43 results on '"Steeneveld, Wilma"'
Search Results
2. Associations between dairy farm performance indicators and culling rates under policy-driven herd size constraints.
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Kulkarni, Pranav, Mourits, Monique, Nielen, Mirjam, and Steeneveld, Wilma
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fertility ,herd characteristics ,longevity ,performance ,phosphate ,primiparous cows ,replacement ,udder health - Abstract
INTRODUCTION: This article aimed to study cross-sectional associations between the performance of dairy farms and their corresponding culling proportions under the herd size constraint as imposed in 2018 by the new phosphate regulation in the Netherlands. METHODS: To this end, production data from 10,540 Dutch dairy farms were analyzed to capture the inflow and outflow of both primiparous and multiparous cows. Farm performance was measured by 10 indicators structured in four areas of longevity, production, reproduction, and udder health. Farm culling proportions were represented by the overall culling (OC) and the number of culled primiparous cows in relation to (i) the total number of producing cows (PC), (ii) the number of producing primiparous cows (PPC), and (iii) the number of culled producing cows (POC). Spearmans rank correlation and weighted logistic regression were adopted to study associations. RESULTS: In 2018, on average, 28% of producing cows were culled (OC). The number of primiparous cows culled represented 4.5% of the total number of producing cows (PC) and the mean proportion of culled primiparous cows was 18.8% of the total number of producing primiparous cows (PPC), and, of the total number of producing culled cows, 15% were primiparous cows (POC). However, the variance around the mean, and among individual farms, was high (SD 4-15% for all four culling proportions). Results from rank correlation showed very low-rank conformity (
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- 2023
3. The economic impact of endemic respiratory disease in pigs and related interventions - a systematic review
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Boeters, Marloes, Garcia-Morante, Beatriz, van Schaik, Gerdien, Segalés, Joaquim, Rushton, Jonathan, and Steeneveld, Wilma
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- 2023
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4. Economic impacts of constrained replacement heifer supply in dairy herds
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Kulkarni, Pranav S., Haijema, Rene, Hogeveen, Henk, Steeneveld, Wilma, and Mourits, Monique C.M.
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- 2024
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5. Hormone use for reproductive diseases and heat induction in relation to herd-level reproductive performance in Dutch dairy farms
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Wicaksono, Ardilasunu, van den Borne, Bart H.P., Steeneveld, Wilma, van Werven, Tine, and Hogeveen, Henk
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- 2023
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6. Quantifying cost of disease in livestock: a new metric for the Global Burden of Animal Diseases
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Gilbert, William, primary, Marsh, Thomas L, additional, Chaters, Gemma, additional, Jemberu, Wudu T, additional, Bruce, Mieghan, additional, Steeneveld, Wilma, additional, Afonso, Joao S, additional, Huntington, Benjamin, additional, and Rushton, Jonathan, additional
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- 2024
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7. A stochastic modelling approach to determine the effect of diverse Staphylococcus aureus strains on the economic and epidemiological outcomes of mastitis intervention strategies in dairy cattle
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Exel, Catharina E., Halasa, Tariq, Koop, Gerrit, Steeneveld, Wilma, Lam, Theo J.G.M., Benedictus, Lindert, and Gussmann, Maya
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- 2022
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8. Survival analysis of dairy cows in the Netherlands under altering agricultural policy
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Kulkarni, Pranav, Mourits, Monique, Nielen, Mirjam, van den Broek, Jan, and Steeneveld, Wilma
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- 2021
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9. Prediction of persistency for day 305 of lactation at the moment of the insemination decision
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Chen, Yongyan, primary, Steeneveld, Wilma, additional, Nielen, Mirjam, additional, and Hostens, Miel, additional
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- 2023
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10. Milk β-hydroxybutyrate metrics and its consequences for surveillance of hyperketonaemia on commercial dairy farms
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De Jong, Elise, primary, Rijpert-Duvivier, Angelique, additional, Veldman, Hendrik, additional, Steeneveld, Wilma, additional, and Jorritsma, Ruurd, additional
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- 2023
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11. Economic and epidemiological impact of different intervention strategies for subclinical and clinical mastitis
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Gussmann, Maya, Steeneveld, Wilma, Kirkeby, Carsten, Hogeveen, Henk, Farre, Michael, and Halasa, Tariq
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- 2019
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12. The DECIDE project: from surveillance data to decision-support for farmers and veterinarians
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van Schaik, Gerdien, primary, Hostens, Miel, additional, Faverjon, Céline, additional, Jensen, Dan B., additional, Kristensen, Anders R., additional, Ezanno, Pauline, additional, Frössling, Jenny, additional, Dórea, Fernanda, additional, Jensen, Britt-Bang, additional, Carmo, Luis Pedro, additional, Steeneveld, Wilma, additional, Rushton, Jonathan, additional, Gilbert, William, additional, Bearth, Angela, additional, Siegrist, Michael, additional, Kaler, Jasmeet, additional, Ripperger, Johannes, additional, Siehler, Jamuna, additional, de Wit, Sjaak, additional, Garcia-Morante, Beatriz, additional, Segalés, Joaquim, additional, Pardon, Bart, additional, Bokma, Jade, additional, and Nielen, Mirjam, additional
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- 2023
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13. Editorial: Proceedings of the 5th ISESSAH conference 2021: economics and social sciences applied to livestock and aquaculture health
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Indrawan, Dikky, primary, Mohd Nor, Norhariani, additional, Vosough Ahmadi, Bouda, additional, Raboisson, Didier, additional, Pendell, Dustin L., additional, Buda, Mark, additional, Kamarulzaman, Nitty Hirawaty, additional, Steeneveld, Wilma, additional, Rushton, Jonathan, additional, and Hogeveen, Henk, additional
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- 2023
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14. Associations between dairy farm performance indicators and culling rates under policy-driven herd size constraints
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Kulkarni, Pranav Shrikant, primary, Mourits, Monique, additional, Nielen, Mirjam, additional, and Steeneveld, Wilma, additional
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- 2023
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15. Economic Impacts of Constrained Replacement Heifer Supply in Dairy Herds
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Kulkarni, Pranav Shrikant Shrikant, primary, Haijema, Rene, additional, Hogeveen, H., additional, Steeneveld, Wilma, additional, and Mourits, M., additional
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- 2023
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16. Stochastic Model to Assess Bio-Economic Impact of PRRS on Pig Farms in Costa Rica
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Meléndez-Arce, Ronald, primary, Vargas-Leitón, Bernardo, additional, Steeneveld, Wilma, additional, van Nes, Arie, additional, Stegeman, Arjan, additional, and Romero Zúñiga, Juan, additional
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- 2023
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17. The association of herd performance indicators with dairy cow longevity: An empirical study
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Han, Ruozhu, primary, Mourits, Monique, additional, Steeneveld, Wilma, additional, and Hogeveen, Henk, additional
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- 2022
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18. Linear Mixed-Effects Model to Quantify the Association between Somatic Cell Count and Milk Production in Italian Dairy Herds
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Luo, Tiantian, primary, Steeneveld, Wilma, additional, Nielen, Mirjam, additional, Zanini, Lucio, additional, and Zecconi, Alfonso, additional
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- 2022
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19. Herd level economic comparison between the shape of the lactation curve and 305 d milk production
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Chen, Yongyan, primary, Hostens, Miel, additional, Nielen, Mirjam, additional, Ehrlich, Jim, additional, and Steeneveld, Wilma, additional
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- 2022
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20. Dutch dairy farmers' perspectives on culling reasons and strategies
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Kulkarni, Pranav Shrikant, Mourits, Monique (MCM), Slob, Jasmijn, Veldhuis, Anouk (AMB), Nielen, Mirjam, Hogeveen, Henk, van Schaik, Gerdien, and Steeneveld, Wilma
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culling ,longevity ,dairy ,reasons ,survey ,intentions - Abstract
Supplementary information/ material for manuscript titled "Dutch dairy farmers’ perspectives on culling reasons and strategies"
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- 2022
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21. Estimating the Effect of a Bovine Viral Diarrhea Virus Control Program: An Empirical Study on the Performance of Dutch Dairy Herds
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Yue, Xiaomei, primary, Wu, Jingyi, additional, van der Voort, Mariska, additional, Steeneveld, Wilma, additional, and Hogeveen, Henk, additional
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- 2022
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22. When in Doubt ... Be Indecisive
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van der Gaag, Linda C., Renooij, Silja, Steeneveld, Wilma, Hogeveen, Henk, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Sossai, Claudio, editor, and Chemello, Gaetano, editor
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- 2009
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23. Dutch dairy farmers’ perspective on culling reasons and strategies
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Pranav Kulkarni, Mourits, Monique, Slob, Jasmijn, Veldhuis, Anouk, Nielen, Mirjam, Hogeveen, Henk, Van Schaik, Gerdien, and Steeneveld, Wilma
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- 2022
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24. The impact of changes in national agricultural policy on the survival age of Dutch dairy cows
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Pranav Kulkarni, Mourits, Monique, Van Den Broek, Jan, Nielen, Mirjam, and Steeneveld, Wilma
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- 2022
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25. Linear Mixed-Effects Model to Quantify the Association between Somatic Cell Count and Milk Production in Italian Dairy Herds.
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Luo, Tiantian, Steeneveld, Wilma, Nielen, Mirjam, Zanini, Lucio, and Zecconi, Alfonso
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MILK yield , *DAIRY cattle , *SOMATIC cells , *DAIRY farm management , *PRODUCTION losses , *SCIENTIFIC literature , *DAIRY farms - Abstract
Simple Summary: Milk production loss due to mastitis in dairy herds is economically important. This study based on milk test records on more than 800,000 cows in Lombardy (Italy), and using a mixed-effects model with six fixed effects (geographical Area, Breed, Days in Milk, Parity, Season and Year) this study confirmed a negative association of somatic cell counts with milk production. However, the changes in milk production were different from others reported from previous scientific literature, suggesting that local factors may affect this association. Therefore, before estimating the economic impacts of mastitis, it is crucial to quantify the association between mastitis and milk production in relation to the characteristics of the sampled population. The results could help in prioritizing the interventions from the advisory services. They may be also used as a reference for areas in other countries with similar characteristics to Lombardy. Milk production loss due to mastitis in dairy herds is economically important. Before estimating the economic impacts of mastitis, it is crucial to quantify the association between mastitis and milk production. The objective of this study was to estimate the association between somatic cell count (SCC, as an indicator of intramammary infection due to mastitis) and milk production for dairy cows in Lombardy, Italy. The test-day (TD) records data of 3816 dairy herds located in three different geographical areas of Lombardy from January 2016 to December 2018 were used. After data editing, the final dataset comprised 10,445,464 TD records from 2970 farms and 826,831 cows. The analysis was carried out by using a mixed-effects model with six fixed effects (geographical Area, Breed, Days in Milk, Parity, Season and Year) and nested random effects for each cow and herd. The results confirmed that the SCC had a negative association with milk production. On average, this study found that any two-fold increase of SCC resulted in a milk production loss of 0.830 (95% CI: −0.832, −0.828) kg/cow/day in the whole of Lombardy. These results can be used for economic calculations on the costs of mastitis. [ABSTRACT FROM AUTHOR]
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- 2023
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26. The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus–free program
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Yue, Xiaomei, Voort, Mariska van der, Steeneveld, Wilma, Schaik, Gerdien van, Vernooij, Johannes C.M., Duijn, Linda van, Hogeveen, Henk, FAH Evidence based Veterinary Medicine, dFAH AVR, FAH Evidence based Veterinary Medicine, and dFAH AVR
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Diarrhea ,Veterinary medicine ,viruses ,animal diseases ,Bedrijfseconomie ,Cattle Diseases ,Cell Count ,WASS ,Culling ,Biology ,Virus ,Herd immunity ,03 medical and health sciences ,Business Economics ,Calving interval ,Taverne ,Genetics ,Animals ,control program ,Viral diarrhea ,030304 developmental biology ,calving interval ,0303 health sciences ,culling ,Diarrhea Viruses, Bovine Viral ,somatic cell count ,Diarrhea Virus 1, Bovine Viral ,0402 animal and dairy science ,virus diseases ,04 agricultural and veterinary sciences ,040201 dairy & animal science ,bovine viral diarrhea virus ,Herd ,Bovine Virus Diarrhea-Mucosal Disease ,Cattle ,Female ,Calf mortality ,Animal Science and Zoology ,Somatic cell count ,Food Science - Abstract
Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date. To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explanatory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program.
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- 2021
27. An Empirical Analysis on the Longevity of Dairy Cows in Relation to Economic Herd Performance
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Vredenberg, Imke, Han, Ruozhu, Mourits, Monique, Hogeveen, Henk, Steeneveld, Wilma, FAH veterinaire epidemiologie, FAH Evidence based Veterinary Medicine, dFAH AVR, FAH veterinaire epidemiologie, FAH Evidence based Veterinary Medicine, and dFAH AVR
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media_common.quotation_subject ,animal diseases ,Bedrijfseconomie ,Environmental pollution ,WASS ,Culling ,Biology ,Gross margin ,Milking ,Animal science ,culling age ,longevity ,Business Economics ,Animal welfare ,media_common ,Original Research ,lcsh:Veterinary medicine ,General Veterinary ,Longevity ,food and beverages ,lifetime milk production ,economics ,Random effects model ,accounting data ,Herd ,lcsh:SF600-1100 ,Veterinary Science ,dairy (cows) - Abstract
Several studies have stated the various effects of an increased dairy cow longevity on economic herd performance, but empirical studies are lacking. This study aimed to investigate the association between longevity of dairy cows and the economic performance of dairy herds based on longitudinal Dutch accounting data. Herd and farm accounting data (n = 855 herds) over the years 2007–2016 were analyzed. Herd data contained yearly averages on longevity features, herd size and several production variables. Longevity was defined as the age of cows at culling and by lifetime milk production of culled cows. Farm accounting data contained yearly averages on revenues, fixed and variable costs of the herds, by which gross margins were defined. Data was analyzed using generalized linear mixed modeling, with gross margin as dependent variable. The independent variables consisted of average age of culled cows, average lifetime production of culled cows, year, herd size, herd intensity (milk production per ha), herd expansion rate, soil type, milking system, successor availability, total full-time equivalent, heifer ratio (% of heifers per cow) and use of outsourced heifer rearing. Herd was included as a random effect to account for the heterogeneity among herds. Descriptive statistics showed that the average age of culled cows was 5.87 (STD = 0.78) years and the average lifetime milk production of culled cows was 31.87 (STD = 7.56) tons per cow with an average herd size of 89 cows (STD = 38.85). The average age of culled cows was stable over the 10 years (variation between 5.79 AND 5.90 years). The gross margin was on average €24.80/100 kg milk (STD = 4.67), with the lowest value in year 2009 and the highest value in year 2013. Gross margin was not significantly associated with age of culled cows and lifetime milk production of culled cows. Variance in longevity between herds was large (STD = 0.78 years) but herds with a higher longevity did not perform economically better nor worse than herds resulting in lower longevity. This indicates that, within current practice, there is potential for improving longevity in order to meet society's concerns on animal welfare and environmental pollution, without affecting the economic performance of the herd.
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- 2021
28. The effect of bovine viral diarrhea virus introduction on milk production of Dutch dairy herds
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Yue, Xiaomei, Steeneveld, Wilma, van der Voort, Mariska, van Schaik, Gerdien, Vernooij, Johannes C.M., van Duijn, Linda, Veldhuis, Anouk M.B., Hogeveen, Henk, FAH Evidence based Veterinary Medicine, dFAH AVR, FAH veterinaire epidemiologie, Dep Gezondheidszorg Landbouwhuisdieren, FAH Evidence based Veterinary Medicine, dFAH AVR, FAH veterinaire epidemiologie, and Dep Gezondheidszorg Landbouwhuisdieren
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Yield (finance) ,viruses ,animal diseases ,Bedrijfseconomie ,WASS ,Biology ,Antibodies, Viral ,Virus ,Herd immunity ,03 medical and health sciences ,bovine viral diarrhea virus introduction ,Animal science ,Milk yield ,Business Economics ,Genetics ,Animals ,control program ,milk production ,Viral diarrhea ,030304 developmental biology ,0303 health sciences ,Diarrhea Viruses, Bovine Viral ,Dairy herds ,0402 animal and dairy science ,virus diseases ,04 agricultural and veterinary sciences ,Milk production ,040201 dairy & animal science ,Dairying ,Milk ,bovine viral diarrhea virus ,Herd ,Bovine Virus Diarrhea-Mucosal Disease ,Cattle ,Female ,Animal Science and Zoology ,Food Science - Abstract
Dairy cows are negatively affected by the introduction of bovine viral diarrhea virus (BVDV), and consequently, produce less milk. Existing literature on potential milk production losses is based on relatively outdated data and hardly evaluates milk production loss in relation to a new BVDV infection in a surveillance system. This study determined the annual and quarterly loss in milk production of BVDV introduction in 3,126 dairy herds participating in the Dutch BVDV-free program between 2007 and 2017. Among these herds, 640 were "breakdown-herds" that obtained and subsequently lost their BVDV-free status during the study period, and 2,486 herds obtained and retained their BVDV-free status during the study period. Milk yields before and after BVDV introduction were compared through annual and quarterly linear mixed models. The fixed variables for both models included herd type (breakdown-herd or free-herd), bovine viral diarrhea status (on an annual and quarterly basis), year, season, and a random herd effect. The dependent variable was the average daily milk yield on the test day. To define the possible BVDV-introduction dates, 4 scenarios were developed. In the default scenario, the date of breakdown (i.e., loss of the BVDV-free status) was assumed as the BVDV-introduction date. For the other 3 scenarios, the BVDV-introduction dates were set at 4, 6, and 9 mo before the date of breakdown, based on the estimated birth date of a persistently infected calf. In the default scenario, the loss in milk yield due to BVDV introduction occurred mainly in the first year after breakdown, with a reduction in yield of 0.08 kg/cow per day compared with the last year before breakdown. For the other 3 scenarios, the greatest yield reduction occurred in the second year after BVDV introduction, with a loss of 0.09, 0.09, and 0.1 kg/cow per day, respectively. For the first 4 quarters after BVDV introduction in the default scenario, milk yield loss was 0.14, 0.09, 0.02, and 0.08 kg/cow per day, respectively. These quarterly results indicated that milk yield loss was greatest in the first quarter after BVDV introduction. Overall, BVDV introduction had a negative, but on average a relatively small, effect on milk yield for herds participating in the BVDV-free program. This study will enable dairy farmers and policymakers to have a clearer understanding of the quantitative milk production effect of BVDV on dairy farms in a control program.
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- 2021
29. Estimating the combined costs of clinical and subclinical ketosis in dairy cows
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Steeneveld, Wilma, Amuta, Paul, van Soest, Felix J.S., Jorritsma, Ruurd, Hogeveen, Henk, FAH Evidence based Veterinary Medicine, dFAH AVR, FAH GZ herkauwer, FAH Evidence based Veterinary Medicine, dFAH AVR, and FAH GZ herkauwer
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Percentile ,Animal Culling ,Physiology ,Economics ,Maternal Health ,Social Sciences ,WASS ,Culling ,Mastitis ,Animal Diseases ,0403 veterinary science ,Endocrinology ,Reproductive Physiology ,Medicine and Health Sciences ,Medicine ,Multidisciplinary ,Simulation and Modeling ,04 agricultural and veterinary sciences ,Veterinary Diagnostics ,Body Fluids ,Dairying ,Milk ,Anatomy ,Research Article ,Risk ,Veterinary Medicine ,Farms ,040301 veterinary sciences ,Science ,Bedrijfseconomie ,Cattle Diseases ,Context (language use) ,Research and Analysis Methods ,Insemination ,Beverages ,Animal science ,Business Economics ,Life Science ,Animals ,Lactation ,Nutrition ,Endocrine Physiology ,business.industry ,0402 animal and dairy science ,Biology and Life Sciences ,Bovine Mastitis ,Ketosis ,Models, Theoretical ,medicine.disease ,040201 dairy & animal science ,Diet ,Fertilization ,Herd ,Women's Health ,Cash flow ,Cattle ,Veterinary Science ,business ,Zoology ,Developmental Biology - Abstract
Clinical ketosis (CK) and subclinical ketosis (SCK) are associated with lower milk production, lower reproductive performance, an increased culling of cows and an increased probability of other disorders. Quantifying the costs related to ketosis will enable veterinarians and farmers to make more informed decisions regarding the prevention and treatment of the disease. The overall aim of this study was to estimate the combined costs of CK and SCK using assumptions and input variables from a typical Dutch context. A herd level dynamic stochastic simulation model was developed, simulating 385 herds with 130 cows each. In the default scenario there was a CK probability of almost 1% and a SCK probability of 11%. The herds under the no risk scenario had no CK and SCK, while the herds under the high-risk scenario had a doubled probability of CK and SCK compared to the default scenario. The results from the simulation model were used to estimate the annual cash flows of the herds, including the costs related to milk production losses, treatment, displaced abomasum, mastitis, calf management, culling and feed, as well as the returns from sales of milk and calves. The difference between the annual net cash flows of farms in the no risk scenario and the default scenario provides the estimate of the herd level costs of ketosis. Average herd level costs of ketosis (CK and SCK combined) were €3,613 per year for a default farm and €7,371 per year for a high-risk farm. The costs for a single CK case were on average €709 (with 5 and 95 percentiles of €64 and €1,196, respectively), while the costs for a single SCK case were on average €150 (with 5 and 95 percentiles of €18 and €422, respectively) for the default farms. The differences in costs between cases occurred due to differences between cases (e.g., cow culled vs cow not culled, getting another disease vs not getting another disease).
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- 2020
30. Production Diseases Reduce the Efficiency of Dairy Production: A Review of the Results, Methods, and Approaches Regarding the Economics of Mastitis
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Hogeveen, Henk, primary, Steeneveld, Wilma, additional, and Wolf, Christopher A., additional
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- 2019
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31. Economic and epidemiological impact of different intervention strategies for clinical contagious mastitis
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Gussmann, Maya, Steeneveld, Wilma, Kirkeby, Carsten, Hogeveen, Henk, Nielen, Mirjam, Farre, Michael, Halasa, Tariq, LS Evidence Based Vet Medicine, dFAH AVR, LS Evidence Based Vet Medicine, and dFAH AVR
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Staphylococcus aureus ,medicine.medical_specialty ,medicine.drug_class ,Denmark ,cow-specific ,Bedrijfseconomie ,Antibiotics ,WASS ,Culling ,03 medical and health sciences ,Business Economics ,Intervention (counseling) ,Internal medicine ,Epidemiology ,Genetics ,medicine ,Animals ,Computer Simulation ,Mastitis, Bovine ,Dairy cattle ,030304 developmental biology ,0303 health sciences ,culling ,treatment ,business.industry ,simulation model ,Incidence (epidemiology) ,0402 animal and dairy science ,food and beverages ,04 agricultural and veterinary sciences ,Staphylococcal Infections ,medicine.disease ,040201 dairy & animal science ,Anti-Bacterial Agents ,Mastitis ,Dairying ,Milk ,Herd ,Cattle ,Female ,Animal Science and Zoology ,business ,Food Science - Abstract
The overall aim of this study was to compare different intervention strategies for clinical intramammary infections (IMI). We conducted a simulation study to represent a Danish dairy cattle herd with IMI caused mostly by Staphylococcus aureus and 9 different intervention strategies for clinical IMI. A standard intervention of 3 d of treatment consisting of intramammary injections for all clinical cases was used. Two of the strategies reflected the use of more antibiotics and 6 strategies reflected cow-specific treatment or culling decisions. For these strategies, we assessed the cost and effectiveness of culling as an IMI intervention. Our results showed that nearly all strategies could reduce the number of IMI cases [e.g., a median of 37 clinical cases with the extended intramammary treatment over 5 d strategy (Basic5) and 30 clinical cases with the cow culled with recovery probability below 50% (Before50)] compared with the standard intervention (median of 42 clinical cases). This happened alongside either increased antibiotic usage (e.g., from a median of 123 treatment days up to 179 treatment days with strategy Basic5) or an increased number of cows culled in relation to IMI (e.g., from a median of 16 up to 24 cows with strategy Before50). Strategies with more antibiotics or reactive culling had a slightly higher net income (e.g., €190,014 median net income with strategy Basic5 or €196,995 with strategy Before50 compared with €187,666 with the standard strategy). This shows that a cow-specific clinical intervention approach can be cost-effective in reducing IMI incidence.
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- 2019
32. Providing probability distributions for the Gram-status of clinical mastitis cases in dairy cattle
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Steeneveld, Wilma, van der Gaag, Linda, Barkema, H.W., Hogeveen, H., Bregt, A., Wolfert, S., Wien, J.E., Lokhorst, C., Sub Decision Support Systems begr 1/1/13, and Decision Support Systems
- Subjects
diagnosis ,dairy ,pathogen - Abstract
Clinical mastitis (CM) can be caused by a wide variety of pathogens and a farmer has to start treatment before the actual causal pathogen is known. Knowing the Gram-status of CM cases would aid in the decision for the most appropriate treatment. By providing a probability distribution for the Gram-status, rather than only providing the most likely Gram-status, the involved uncertainty is visible for a farmer, thereby allowing a more informed treatment decision. The objective of this study was to examine the value of providing probability distributions for the Gram-status of CM cases to a farmer to take a more informed treatment decision. A naive Bayesian network (NBN) based on data from 274 Dutch dairy herds in which the occurrence of CM was recorded over an 18-month period was constructed. The dataset contained 3,534 CM cases, all classified accordingto their Gram-status. Two-third of the dataset was used for the construction and one-third was retained for validation. Information usually available at a dairy farm was included in the NBN under construction (parity, month in lactation, season of the year, quarter position, somatic cell count history and CM history, being sick or not, and color and texture of the milk). For getting insight in the quality of the constructed NBN, the accuracy was determined. The accuracy of classifying CM cases into Gram-positive or Gram-negative pathogens was 73%. Because only CM cases with a high probability for Gram-negative or Gram-positive pathogens will be considered for specific treatment, it was interesting to have a closer look at CM cases with probabilities > 0.90. We foundthat the accuracy of the classification increased with the calculated probability for Gram-negative or Gram-positive pathogens. The probability distributions for the Gram-status provide the farmer with considerable additional information about the most likely Gram-status of a CM case and the uncertainty involved.
- Published
- 2009
33. Bayesian networks for mastitis management on dairy farms
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Steeneveld, Wilma, van der Gaag, Linda, Barkema, H.W., Hogeveen, H., Sub Decision Support Systems begr 1/1/13, and Decision Support Systems
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Business Economics ,Bedrijfseconomie ,Life Science ,WASS ,Research Institute for Animal Husbandry ,Praktijkonderzoek Veehouderij - Abstract
This manuscript presents the idea of providing dairy farmers with probability distributions to support decisions on mastitis management and illustrates its feasibility by two applications. Naive Bayesian networks were developed for both applications. The networks in the first application were used to compute probability distributions to support decisions on which cows from a mastitis alert list generated by detection sensors in an automatic milking system should be visually inspected for clinical mastitis. The computed probability distribution allows farmers to interpret the uncertainty in an alert. The network in the second application was used to compute probability distributions to support treatment decisions for clinical mastitis cases. The computed probability distribution allows for distinguishing a situation in which a single pathogen has a high probability from the situation where two or more pathogens have almost equal probabilities. The first situation would support the choice for a pathogen-specific treatment.
- Published
- 2009
34. The average culling rate of Dutch dairy herds over the years 2007 to 2010 and its association with herd reproduction, performance and health
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Nor, Norhariani Mohd, primary, Steeneveld, Wilma, additional, and Hogeveen, Henk, additional
- Published
- 2013
- Full Text
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35. Sensors and Clinical Mastitis—The Quest for the Perfect Alert
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Hogeveen, Henk, primary, Kamphuis, Claudia, additional, Steeneveld, Wilma, additional, and Mollenhorst, Herman, additional
- Published
- 2010
- Full Text
- View/download PDF
36. Stochastic modelling to assess economic effects of treatment of chronic subclinical mastitis caused by Streptococcus uberis
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Steeneveld, Wilma, primary, Swinkels, Jantijn, additional, and Hogeveen, Henk, additional
- Published
- 2007
- Full Text
- View/download PDF
37. The average culling rate of Dutch dairy herds over the years 2007 to 2010 and its association with herd reproduction, performance and health.
- Author
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Nor, Norhariani Mohd, Steeneveld, Wilma, and Hogeveen, Henk
- Subjects
CULLING of dairy cattle ,CATTLE herding ,CATTLE reproduction ,HEALTH of cattle ,PERFORMANCE evaluation ,SOMATIC cells - Abstract
Optimising the number of replacement heifers needed will have positive economic and environmental consequences on herds that rear their own young stock. The number of heifers needed to be kept is closely related with the number of culled dairy cows in the herd. This study therefore looked at the variation that exists in culling rate and herd level factors associated with it. A dataset from 1903 dairy herds available included information at animal level (dates of culling, slaughter/death) and herd level (characteristics of reproduction, performance, health) over the years 2007 to 2010. The average culling rate for slaughter/death was used and was defined for each year as percentage of the herd size that died within 30 d after they were culled. The analysis of the association between average culling rate for slaughter/death and the characteristics of the herd was performed using a mixed model. The results showed that the average culling rate for slaughter/death was 25·4% and varied between 23% (2007) and 28% (2010). More than 70% of the herds have an average culling rate for slaughter/death of less than 30%, showing that there is room for lowering the average culling rate for slaughter/death. A higher average culling rate for slaughter/death is associated with a longer average calving interval, a higher average 305-d protein production, a higher average somatic cell count (SCC), a higher percentage of new high SCC, a more than 5% decrease in herd size, and herds that bought more than 1% of animals per year. A lower average culling rate for slaughter/death is associated with a longer average age, herds that bought less than 1% of animals per year and a more than 5% increase in herd size. In conclusion, the average culling rate for slaughter/death is associated with fertility, udder health and openness of the herd. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
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38. Templates to classify progesterone profiles, built using real-time milk progesterone measurements
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Derks, M., Blavy, Pierre, Höglund, Johanna, Friggens, Nic, Kamphuis, Claudia, and Steeneveld, Wilma
- Published
- 2016
39. Tool for assessing the intervention effect on milk production in an evolutionary operation setup
- Author
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Stygar, Anna Helena, Krogh, Mogens Agerbo, Østergaard, Søren, Kristensen, Anders Ringgaard, Kamphuis, Claudia, and Steeneveld, Wilma
- Abstract
Modern dairy herds resemble factories. Cows, organized in production units, are manufacturing milk from many components (e.g. concentrates, silage). However, both production units and components can greatly differ between each other. Therefore, production optimization based on general recommendations might be inefficient. Instead, as in manufacturing industry, decision support could be based on systematic experimentation within ongoing production system. This concept, known as Evolutionary Operations (EVOP), is based on small changes to the production system. However, a challenge here is lack of a tool which would allow a farmer to assess how small changes, for example in feeding, influence productivity. The objective of this study was to construct a multivariate dynamic linear model (DLM) to assess the intervention effect on milk production.The DLM was built to account for intervention at individual and herd level. It consisted of an observation and a system equation. The observation equation links the observations to parameters describing the herd (lactation curve), individual cows and an intervention effect. The system equation expresses how the parameters may change over time. The lactation curve was modeled by two linear expressions and was parameterized using: milk yield 60 days after calving, slope over the first 60 days in milk and slope after 60 days in milk. The variance components of the DLM were estimated using a maximum likelihood method. The application of the model was demonstrated on a field experiment in a commercial herd with 4 automatic milking systems (AMS). The herd was split into 2 groups based on the AMS. The experiment relied on two steps. The first step was to reduce the feed energy given to cows in the AMS and instead supply the feed energy to the cows at the feed bunk. The second step was to reduce the feed energy given in two of the four AMS. The DLM presented here was successful in providing estimates of the effects on milk yield of change in feed energy given to the cows in the AMS. The DLM results support the sequential tactical decisions within EVOP and are readily applicable in other herd experiments.
- Published
- 2016
40. Economics of young stock rearing decisions on Dutch dairy farms
- Author
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Mohd Nor, N.B., dFAH AVR, LS Theoretische Epidemiologie, Stegeman, Arjan, Hogeveen, H., and Steeneveld, Wilma
- Subjects
culling ,calf diseases ,young stock ,simulation model ,dairy ,economics ,heifer - Abstract
The increasing intensiveness of agriculture has contributed to environmental pollution through a higher production of waste materials. The environmental and economic pressures mean that it is nowadays important that milk is produced in a more sustainable way. The young stock rearing enterprise also contributes to the sustainability of dairy farming. For example, decisions about the number of young stock to retain on the farm have consequences for the amount of waste produced. A more sustainable young stock rearing enterprise can be achieved if the optimal decisions are taken during the rearing period. However, these decisions are very complex because many different factors are involved. For instance, retaining too few young stocks can result in not enough replacement heifers to replace culled dairy cows, and a shorter rearing period might negatively influence the future performance of dairy cows. Therefore, it is necessary to obtain insight into these decisions. The general objective of this thesis was to provide insight in the economic consequences of the decisions taken during young stock rearing. For this thesis, we focused on 2 important decisions that are directly related to the number of animals on the farm, and therefore to waste production. These decisions are about the first calving age and the number of 2-week-old heifer calves to be retained. Results of data analysis on 8,454 heifers showed that the first calving age can be lowered by starting inseminations earlier. However, earlier inseminations need to be accompanied by an adjustment of the rearing management to ensure sufficient development. Otherwise, earlier inseminations will lead to a lower milk production. These findings showed that an economic optimum exists between rearing costs and the first calving age. The decision about the optimal number of 2-week-old heifer calves to be retained is analysed using a stochastic herd level simulation model. In that model, the optimal percentage of 2-week-old heifer calves to be retained was defined as the percentage of heifer calves which minimized the average net cost of rearing replacement heifers. Inputs for this model were based on literature, expert opinion and authors’ expertise. In addition, inputs that are important but not readily available for Dutch circumstances were also studied. These were the cost of rearing and the culling rate of dairy cows. The cost of rearing was estimated using a cow level simulation model. The culling rate of dairy cows was studied by using a multivariate regression analysis. The results on costs and culling rate were used as inputs in the stochastic herd level simulation model. Results of the model showed that in a 100-cow herd, the optimal retention of 2-week-old heifer calves in default scenario was 73%. The net cost of rearing when retaining the optimal percentage of heifer calves was estimated at €40,939 per herd per year. This amount is 6.5% lower compared to when a farm retain all heifer calves. In conclusion, for Dutch dairy farms, it is economically optimal not to retain all heifer calves.
- Published
- 2015
41. The effect of new bovine viral diarrhea virus introduction on somatic cell count, calving interval, culling, and calf mortality of dairy herds in the Dutch bovine viral diarrhea virus-free program.
- Author
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Yue X, van der Voort M, Steeneveld W, van Schaik G, Vernooij JCM, van Duijn L, and Hogeveen H
- Subjects
- Animals, Cattle, Cell Count veterinary, Diarrhea veterinary, Female, Bovine Virus Diarrhea-Mucosal Disease prevention & control, Cattle Diseases, Diarrhea Virus 1, Bovine Viral, Diarrhea Viruses, Bovine Viral
- Abstract
Bovine viral diarrhea virus (BVDV) infection has a major effect on the health of cows and consequently on herd performance. Many countries have implemented control or eradication programs to mitigate BVDV infection and its negative effects. These negative effects of BVDV infection on dairy herds are well documented, but there is much less information about the effects of new introduction of BVDV on dairy herds already participating in a BVDV control program. The objective of our study was to investigate the effect of a new BVDV introduction in BVDV-free herds participating in the Dutch BVDV-free program on herd performance. Longitudinal herd-level surveillance data were combined with herd information data to create 4 unique data sets, including a monthly test-day somatic cell count (SCC) data set, annual calving interval (CIV) and culling risk (CR) data sets, and a quarterly calf mortality rate (CMR) data set. Each database contained 2 types of herds: herds that remained BVDV free during the whole study period (defined as free herds), and herds that lost their BVDV-free status during the study period (defined as breakdown herds). The date of losing the BVDV-free status was defined as breakdown date. To compare breakdown herds with free herds, a random breakdown date was artificially generated for free herds by simple random sampling from the distribution of the breakdown month of the breakdown herds. The SCC and CIV before and after a new introduction of BVDV were compared through linear mixed-effects models with a Gaussian distribution, and the CR and CMR were modeled using a negative binomial distribution in generalized linear mixed-effects models. The explanatory variables for all models included herd type, BVDV status, year, and a random herd effect. Herd size was included as an explanatory variable in the SCC, CIV, and CMR model. Season was included as an explanatory variable in the SCC and CMR model. Results showed that free herds have lower SCC, CR, CMR, and shorter CIV than the breakdown herds. Within the breakdown herds, the new BVDV introduction affected the SCC and CMR. In the year after BVDV introduction, the SCC was higher than that in the year before BVDV introduction, with a factor of 1.011 [2.5th to 97.5th percentile (95% PCTL): 1.002, 1.020]. Compared with the year before BVDV breakdown, the CMR in the year of breakdown and the year after breakdown was higher, with factors of 1.170 (95% PCTL: 1.120; 1.218) and 1.096 (95% PCTL: 1.048; 1.153), respectively. This study reveals that a new introduction of BVDV had a negative but on average relatively small effect on herd performance in herds participating in a BVDV control program., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)
- Published
- 2021
- Full Text
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42. The effect of bovine viral diarrhea virus introduction on milk production of Dutch dairy herds.
- Author
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Yue X, Steeneveld W, van der Voort M, van Schaik G, Vernooij JCM, van Duijn L, Veldhuis AMB, and Hogeveen H
- Subjects
- Animals, Antibodies, Viral, Bovine Virus Diarrhea-Mucosal Disease epidemiology, Cattle, Dairying, Female, Bovine Virus Diarrhea-Mucosal Disease physiopathology, Diarrhea Viruses, Bovine Viral, Milk
- Abstract
Dairy cows are negatively affected by the introduction of bovine viral diarrhea virus (BVDV), and consequently, produce less milk. Existing literature on potential milk production losses is based on relatively outdated data and hardly evaluates milk production loss in relation to a new BVDV infection in a surveillance system. This study determined the annual and quarterly loss in milk production of BVDV introduction in 3,126 dairy herds participating in the Dutch BVDV-free program between 2007 and 2017. Among these herds, 640 were "breakdown-herds" that obtained and subsequently lost their BVDV-free status during the study period, and 2,486 herds obtained and retained their BVDV-free status during the study period. Milk yields before and after BVDV introduction were compared through annual and quarterly linear mixed models. The fixed variables for both models included herd type (breakdown-herd or free-herd), bovine viral diarrhea status (on an annual and quarterly basis), year, season, and a random herd effect. The dependent variable was the average daily milk yield on the test day. To define the possible BVDV-introduction dates, 4 scenarios were developed. In the default scenario, the date of breakdown (i.e., loss of the BVDV-free status) was assumed as the BVDV-introduction date. For the other 3 scenarios, the BVDV-introduction dates were set at 4, 6, and 9 mo before the date of breakdown, based on the estimated birth date of a persistently infected calf. In the default scenario, the loss in milk yield due to BVDV introduction occurred mainly in the first year after breakdown, with a reduction in yield of 0.08 kg/cow per day compared with the last year before breakdown. For the other 3 scenarios, the greatest yield reduction occurred in the second year after BVDV introduction, with a loss of 0.09, 0.09, and 0.1 kg/cow per day, respectively. For the first 4 quarters after BVDV introduction in the default scenario, milk yield loss was 0.14, 0.09, 0.02, and 0.08 kg/cow per day, respectively. These quarterly results indicated that milk yield loss was greatest in the first quarter after BVDV introduction. Overall, BVDV introduction had a negative, but on average a relatively small, effect on milk yield for herds participating in the BVDV-free program. This study will enable dairy farmers and policymakers to have a clearer understanding of the quantitative milk production effect of BVDV on dairy farms in a control program., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)
- Published
- 2021
- Full Text
- View/download PDF
43. Economic and epidemiological impact of different intervention strategies for clinical contagious mastitis.
- Author
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Gussmann M, Steeneveld W, Kirkeby C, Hogeveen H, Nielen M, Farre M, and Halasa T
- Subjects
- Animals, Anti-Bacterial Agents economics, Anti-Bacterial Agents therapeutic use, Cattle, Computer Simulation, Dairying economics, Denmark epidemiology, Female, Milk, Staphylococcal Infections economics, Staphylococcal Infections epidemiology, Staphylococcus aureus, Mastitis, Bovine economics, Mastitis, Bovine epidemiology, Staphylococcal Infections veterinary
- Abstract
The overall aim of this study was to compare different intervention strategies for clinical intramammary infections (IMI). We conducted a simulation study to represent a Danish dairy cattle herd with IMI caused mostly by Staphylococcus aureus and 9 different intervention strategies for clinical IMI. A standard intervention of 3 d of treatment consisting of intramammary injections for all clinical cases was used. Two of the strategies reflected the use of more antibiotics and 6 strategies reflected cow-specific treatment or culling decisions. For these strategies, we assessed the cost and effectiveness of culling as an IMI intervention. Our results showed that nearly all strategies could reduce the number of IMI cases [e.g., a median of 37 clinical cases with the extended intramammary treatment over 5 d strategy (Basic5) and 30 clinical cases with the cow culled with recovery probability below 50% (Before50)] compared with the standard intervention (median of 42 clinical cases). This happened alongside either increased antibiotic usage (e.g., from a median of 123 treatment days up to 179 treatment days with strategy Basic5) or an increased number of cows culled in relation to IMI (e.g., from a median of 16 up to 24 cows with strategy Before50). Strategies with more antibiotics or reactive culling had a slightly higher net income (e.g., €190,014 median net income with strategy Basic5 or €196,995 with strategy Before50 compared with €187,666 with the standard strategy). This shows that a cow-specific clinical intervention approach can be cost-effective in reducing IMI incidence., (© 2019, The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)
- Published
- 2019
- Full Text
- View/download PDF
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