Avoiding double counting when deriving economic values through stochastic dairy herd simulation

Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis

An economic simulation was carried out over 183 milk-producing countries to estimate the global economic impacts of 12 dairy cattle diseases and health conditions: mastitis (subclinical and clinical), lameness, paratuberculosis (Johne's disease), displaced abomasum, dystocia, metritis, milk fever, ovarian cysts, retained placenta, and ketosis (subclinical and clinical). Estimates of disease impacts on milk yield, fertility, and culling were collected from the literature, standardized, meta-analyzed using a variety of methods ranging from simple averaging to random-effects models, and adjusted for comorbidities to prevent overestimation. These comorbidity-adjusted disease impacts were then combined with a set of country-level lactational incidence and/or prevalence estimates, herd characteristics, and price estimates within a series of Monte Carlo simulations that estimated and valued the economic losses due to these diseases. It was estimated that total annual global losses are USD 65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately USD 18B, USD 13B, and USD 9B, respectively. Estimated global annual losses due to clinical ketosis, displaced abomasum, dystocia, lameness, metritis, milk fever, ovarian cysts, paratuberculosis, and retained placenta were estimated to be USD 0.2B, 0.6B, 0.6B, 6B, 5B, 0.6B, 4B, 4B, and 3B, respectively. Without adjustment for comorbidities, when statistical associations between diseases were disregarded, mean aggregate global losses would have been overestimated by 45%. Although annual losses were greatest in India (USD 12B), the USA (USD 8B), and China (USD 5B), depending on the measure of losses used (losses as a percent of GDP, losses per capita, losses as a percent of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds

Simple Summary

The aims of dairy cattle breeding are more often associated with direct health evidence in relation to the net financial gain and the weighting factors are usually economic values that are retrieved from a model of a dairy herd production system. In our study we used a stochastic bio-economic model SimHerd, which allows us to derive economic values for production, fertility, calving, the survival of cows and calves and assign the importance of health traits to the economic values. Special emphasis was placed on the economics values of health traits and their importance for Lithuanian dairy cattle.

Abstract

Assessing the economic importance of traits is crucial for delivering appropriate breeding goals in dairy cattle breeding. The aim of the present study was to calculate economic values (EV) and assign the importance of health traits for three dairy cattle breeds: Lithuanian Black-and-White open population (LBW), Lithuanian Red open population (LR) and Lithuanian Red old genotype (LROG). The EV estimation was carried out using a stochastic bio-economic model SimHerd, which allows the simulation of the expected monetary gain of dairy herds. The simulation model was calibrated for LBW, LR and LROG breeds, taking into account breed-specific phenotypic and economic data. For each trait, two scenarios were simulated with a respective trait at different phenotypic levels. To obtain the EVs, the scenarios were compared with each other in terms of their economic outcomes. In order to avoid the double counting of the effects, the output results were corrected using a multiple regression analysis with mediator variables. The EVs were derived for the traits related to production ECM (energy-corrected milk), fertility, calving traits, calf survival, cow survival and direct health. To demonstrate the importance of health traits in herd management, we provided reliable EVs estimates for functional traits related to herd health. The highest EV for direct health traits, caused by an increase in of 1 percentage point, were those found for mastitis (EUR 1.73 to EUR 1.82 per cow-year) and lameness (EUR 1.07 to EUR 1.27 per cow-year). The total costs per case of ketosis, milk fever and metritis ranged from EUR 1.01 to EUR 1.30, EUR 1.14 to EUR 1.26 and EUR 0.95 to EUR 1.0, respectively. The highest economic values of dystocia were estimated for LROG (EUR −1.32), slightly lower for LBW (EUR −1.31) and LR (EUR −1.23). The results of this study show the importance of health traits to the economic features of cattle herd selection of new breeding goal and this would improve the herd health. The economic evaluation of the functional traits analyzed in this study indicated the significant economic importance of the functional traits in Lithuanian dairy cattle breeds.

Derivation of economic values for German dairy breeds by means of a bio-economic model-with special emphasis on functional traits

To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.

Traps and Opportunities of Czech Small-Scale Beef Cattle Farming

Small farmers represent a majority of the European Union (EU) farming sector and are considered the cornerstone of both the current and future sustainable EU agriculture. The dynamic complexity of livestock systems hinders the understanding of its behaviour, as well as recognizing the causes of problems and sources of resistance to applied policies and strategies. Livestock system behaviour needs to be understood in order to find leverage points and identify efficient solutions. The presented study depicts issues of small-scale beef cattle farmers in the market environment from a systemic perspective. The common complexity of managing a company increases with biological processes characterized by very long time periods, especially in the case of beef cattle farming. The scenarios analysed by the computer simulation model presented in the study evaluate the benefits of basic diversification into meat processing and a farm-to-table approach. The direct contact of the farmer with the final consumers represents increased demand and requirements on farmers’ entrepreneurship; nevertheless, such a strategy is a significant growth driver that allows faster maximisation of the farm’s output, accelerates the return of the investments, strengthens the market position of the farmer, and increases the farm’s sustainability.