Associations between the time of conception and the shape of the lactation curve in early lactation in Norwegian dairy cattle

<p>Abstract</p> <p>Background</p> <p>This study was carried out to determine if an association exists between the shape of the lactation curve before it is influenced by the event of conception and the time from calving to conception in Norwegian dairy cattle. Lactation curves of Norwegian Red cows during 5 to 42 days in milk (DIM) were compared between cows conceiving between 43 and 93 DIM and cows conceiving after 93 DIM.</p> <p>Methods</p> <p>Data from 23,049 cows, represented by one lactation each, with 219,538 monthly test days were extracted from the Norwegian Dairy Herd Recording System, which represents 97% of all Norwegian dairy cows. Besides veterinary treatments, these records also included information on daily milk yield at monthly test days. The data were stratified by parity groups (1, 2, and 3 and higher) and time to conception periods (43-93 DIM and >93 DIM). The sample was selected using the following selection criteria: conception later than 42 DIM, calving season July to September, no records of veterinary treatment and the level of energy fed as concentrates between 8.69 and 12.83 MJ. The shape of the lactation curves were parameterized using a modified Wilmink-model in a mixed model analysis. Differences in the parameters of the lactation curves with different conception times were evaluated using confidence intervals.</p> <p>Results</p> <p>Lactation curves characterized by a low intercept and a steep ascending slope and a steep descending slope were associated with early conception across all parities. The peak milk yield was not associated with time of conception.</p> <p>Conclusions</p> <p>A practical application of the study results is the use of the shape of the lactation curve in future herd management. Groups of cows with impaired reproductive performance may be identified due to an unfavorable shape of the lactation curve. Monitoring lactation curves and adjusting the feeding strategy to adjust yield therefore may be useful for the improvement of reproductive performance at herd level.</p

Mastitis risk effect on the economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

The benefits and efficacy of control programs for herds infected with Mycobacterium avium subsp. paratuberculosis (MAP) have been investigated under various contexts. However, most previous research investigated paratuberculosis control programs in isolation, without modeling the potential association with other dairy diseases. This paper evaluated the benefits of MAP control programs when the herd is also affected by mastitis, a common disease causing the largest losses in dairy production. The effect of typically suggested MAP controls were estimated under the assumption that MAP infection increased the rate of clinical mastitis. We evaluated one hundred twenty three control strategies comprising various combinations of testing, culling, and hygiene, and found that the association of paratuberculosis with mastitis alters the ranking of specific MAP control programs, but only slightly alters the cost-benefit difference of particular MAP control components, as measured by the distribution of net present value of a representative U.S. dairy operation. In particular, although testing and culling for MAP resulted in a reduction in MAP incidence, that control led to lower net present value (NPV) per cow. When testing was used, ELISA was more economically beneficial than alternative testing regimes, especially if mastitis was explicitly modeled as more likely in MAP-infected animals, but ELISA testing was only significantly associated with higher NPV if mastitis was not included in the model at all. Additional hygiene was associated with a lower NPV per cow, although it lowered MAP prevalence. Overall, the addition of an increased risk of mastitis in MAP-infected animals did not change model recommendations as much as failing to consider

A data-driven individual-based model of infectious disease in livestock operation : A validation study for paratuberculosis

Chronic livestock diseases cause large financial loss and affect animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform the farmer’s decisions, but even successful control pro-grammes do by no means assure elimination. Mathematical models provide opportunities to test different control and elimination options rather than implementing them in real herds, but these models require robust parameter estimation and validation. Fitting these models to data is a difficult task due to heterogeneities in livestock processes. In this paper, we develop an infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and causes significant economic losses to the dairy industry. These economic effects are particularly important motivations in the control and elimination of MAP. In this framework, an individual-based model (IBM) of a dairy herd was built and MAP infection dynamics was integrated. Once the model produced realistic dynamics of MAP infection, we implemented an evaluation method by fitting it to data from three dairy herds from the Northeast region of the US. The model fitting exercises used least-squares and parameter space searching methods to obtain the best-fitted values of selected parameters. The best set of parameters were used to model the effect of interventions. The results show that the presented model can complement real herd statistics where the intervention strategies suggest a reduction in MAP prevalence without elimination. Overall, this research not only provides a complete model for MAP infection dynamics in a dairy herd but also offers a method for estimating parameters by fitting IBM models

A data-driven individual-based model of infectious disease in livestock operation : A validation study for paratuberculosis

Chronic livestock diseases cause large financial loss and affect animal health and welfare. Controlling these diseases mostly requires precise information on both individual animal and population dynamics to inform the farmer’s decisions, but even successful control pro-grammes do by no means assure elimination. Mathematical models provide opportunities to test different control and elimination options rather than implementing them in real herds, but these models require robust parameter estimation and validation. Fitting these models to data is a difficult task due to heterogeneities in livestock processes. In this paper, we develop an infectious disease modeling framework for a livestock disease (paratuberculosis) that is caused by Mycobacterium avium subsp. paratuberculosis (MAP). Infection with MAP leads to reduced milk production, pregnancy rates, and slaughter value and increased culling rates in cattle and causes significant economic losses to the dairy industry. These economic effects are particularly important motivations in the control and elimination of MAP. In this framework, an individual-based model (IBM) of a dairy herd was built and MAP infection dynamics was integrated. Once the model produced realistic dynamics of MAP infection, we implemented an evaluation method by fitting it to data from three dairy herds from the Northeast region of the US. The model fitting exercises used least-squares and parameter space searching methods to obtain the best-fitted values of selected parameters. The best set of parameters were used to model the effect of interventions. The results show that the presented model can complement real herd statistics where the intervention strategies suggest a reduction in MAP prevalence without elimination. Overall, this research not only provides a complete model for MAP infection dynamics in a dairy herd but also offers a method for estimating parameters by fitting IBM models.</p

The risk and control of Salmonella outbreaks in calf-raising operations: a mathematical modeling approach

Salmonellosis in calves has economic and welfare implications, and serves as a potential source of human infections. Our objectives were to assess the risk of Salmonella spread following its introduction into a herd of pre-weaned calves and to evaluate the efficacy of control strategies to prevent and control outbreaks. To meet these objectives, we developed a model of Salmonella transmission within a pre-weaned group of calves based on a well documented outbreak of salmonellosis in a calf-raising operation and other literature. Intervention scenarios were evaluated in both deterministic and stochastic versions of the model. While the basic reproduction number ($R_0$) was estimated to be 2.4, simulation analysis showed that more than 60% of the invasions failed after the introduction of a single index case. With repeated introduction of index cases, the probability of Salmonella spread was close to 1, and the tested control strategies were insufficient to prevent transmission within the group. The most effective strategies to control ongoing outbreaks were to completely close the rearing operation to incoming calves, to increase the proportion of admitted calves that were immunized ($>75$%), and to assign personnel and equipment to groups of calves

Agar disk diffusion and automated microbroth dilution produce similar antimicrobial susceptibility testing results for salmonella serotypes Newport, Typhimurium, and 4,5,12:i-, but differ in economic cost

Data generated using different antimicrobial testing methods often have to be combined, but the equivalence of such results is difficult to assess. Here we compared two commonly used antimicrobial susceptibility testing methods, automated microbroth dilution and agar disk diffusion, for 8 common drugs, using 222 Salmonella isolates of serotypes Newport, Typhimurium, and 4,5,12:i-, which had been isolated from clinical salmonellosis cases among cattle and humans. Isolate classification corresponded well between tests, with 95% overall category agreement. Test results were significantly negatively correlated, and Spearman's correlation coefficients ranged from -0.98 to -0.38. Using Cox's proportional hazards model we determined that for most drugs, a 1mm increase in zone diameter resulted in an estimated 20%-40% increase in the hazard of growth inhibition. However, additional parameters such as isolation year or serotype often impacted the hazard of growth inhibition as well. Comparison of economical feasibility showed that agar disk diffusion is clearly more cost-effective if the average sample throughput is small but that both methods are comparable at high sample throughput. In conclusion, for the Salmonella serotypes and antimicrobial drugs analyzed here, antimicrobial susceptibility data generated based on either test are qualitatively very comparable, and the current published break points for both methods are in excellent agreement. Economic feasibility clearly depends on the specific laboratory settings, and disk diffusion might be an attractive alternative for certain applications such as surveillance studies

Agar Disk Diffusion and Automated Microbroth Dilution Produce Similar Antimicrobial Susceptibility Testing Results for Salmonella Serotypes Newport, Typhimurium, and 4,5,12:i-, But Differ in Economic Cost

Data generated using different antimicrobial testing methods often have to be combined, but the equivalence of such results is difficult to assess. Here we compared two commonly used antimicrobial susceptibility testing methods, automated microbroth dilution and agar disk diffusion, for 8 common drugs, using 222 Salmonella isolates of serotypes Newport, Typhimurium, and 4,5,12:i-, which had been isolated from clinical salmonellosis cases among cattle and humans. Isolate classification corresponded well between tests, with 95% overall category agreement. Test results were significantly negatively correlated, and Spearman's correlation coefficients ranged from −0.98 to −0.38. Using Cox's proportional hazards model we determined that for most drugs, a 1 mm increase in zone diameter resulted in an estimated 20%–40% increase in the hazard of growth inhibition. However, additional parameters such as isolation year or serotype often impacted the hazard of growth inhibition as well. Comparison of economical feasibility showed that agar disk diffusion is clearly more cost-effective if the average sample throughput is small but that both methods are comparable at high sample throughput. In conclusion, for the Salmonella serotypes and antimicrobial drugs analyzed here, antimicrobial susceptibility data generated based on either test are qualitatively very comparable, and the current published break points for both methods are in excellent agreement. Economic feasibility clearly depends on the specific laboratory settings, and disk diffusion might be an attractive alternative for certain applications such as surveillance studies