Analysis of associations among diseases in French dairy cows in two consecutive lactations

Invited review: Incidence, risk factors, and effects of clinical mastitis recurrence in dairy cows

Clinical mastitis (CM) is one of the most frequent and costly diseases in dairy cows. A frustrating aspect of CM is its recurrent nature. This review was conducted to synthesize knowledge on risk of repeated cases of CM, effects of recurrent CM cases, and risk factors for CM recurrence. A systematic review methodology was used to identify articles for this narrative review. Searches were performed to identify relevant scientific literature published after 1989 in English or French from 2 databases (PubMed and CAB Abstracts) and 1 search platform (Web of Science). Fifty-seven manuscripts were selected for qualitative synthesis according to the inclusion criteria. Among the 57 manuscripts selected in this review, a description of CM recurrence, its risk factors, and effects were investigated and reported in 33, 37, and 19 selected manuscripts, respectively. Meta-analysis and meta-regression analyses were used to compute risk ratio comparing risk of CM in cows that already had 1 CM event in the current lactation with risk of CM in healthy cows. For these analyses, 9 manuscripts that reported the total number of lactations followed and the number of lactations with ≤1 and ≤2 CM cases were used. When summarizing results from studies requiring ≥5 d between CM events to consider a CM event as a new case, we observed no significant change in CM susceptibility following a first CM case (risk ratio: 0.99; 95% confidence interval: 0.86-1.14). However, for studies using a more liberal CM recurrence definition (i.e., only 24 h between CM events to consider new CM cases), we observed a 1.54 times greater CM risk (95% confidence interval: 1.20-1.97) for cows that already had 1 CM event in the current lactation compared with healthy cows. The most important risk factors for CM recurrence were parity (i.e., higher risk in older cows), a higher milk production, pathogen species involved in the preceding case, and whether a bacteriological cure was observed following the preceding case. The most important effects of recurrent CM were the milk yield reduction following a recurrent CM case, which was reported to be similar to that of the first CM case, and the increased risk of culling and mortality, which were reported to surpass those of first CM cases.

A stochastic model simulating pathogen-specific mastitis control in a dairy herd

The objective of this study was to develop a model simulating mastitis control in dairy herds and to investigate how sensitive the model is when varying the effect parameters according to the uncertainty. The model simulates 9 pathogen-specific mastitis types, each of which can be subclinical or clinical. The clinical cases can be 1 of 4 severities defined according to the effect of the mastitis case: mild, moderate, severe, and permanent effect. The risk factors include lactation stage, parity, yield level, previous diseases, season, and contagious spread of the infection from herd mates. Occurrence of mastitis is modeled to have direct effects on feed intake, body weight, milk yield, somatic cell count in the milk, subsequent mastitis cases within the cow and in herd mates, voluntary and involuntary culling, mortality, and milk withdrawal. Thirty-five scenarios were simulated to study model behavior and model sensitivity. The consequences per cow/yr of mastitis in the default simulated herd included 0.42 clinical mastitis occurrences, 0.56 subclinical mastitis occurrences, loss of 385-kg milk yield, a 1.3% reduced feed intake, 61-kg milk withdrawal and 146 in reduced economic net return. Based on scenarios demonstrating model behavior and sensitivity analysis, the model appears to produce valid consequences of mastitis control strategies. Representation of the effect of subclinical mastitis and of variation in mastitis severity was concluded in this study to be important when modeling mastitis economics in a dairy herd. The model offers the opportunity to study the long-term herd specific effects of a wide range of control strategies against mastitis.

A stochastic model simulating milk fever in a dairy herd

A simulation model was developed to evaluate the long-term effect of control strategies against milk fever (MF); here, we present the base model and sensitivity analyses. The representation of the within-herd dynamics was based on the existing SimHerd II model. Because of the relationships between MF and other diseases, the new model (called "SimHerd III") includes diseases common in a dairy herd. The cow level risk factors modelled were: base risk in the herd, parity, milk-yield potential, lactational disease recurrence, disease interrelationships, body condition and season. The diseases include clinical cases of MF, dystocia, downer-cow syndrome, retained placenta, metritis, displaced abomasum, ketosis and mastitis. The effects of diseases were represented by daily milk yield, daily body weight, daily feed intake, risk of stillbirth, conception probability, decision on culling, death and immediate removal. Simulated technical results showed that the herd effects of reduced risk of MF differed according to the reproductive efficiency in the herd. These interactions between reproduction efficiency and the effect of reduced base risk of MF were related to differences in how the simulated herds reacted to the reduction in replacements caused by MF. In the sensitivity analysis, eight potential key parameters were changed to their lowest and highest expected values retrieved from the literature. When measuring the sensitivity on milk production in the herd (as the economically most important technical effect), the model seemed most sensitive to the uncertainty of effect of MF on death risk and MF-recurrence risk.

A mixed-effects time-to-event analysis of the relationship between first-lactation lameness and subsequent lameness in dairy cows in the UK

Data for 611 second-lactation and 251 third-lactation cows were examined using mixed-effects time-to-event models to determine the shape of the hazard, quantify relative risk and estimate herd- and sire-level variation in time to lameness. The semi-parametric Cox and fully parametric Weibull models were suggested from univariable Kaplan-Meier plots. Time to all-lameness, claw-horn lameness and skin lameness were modelled. Explanatory variables were season of current-lactation calving, age at first calving and first-lactation lameness history (whether all-lameness or claw-horn and skin lameness). In mixed-effects models of lactation-2 lameness, previously lame cows had a significantly increased hazard (hazard ratio (HR)=2.0 for all types of lameness and HR=3.2 for claw-horn lameness) compared to those not previously lame. These relationships were less marked in the third lactation. There was little evidence for an effect of age at first calving, whilst possible differences between calving seasons were observed. The hazard function suggested that the rate of lameness was roughly flat across each lactation. Herd-level variation was more evident for infectious foot diseases. The contribution of the sire increased with parity and might be important for sole ulcer and white-line disease.

The relationship between milk yield and the incidence of some diseases in dairy cows

Logistic regression models were used to examine the relationship between milk yield and incidence of certain disorders. Lactations (n = 2197) of 1074 Holstein-Friesian cows from 10 dairies (25 to 146 cows per dairy) in Lower Saxony were studied. The 305-d yield from the previous and current lactations served as the standards for milk yield. Eight disorder complexes were considered: retained placenta, metritis, ovarian cysts, mastitis, claw diseases, milk fever, ketosis, and displaced abomasum. Each disorder complex was modeled separately. In addition to milk yield, the influences of the lactation number, the calving season and the other disorder complexes were examined with the "herd" factor taken into account. A correlation between retained placenta, mastitis, and milk fever to milk yield during the previous lactation was found to be probable and for ketosis and displaced abomasum such a correlation was found to be possible. A connection to the yield in the current lactation was shown for ovarian cysts, claw diseases, and milk fever. No relationship to milk yield existed for metritis. An influence of the lactation number was also demonstrated in various models. Single models allowed a demonstration of the influences of both milk yield and lactation number. Limitations of the model types are discussed.

Relationship between milk somatic-cell counts in the first lactation and clinical mastitis occurrence in the second lactation of French Holstein cows

The relationship between 10 cell-level descriptors in the first lactation and the risk of clinical mastitis in the second lactation was studied in 10205 Holstein cows from 1254 commercial herds using logistic regression. These 10 cell descriptors were based on the mean cell level over the whole first lactation, on the cell level at the beginning or at the end of the first lactation or on the proportion of cell counts below or above given thresholds. Separate analyses were also performed for subsets of herds defined according to their clinical mastitis incidence risk and their lactation mean somatic-cell count (SCC). Odds of clinical mastitis in second lactation was highest (lowest) for high- (low-) yielding cows. All cell descriptors provided consistent results. Lower (higher) mean cell level, higher (lower) proportion of low SCC values, and lower (higher) proportion of high SCC values in the first lactation were associated with a lower (higher) risk of clinical mastitis in the second lactation. The same trends were observed in all subgroups of herds. Cows with the lowest mean SCC in the first lactation had the lowest risk for clinical mastitis in the second lactation. This suggests that selection for decreased SCC may effectively reduce clinical mastitis incidence and that the breeding goal should favor cows with the lowest observed SCC.

A stochastic model simulating the feeding-health-production complex in a dairy herd

A dynamic, stochastic, and mechanistic Monte Carlo model, simulating a dairy herd with focus on the feeding-health-production complex is presented. By specifying biological parameters at cow level and a management strategy at herd level, the model can simulate the technical and economic consequences of scenarios at herd level. The representation of the feeding-health-production complex is aimed to be sufficiently detailed, to include relationships likely to cause significant herd effects, and to be sufficiently simple to enable a feasible parameterization of the model and interpretation of the results from the model. Consequently, diseases are defined as four disease types: two metabolic disease types, an udder disease type, and a reproductive disease type. Risk factors for the diseases were defined as parity, yield capacity, disease recurrence, disease interrelationships, lactation stage, and season. Direct effects of the diseases were defined according to milk yield, feed intake, feed utilization, conception, culling, involuntary removal, and death. Scenarios differing in base risks of milk fever and ketosis, heat detection rate, and culling strategy were simulated for describing the model behavior. Annual milk yield per cow was decreased by increased risk of ketosis and by increased risk of milk fever, even though no direct effect of milk fever on milk yield was modeled at the cow level. The indirect effect from milk fever is a consequence of increased replacement rate (relatively lower milk yield from younger cows). By ignoring the history of milk fever in insemination and replacement decisions, a significantly reduced net income per cow was found in some herds. We concluded that important benefits from using such a herd model are the capability of accounting for herd management factors and the advantage of avoiding to double count the indirect effects from disease, such as increased risk of other diseases, poorer reproduction results, and increased risk of culling and death.

Effects of diseases on test day milk yield and body weight of dairy cows from Danish research herds

The pre- and postdisease interrelationships of energy corrected test day milk yield and body weight of dairy cows caused by mastitis, three reproductive disorders (retained placenta, metritis, cystic ovaries), and seven metabolic disorders (milk fever, ketosis, decreased rumen motility, enteritis, left displaced abomasum, right displaced abomasum, and off feed) were quantified by using mixed models analysis with repeated measures of continuous data. The data were weekly recordings from 4414 lactations collected in three Danish research herds. High milk yield was a risk factor for ketosis and enteritis. Heavier primiparous cows were more likely to contract mastitis. Milk yield was decreased for a disease-specific period for all study diseases except cystic ovaries and right displaced abomasum. Metabolic disorders had a detrimental effect on body weight. The highest weight loss (69 kg) was associated with left displaced abomasum. The persistence of the weight loss differed considerably among study diseases. Almost all weight loss occurred up to and including the initial week after diagnosis, which emphasized the detrimental effect of the subclinical stage. However, weekly measured body weight seemed superior to weekly energy corrected test day milk yield for disease detection only for decreased rumen motility and left displaced abomasum. This study demonstrates the importance of the predisease level for accurate estimation of the loss of milk yield and body weight from disease.

A review of the feeding-health-production complex in a dairy herd

Diseases may be an important link in the relationship between feeding and production in a dairy herd. The low frequency of relevant disorders calls for studies on survey data on a large population. However, this approach suffers from lack of detailed herd feeding data and consequently only few have studied feeding as a risk factor for disease. Therefore, we reviewed information from various studies to integrate what is known of the feeding-health-production complex in a dairy herd. The need for putting together information from different sources, the herd effects, and the fact that the effect of one factor cannot be kept constant for investigation in a real-life dynamic herd call for a conceptual model as a framework for the review. The complexity is minimized to allow the representation of important elements. Within-cow relationships (such as feeding-disease relationships, disease interrelationships, and disease-production relationships) are reviewed specifically for: ketosis, milk fever, displaced abomasum, acidosis, sole ulcers and laminitis, and bloat. The major feeding management factors involved are concentrate feeding (level and how it is provided) and overconditioned cows. Disease interrelationships are important. Generalization of production loss from diseases is complicated due to the variety of estimates and measures used.