Disease frequencies in dairy cows in Sweden. v. mastisis

Bendixen, P.H.; Vilson, B.; Ekesbo, I.; Åstrand, D.B.

doi:10.1016/0167-5877(88)90012-8

Cited by 49 publications

(36 citation statements)

References 14 publications

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“…Among important factors belong the breed as documented in Holstein and also other breeds (Saloniemi et al 1986;Bendixen et al 1987Bendixen et al , 1988Gröhn et al 1989Gröhn et al , 1990aGröhn et al , 1990bGröhn et al , 1994Oltenacu et al 1990;Rajala and Gröhn 1998). None of the above-mentioned studies, however, was carried out in Germany.…”

mentioning

confidence: 99%

Clinical Disorders in Holstein Cows: Incidence and Associations among Lactational Risks Factors

Fleischer¹,

Metzner²,

Hoedemaker³

et al. 2001

Acta Vet. Brno

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mentioning

confidence: 99%

Clinical Disorders in Holstein Cows: Incidence and Associations among Lactational Risks Factors

Fleischer¹,

Metzner²,

Hoedemaker³

et al. 2001

Acta Vet. Brno

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“…The relationship between nutritional / management factors, poor feeding and present in infectious agent in the environment would be the second position of abortion. Twining poor feeding and management as a cause of dystocia [17][18][19][20] ) may be associated with the relatively high incidence of dystocia and retained placenta observed in the study. Similarly the high incidence of urinary tract infection in male would be associated with service to any types of small ruminants, dry weather of the region and neglected of the infection.…”

Section: Discussionmentioning

confidence: 99%

Retrospective Study of Reproductive Diseases of Small Ruminants in Northern Barind Tract in Bangladesh

Islam¹

2015

AVS

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Abstract:Context: The information of diseases prevalence give useful information on disease pattern and thus can be used in preventing diseases as well as formulating policies for future management to prevent diseases. Aim: This study is therefore aimed at determining the pattern of reproductive diseases encountered at the Barind tract in Bangladesh. Materials and Method: The primary data were collected by randomly selected location in each district of retrospective survey from the veterinary and vaccination camp of the study area. Records of 2667 clinical cases of small ruminants (2394 goats, 273 sheep) questionnaires report under this study, from July 2012 to June 2013 were analyzed to assess the importance of existing diseases. The computer program SPSS were analyzed the study and Chi-square and F test were used for significance test. Results: The small ruminants were significantly suffering from various diseases and disorders. The maximum 816 (30.6%) was affected by infectious diseases and lowest 18 (0.7%) was affected with poisonous diseases in small ruminants. The others diseases highest to lowest rate were 444 (16.6%), 354(13.3%), 345 (12.9%), 231 (8.7%), 162 (6.1%),102 (3.8%), 84 (3.1%),72 (2.7%) and 39 (1.5%) affected with gastrointestinal, respiratory, surgical, female reproductive disorder, deficiency syndrome, Integumentary involvement, diseases of sense organ, musculoskeletal system and disease of male sex organ respectively in small . The highest disease prevalence (89.8%) was observed in goat than in sheep (10.2%) and the total reproductive disease prevalence was 10.2%. The highest & lowest incidence rates of reproductive disorders in relation to sex were 32.5% & 1.9% in anoestrus and postitis. Similarly, the age had significant effect (P<0.05) and highest value were 20.4%, 7.9% & 4.5% observed in anoestrus of young, adult and old ages respectively. The season had significant effect and the overall disease prevalence was higher rainy season 40.4%, but the individual highest value observed in anoestrus 14.7% in winter season. Conclusion: The one tenth portion of disease prevalence got in reproductive related case, but most frequent reproductive diseases and disorder were in found in goat, female animal, young age, rainy season and particularly in anoestrus condition of small ruminants at northern Barind tract in Bangladesh.

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“…The International dairy Federation recommends considering the 30 days before calving for primiparous animals [50]. In other studies, lactation is divided into different successive periods: according to the 4 seasons [60], 2 periods of 2 and 7 months [15], or 4 periods [29]. The periods are even fixed by some authors in a cumulative way [43,44].…”

Section: Solutions For Within Lactation Dependencementioning

confidence: 99%

“…Among the lactation splitters, some keep only one occurrence within the lactation [15,29], or integrate the minimal time interval between consecutive CMAST cases (see above). These authors aim to obtain over one specific period, and not on the whole lactation, a dichotomous response.…”

Section: Solutions For Within Lactation Dependencementioning

confidence: 99%

“…According to the calculation, either the observed lactation duration is not considered or the time interval while an animal is not at risk after a CMAST occurrence is a priori variably chosen. In other respects, the calculation from the overall number of lactations (or specific lactation periods) with at least one CMAST is then related to the numbers of cows-lactation at risk [6,11,17,32,39,41,52,55,79] or of CMAST-free months [14,15]. When the calculation is made from the total number of cases (per udder or per quarter), it is divided by the total number of cows-day at risk [3-5, 11, 30, 34, 48, 54, 55, 69, 79], the study period within the lactation [13], or even by the number of cowsweek [9,10,56] or cows-month [28,48,54].…”

Section: Solutions For Within Herd Dependencementioning

confidence: 99%

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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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Disease frequencies in dairy cows in Sweden. v. mastisis

Cited by 49 publications

References 14 publications

Clinical Disorders in Holstein Cows: Incidence and Associations among Lactational Risks Factors

Clinical Disorders in Holstein Cows: Incidence and Associations among Lactational Risks Factors

Retrospective Study of Reproductive Diseases of Small Ruminants in Northern Barind Tract in Bangladesh

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

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