An economic model to calculate farm-specific losses due to bovine respiratory disease in dairy heifers.

This paper describes a personal-computer-based model estimating the economic losses associated with clinical bovine respiratory disease in replacement heifers raised on individual dairy farms. The model is based on the partial-budgeting technique, and calculates the losses for two types of the disease separately: calf pneumonia and a seasonal outbreak. Model input includes farm-specific data such as the incidence of bovine respiratory disease, prices, and effects of the disease on the heifers' productivity. The input database was linked directly with the economic model. For all input parameters, default values used are available to the user and can be modified easily. Losses considered by the model include treatment expenditures and costs associated with increased mortality, increased premature culling, reduced growth, reduced fertility and reduced milk production in first lactation. Uncertainty is taken into account for parameters related to disease incidence, mortality and culling.Basic calculations for a typical Dutch dairy farm with 60% of the heifers (<3 months) affected, indicated total annual losses due to pneumonia average 31.2 per heifer present on the farm (range 18.4-57.1). The estimated losses for one seasonal outbreak with heifers up to 15-months old affected were 27.0 per heifer present (range 17.2-43.1). For both BRD types, the model's outcome was most sensitive to the number of heifers affected. Most of the parameters that had a major impact on the total losses were related to treatment or to the effects on the heifers' productivity. The model is user-friendly and flexible, and can be used as an interactive tool by farmers and veterinarians in the (economic) decision-making process regarding on-farm prevention and control of bovine respiratory disease.

Spatial and stochastic simulation to compare two emergency-vaccination strategies with a marker vaccine in the 1997/1998 Dutch Classical Swine Fever epidemic.

Two alternative emergency-vaccination strategies with a marker vaccine that could have been applied in the 1997/1998 Dutch Classical Swine Fever (CSF) epidemic were evaluated in a modified spatial, temporal and stochastic simulation model: InterCSF. In strategy 1, vaccination would be applied only to overcome a shortage in destruction capacities. Destruction of all pigs on vaccinated farms distinguishes this strategy from strategy 2, which assumes intra-Community trade of vaccinated pig meat. InterCSF simulates the spread of CSF between farms through local spread and three contact types. Disease spread is affected by control measures implemented through different mechanisms. Economic results were generated by a separate model that calculated the direct costs (including the vaccination costs) and consequential losses for farmers and related industries subjected to control measures. The comparison (using epidemiological and economic results) between the different emergency-vaccination strategies with an earlier simulated preventive-slaughter scenario led to some general conclusions on the Dutch CSF epidemic. Both emergency-vaccination strategies were hardly more efficient than the non-vaccination scenario. The intra-Community trade strategy (vaccination-strategy 2) was the least costly of all three scenarios.

Evaluating control strategies for outbreaks in BHV1-free areas using stochastic and spatial simulation.

Several countries within the EU have successfully eradicated bovine herpesvirus type I (BHV1), while others are still making efforts to eradicate the virus. Reintroduction of the virus into BHV1-free areas can lead to major outbreaks - thereby causing severe economic losses. To give decision-makers more insight into the risk and economic consequences of BHV1 reintroduction and into the effectiveness of various control strategies, we developed the simulation model InterIBR. InterIBR is a dynamic model that takes into account risk and uncertainty and the geographic location of individual farms. Simulation of a BHV1-outbreak in the Netherlands starts with introduction of the virus on a predefined farm type, after which both within-farm and between-farm transmission are simulated. Monitoring and control measures are implemented to simulate detection of the infection and subsequent control. Economic consequences included in this study are related to losses due to infection and costs of control. In the simulated basic control strategy, dairy farms are monitored by monthly bulk-milk tests and miscellaneous farms are monitored by half-yearly serological tests. After detection, movement-control measures apply, animal contacts are traced and neighbour farms are put on surveillance. Given current assumptions on transmission dynamics, we conclude that a strategy with either rapid removal or vaccination of infected cattle does not reduce the number of infected farms compared to this basic strategy - but will cost more to control. Farm type with first introduction of BHV1 has a considerable impact on the expected number of secondarily infected farms and total costs. To limit the number of infected farms and total costs due to outbreaks, we suggest intensifying the monitoring program on farms with a high frequency of cattle trade, and monthly bulk-milk testing on dairy farms.

Spatial and stochastic simulation to evaluate the impact of events and control measures on the 1997-1998 classical swine fever epidemic in The Netherlands. I. Description of simulation model.

The simulation model InterCSF was developed to simulate the Dutch Classical Swine Fever (CSF) epidemic of 1997-98 as closely as possible. InterCSF is a spatial, temporal and stochastic simulation model. The outcomes of the various replications give an estimate of the variation in size and duration of possible CSF-epidemics. InterCSF simulates disease spread from an infected farm to other farms through three contact types (animals, vehicles, persons) and through local spread up to a specified distance. The main disease-control mechanisms that influence the disease spread in InterCSF are diagnosis of the infected farms, depopulation of infected farms, movement-control areas, tracing, and pre-emptive slaughter. InterCSF was developed using InterSpread as the basis. InterSpread was developed for foot-and-mouth disease (FMD). This paper describes the process of modifying InterSpread into InterCSF. This involved changing the assumptions and mechanisms for disease spread from FMD to CSF. In addition, CSF-specific control measures based on the standard European Union (EU) regulations were included, as well as additional control measures that were applied during the Dutch epidemic. To adapt InterCSF as closely as possible to the Dutch 1997/98 epidemic, data from the real epidemic were analysed. Both disease spread and disease-control parameters were thus specifically based on the real epidemic. In general, InterSpread turned out to be a flexible tool that could be adapted to simulate another disease with relative ease. The most difficult were the modifications necessary to mimic the real epidemic as closely as possible. The model was well able to simulate an epidemic with a similar pattern over time for number of detected farms as the real outbreak; but the absolute numbers were (despite many relevant modifications) not exactly the same--but were within an acceptable range. Furthermore, the development of InterCSF provided the researchers with a better insight into the existing knowledge gaps. In part II (see the final paper in this issue), InterCSF was used to compare various control strategies as applied to this epidemic.

Spatial and stochastic simulation to evaluate the impact of events and control measures on the 1997-1998 classical swine fever epidemic in The Netherlands. II. Comparison of control strategies.

Using the spatial, temporal and stochastic simulation model InterCSF, several alternative pre-emptive slaughter strategies that could have been applied in the Dutch Classical Swine Fever (CSF) epidemic of 1997-1998 were evaluated. Furthermore, effects of changes in some disease-spread and disease-control parameters were studied. InterCSF simulates the spread of CSF between farms through local spread and contacts (animals, transport and persons). Disease spread is affected by control measures implemented through different mechanisms (e.g. depopulation of infected farms, pre-emptive slaughter, movement control). The starting point for the evaluation of strategies was a simulated basic scenario, which mimicked the real epidemic. Strategies were compared using epidemiological as well as economic results. Economic results were generated by a separate model (EpiLoss) that calculated the direct losses and consequential losses for farmers and related industries. The comparison of the different alternatives to the basic scenario led to some general conclusions on the Dutch CSF-epidemic. Pre-emptive slaughter seemed to be an effective strategy to reduce the size of an epidemic, if started at an early stage. Economically, pre-emptive slaughter was not as expensive as expected; the resulting smaller size of the epidemic, combined with less welfare slaughter, led to much lower overall losses. Furthermore, although large movement control areas seemed effective in reducing the size of the epidemic, the total losses were relatively high because of subsequent welfare slaughter. If infection probabilities could be reduced, for example by improved biosecurity, the resulting epidemics would be much smaller.

Optimizing the herd calving pattern with linear programming and dynamic probabilistic simulation.

Until recently, little attention has been paid to the influence of seasonal variation in performance and prices on the optimal calving pattern of a herd. A method was developed to determine the herd calving pattern that is farm-specific and optimal with use of linear programming. The required technical and economic parameters are calculated with a dynamic probabilistic simulation model of the dairy herd. The approach was illustrated with a situation in which the objective was to maximize the gross margin of the herd and the annual milk production of the herd was restricted, resulting in an optimal calving pattern: all heifers calved during August. When, in addition, only home-reared replacement heifers were allowed to enter the herd, heifer calvings took place from July to October. The gross margin was reduced by only Dfl. .13/100 kg of milk ($1 US = 1.80 Dfl.) as a result of the additional constraint. The sensitivity of the optimal calving pattern of herd was determined for lower reproductive performance and when seasonal price variation was ignored. The method described herein is a flexible tool for determining the optimal calving pattern of herd, taking into account farm-specific inputs and constraints.