasses and the slaughterhouse environment by using the same sampling protocol in 12 slaughterhouses in five European countries. For the statistical analyses, we used logistic regression analysis with random effects, which is a method widely used in veterinary epidemiology, where the occurrence of clustered data is common [23,24]. It is, however, to our knowledge the first time that this method has been used to identify factors associated with carcass contamination and explore the epidemiology of Salmonella contamination at the slaughterhouse level.…”

Section: Introductionmentioning

confidence: 99%

The occurrence and epidemiology of Salmonella in European pig slaughterhouses

Hald

Wingstrand²,

Swanenburg³

et al. 2003

Epidemiol. Infect.

101

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SUMMARYThis study was part of an international research project entitled SALINPORK (FAIR CT-950400) initiated in 1996. The objectives were to investigate the occurrence of Salmonella in pig slaughterhouses and to identify risk factors associated with the contamination of pig carcasses. Data was collected from 12 slaughterhouses in five European countries. Isolates were characterized by serotyping, phage typing and antimicrobial susceptibility. In one country, no Salmonella was found. Salmonella was isolated from 5 . 3% of 3485 samples of pork and from 13 . 8% of 3573 environmental samples from the seven slaughterhouses in the four remaining countries. The statistical analyses (multi-level logistic regression) indicated that the prevalence was significantly higher during the warmer months and that the environmental contamination increased during the day of slaughter. The polishing (OR 3 . 74, 95% CI 1 . 43-9 . 78) and pluck removal (OR 3 . 63, 95 % CI 1 . 66-7 . 96) processes were found to contribute significantly to the total carcass contamination, the latter especially if the scalding water also was contaminated. To reduce carcass contamination, it is recommended to ensure sufficiently high temperatures of scalding water (62 xC) and appropriate cleaning and disinfection of the polishing equipment at least once a day in order to reduce the level of carcass contamination and consequently the prevalence of Salmonella in pork.

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Section: Introductionmentioning

confidence: 99%

The occurrence and epidemiology of Salmonella in European pig slaughterhouses

Hald

Wingstrand²,

Swanenburg³

et al. 2003

Epidemiol. Infect.

101

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“…Due to computational restraints, Mousing et al (1990) did not account adequately for the fact that the data were from clusters of animals (herds) (McDermott and Schukken, 1994). Mousing et al (1990) did, however, recognize this problem.…”

Section: Introductionmentioning

confidence: 99%

Infectious and rearing-system related risk factors for chronic pleuritis in slaughter pigs

Enøe¹,

Mousing²,

Schirmer³

et al. 2002

Preventive Veterinary Medicine

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“…Concerning the herd incidence rate, a binomial distribution must be performed for a dichotomous variable (lactation with/without CMAST). Unfortunately, these theoretical distributions are rarely observed because of the Statistical modelling for clinical mastitis 495 presence of overdispersion of the studied data [50,63], which involves defective adjustments and incorrect statistical tests.…”

Section: Overdispersion At the Lactation Levelmentioning

confidence: 99%

Statistical modelling for clinical mastitis in the dairy cow: problems and solutions

Gasqui¹,

Barnouin²

2003

Vet. Res.

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-Modelling case occurrence and risk factors for clinical mastitis, as a key multifactorial disease in the dairy cow, requires statistical models. The type of model used depends on the choice of perception or the study level: herd, lactation, animal, udder and quarter. The validity of the tests that are performed through these models is especially ensured when hypotheses of independence between statistical units are respected, and when the model adjustments do not involve overdispersion faced with the observed data. In the article, the main sources of overdispersion are identified according to the different levels of perception of mastitis risk. Then, the proposed solutions to control for overdispersion at each study level are discussed and the difficulty to compare the study results is highlighted through a variety of methodological choices of the authors. Two main categories of models are used for modelling clinical mastitis, i.e. generalist exploratory models and explanatory designed models. The contribution of the explanatory models to improve modelling accuracy and relevance is documented through the two main published methodological approaches, the first one being based on a states model, and the second on a survival model. The integration and optimisation of such explanatory modelling methods should be possible in the future in order to develop a more global explanatory model including herd risk factors, which could pertinently predict udder infections (both clinical and subclinical) at the cow, lactation, or even udder and quarter levels.clinical mastitis / dairy cow / epidemiology / modelling / overdispersion

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A review of methods used to adjust for cluster effects in explanatory epidemiological studies of animal populations

Cited by 120 publications

References 82 publications

The occurrence and epidemiology of Salmonella in European pig slaughterhouses

The occurrence and epidemiology of Salmonella in European pig slaughterhouses

Infectious and rearing-system related risk factors for chronic pleuritis in slaughter pigs

Statistical modelling for clinical mastitis in the dairy cow: problems and solutions

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