Autor: Sebastian Metz

Economic assessment of cases of disease in dairy cattle using the herd data-based calculation module “Entgangener Ertrag” The company dsp-Agrosoft Gmbh markets a dairy farm management software called Herde. For this software, a module called Entgangener Ertrag is available. According to the company the purpose of the module is the estimation of the influence of diseases and culling rates on the profitability of the dairy farm (dsp-Agrosoft GmbH, 2018). The basic approach is as follows: The user chooses a disease whose economic impact he or she wants to have illustrated. The module then displays two groups of animals next to each other: animals with the diagnosis in question on the one hand and animals without the diagnosis on the other hand. The two groups’ past milk yield, reproductive parameters, cost of stock replacement and cost of cow maintenance are compared. The “Entgangener Ertrag” (loss of revenue) associated with the diagnosis is displayed. The “Entgangener Ertrag” is defined as the difference in economic outcome between the two groups. The analysis of the impact of diseases is, thus, specific to the dairy farm in question. This constitutes an essential difference to strategies that rely on information from the relevant literature in order to assess the impact of diseases. Two screenshots of the user interface are to be found in section 3.2 of this doctoral thesis. Apart from the diagnoses the fat-to-protein ratio (screening for ketotic status) and the somatic cell count (indicator for udder health) can be assessed for their economic significance. The principle of analysis is analogous to the one described above for the diagnoses. For the sake of simplicity in the following description only the terms “diseases” and “diagnoses” are used. In addition, instead of an “Entgangener Ertrag” the effect on the “Income over feedcost” can be assessed. Details on this can be found in section 4.1.5. The subject of this doctoral thesis is the critical discussion of the module described. All the corresponding remarks relate to the version of the software package described in section 3.1. The first research question is whether the module in its current version depicts the effect of a disease on the economic income of the farm in a precise enough manner to constitute a valuable decision-making support when planning investments in disease control and prophylaxis. The second goal of the thesis is to not only identify possible weak points of the module but to also elucidate what changes to the module are to be made in order to refine it with the above-mentioned scenario of application in mind. The mathematical approach of the module is described in detail. Furthermore, the results of the application of the module to real life data are described. The data stem from the backup files of the Herde-software of two German dairy farms. Subsequently, a detailed discussion of the module is undertaken, also with reference to the relevant literature on the economic effects of diseases on the parameters in question. Both fundamental conceptual problems as well as “minor technical shortcomings” in the programming are identified. Suggestions for improvement are made. When designing an economic decision-making support tool, methodical precision must be weighed against practicality and usability. In view of this, it must be taken into consideration that the identified weak points of the module in its current form differ in relevance for its overall assessment. The improvement of the presentation of the effect of a disease on the milk yield is identified as a priority in the future further development of the module. Because of the particular significance of this aspect, both the underlying problem and a possible approach to its resolution are described in some detail using the example of the diagnosis sole ulcer: Assuming that animals that, for genetic reasons, are especially high producing have an especially strong predisposition for sole ulcers (because of an especially strong mobilization of adipose tissue and therefore an especially thin digital cushion; see section 5.1.1) it must be deduced that the diagnosis sole ulcer constitutes an indirect selection criterion for animals with a high potential milk yield. It should then come as no surprise that – at least for the time period analysed here – in both dairy farms this diagnosis is largely associated with a higher milk yield. The chances are that this can be explained by a situation where the disease does in fact reduce the milk yield of the effected animal (painful standing, therefore reduced feed intake and so on) but only to an extent where the average yield of these animals is still above that of animals without sole ulcer. The actual reduction in milk yield of the diseased animal in the sense of a negative deviation from its potential – and therefore the effect of the disease – cannot be deduced. A possible approach towards an improvement of the presentation is the division of the animals into productivity groups based on their potential milk yield. Animals with/without the diagnosis could then be compared within the same productivity group. The milk yield in previous lactations could be used as an indicator for the potential yield of an animal. Some other approaches are also outlined (see section 5.1.1). The particular significance of the presentation of the association between disease and milk yield is, on the one hand, due to the large share of the milk yield in the “Entgangener Ertrag.” On the other hand, in both dairy farms analysed here the diagnosis sole ulcer is largely associated with a considerably lower culling rate. This is probably owing to a protective effect of the high milk yield rather than a direct (positive) effect of the disease, the protective effect being that the farmer is inclined to keep high yielding animals in the herd rather than culling them. The comparison of animals within the same productivity group could also improve this part of the presentation. There is yet another aspect: in both dairy farms the diagnosis sole ulcer is largely associated with a lower reproductive performance – especially when looking at the calving interval. In this case it is conceivable that this is at least in part due to a more or less direct effect of the disease. On the other hand, it cannot be ruled out that the high milk yield per se is associated with a low reproductive performance. The question of whether such an association exists is the subject of some controversy in the literature (see section 5.1.1). If it does in fact exist, then also this part of the presentation could be improved by comparing animals with/without diagnosis within the same productivity group. It is important to note, that the reasoning described above is not only valid for the diagnosis sole ulcer but rather for any disease whose incidence is associated with the level of the potential milk yield. Further room for improvement was identified in the following areas. The individual points are discussed in detail elsewhere in this thesis and therefore only mentioned briefly here: • Further aspects of the creation of the comparison groups with/without diagnosis (apart from the division into productivity groups), especially bias of the results due to nonconsideration of diagnoses other than the one chosen for analysis, are discussed. • Calculation of the cost of stock replacement in the herd: currently only those payments that are the immediate result of the culling of an animal and its replacement by a new one are considered. The change in future payments due to the change in the herd structure (net present value approach) have up until now not been taken into account. • Currently the assumed cost of cow maintenance stay the same throughout the whole lactation. The possibility of a differentiation specific to the farm in question should be considered. • The calculation of the economic effect of diseases is currently only undertaken in retrospect. Possible approaches towards also taking into consideration future effects are outlined briefly. • Associations between diseases and the two reproductive parameters (calving interval and number of portions of semen used) are generally considered in the calculation of the “Entgangener Ertrag”. This is true even for cases of disease appearing after the beginning of pregnancy. This aspect of the presentation should be reviewed. What is more, the costs of semen are systematically exaggerated due to the presumption of costs for animals that were de facto not inseminated. Both points can readily be rectified by changing the programming of the module. • In the current definition of the amount of milk it is not taken into consideration whether the milk is marketable; this means milk discarded due to the use of antibiotics is indiscriminately considered. It would be preferable to focus the presentation on marketable milk. • Various cost categories remain unconsidered in the calculus of the module until now. Weighing methodical effort on the one hand against the significance for the overall result on the other, the inclusion of treatment costs seems particularly worth considering. • Even in situations with zero cases of the diagnosis chosen for analysis a “Entgangener Ertrag” is displayed. This should be reviewed. • When the fat-to-protein ratio (screening for ketotic status) is chosen for analysis the differentiating criterion is > 1.5. The results of a recent clinical study suggest that a lower cut-off point may be more favourable. What is more, there is currently potential for misunderstanding regarding the user’s selection of the observation period. • A few minor problems or rather potential for misunderstanding in the user interface are outlined. • Alongside the calculation of the “Entgangener Ertrag” the indication of the farm-specific marginal revenue of different courses of action in the field of disease control and prophylaxis would be useful. This would constitute another decision-making support for the user of the module. In the course of a future iterative improvement of the module an assessment of the practical relevance for the functionality of the module should be undertaken for each of the points made above. A comparison of the results calculated by the respective level of development with results from the relevant literature can contribute to this. The overview of the relevant literature found in this doctoral thesis can be consulted to this end. Regarding the research questions stated above the conclusions drawn can be summarised as follows: When using the module as a decision-making support while planning investments in disease control and prophylaxis the presented “Entgangener Ertrag” must be interpreted with prudence. No universally valid statement regarding the precision of the presentation of the effect of a disease on the economic income of the farm can be made. Rather, the precision of the presentation depends decisively on the question whether the incidence of the disease chosen for analysis is associated with the potential milk yield. For the group of diseases where such an association is present it is to be expected to an especially high extent that the module does in fact depict the association between disease and average milk yield but not the actual effect of the disease. Specifically regarding the above-mentioned group of diseases, this results in a substantial limitation in the applicability of the results of the module as a direct decision-making support in the above-mentioned scenario. As described above, this conclusion results to a large extent from the generally large share of the milk yield in the “Entgangener Ertrag” but also from a presumed biasing effect on the presentation of other parameters. More details regarding these aspects and possible approaches for further improvement of the module can be found in section 5.1. Within the scope of this doctoral thesis a number of further fundamental conceptual problems of the module as well as “minor technical shortcomings” in the programming were identified, which generally deserve attention – independently from the characteristics of the disease chosen for analysis. Suggestions for improvement were made. The relevance of the individual aspects for the overall functionality of the module cannot be assessed in an objective fashion. Rather, this is up to the user to decide and will ultimately depend on his or her requirements for the module. The necessary balance between methodical precision on the one hand and practicality and usability on the other hand was discussed in section 5.1. It is crucial that the user know about the explanatory power of the module results – and about its limits – and that he or she, thus, be in a position to make an informed decision about whether or not the module results are of value in view of the particular goal of itsapplication. The observations made in this doctoral thesis can be used to both inform the user to that effect as well as to serve as a basis for a possible – and if necessary gradual − methodical improvement of the module.