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In 1997–1998, the Netherlands experienced a large epidemic of classical swine fever (CSF). The magnitude of this epidemic stressed the role information systems could play in supporting the management during an eradication campaign. The enforcement of an eradication strategy can become very complicated, especially with large epidemics, due to time pressure and many different procedures that have to be executed at the same time. The application of comprehensive information systems may result in more control over the process and in a relief of the operational management. After a brief description of the Dutch epidemic the authors provide an overview and the general application of four different types of information systems, classified as decision support systems. The application of these information systems in animal disease control is illustrated by providing concepts for a system architecture for transaction processing, management and executive information support and decision support. The application of a data warehouse as part of this systems architecture is explained. The eradication of CSF from the Netherlands was complicated by several factors. It is important to notice that information systems cannot prevent these factors. However, information systems can support disease control authorities in controlling these factors.

Abstract The recent bluetongue virus serotype 8 (BTV-8) epidemic in Western Europe struck hard. Controlling the infection was difficult and a good and safe vaccine was not available until the spring of 2008. Little was known regarding BTV transmission in Western Europe or the efficacy of control measures. Quantitative details on transmission are essential to assess the potential and efficacy of such measures. To quantify virus transmission between herds, a temporal and a spatio-temporal analysis were applied to data on reported infected herds in 2006. We calculated the basic reproduction number between herds (Rh: expected number of new infections, generated by one initial infected herd in a susceptible environment). It was found to be of the same order of magnitude as that of an infection with Foot and Mouth Disease (FMD) in The Netherlands, e.g. around 4. We concluded that an average day temperature of at least 15°C is required for BTV-8 transmission between herds in Western Europe. A few degrees increase in temperature is found to lead to a major increase in BTV-8 transmission. We also found that the applied disease control (spatial zones based on 20 km radius restricting animal transport to outside regions) led to a spatial transmission pattern of BTV-8, with 85% of transmission restricted to a 20 km range. This 20 km equals the scale of the protection zones. We concluded that free animal movement led to substantial faster spread of the BTV-8 epidemic over space as compared to a situation with animal movement restrictions.

Abstract Background In August 2006 a major epidemic of bluetongue virus serotype 8 (BTV8) started off in North-West Europe. In the course of 2007 it became evident that BTV8 had survived the winter in North-West Europe, re-emerged and spread exponentially. Recently, the European Union decided to start vaccination against BTV8. In order to improve the understanding of the epidemiological situation, it was necessary to execute a cross-sectional serological study at the end of the BT vector season. Cattle were the target species for cross-sectional serological studies in Europe at the end of 2006 and 2007. However, there was no information on the BTV8-seroprevalence in sheep and goats. Results On the basis of our cross-sectional study, the estimated seroprevalence of BTV8-exposed locations in the Netherlands in 2006 was 0% for goats (95% confidence interval: 0 – 5.6%) and 7.0% for sheep (95% confidence interval: 3.5 – 12.9%). The estimated seroprevalence of BTV-8 exposed locations in 2007 was 47% for goats (95% confidence interval: 36 – 58%) and 70% for sheep (95% confidence interval: 63 – 76%). There was a wide range in within-location seroprevalence in locations with goats and sheep (1 – 100%). A gradient in seroprevalence was seen, with the highest level of seroprevalence in the southern Netherlands, the area where the epidemic started in 2006, and a decreasing seroprevalence when going in a northern direction. Conclusion There is a much higher estimated seroprevalence of locations with goats exposed to BTV8 than can be inferred from the rather low number of reported clinical outbreaks in goats. This is probably due to the fact that clinical signs in infected goats are far less obvious than in sheep. The wide range in within-location seroprevalence observed means that the proportion of animals protected in 2008 by a natural infection in 2006 and/or 2007 can differ highly between flocks. This should be taken into account when vaccinating animals.

Abstract Background In the recent past, the introduction of Classical Swine Fever Virus (CSFV) followed by between-herd spread has given rise to a number of large epidemics in The Netherlands and Belgium. Both these countries are pork-exporting countries. Particularly important in these epidemics has been the occurrence of substantial "neighborhood transmission" from herd to herd in the presence of base-line control measures prescribed by EU legislation. Here we propose a calculation procedure to map out "high-risk areas" for local between-herd spread of CSFV as a tool to support decision making on prevention and control of CSFV outbreaks. In this procedure the identification of such areas is based on an estimated inter-herd distance dependent probability of neighborhood transmission or "local transmission". Using this distance-dependent probability, we derive a threshold value for the local density of herds. In areas with local herd density above threshold, local transmission alone can already lead to epidemic spread, whereas in below-threshold areas this is not the case. The first type of area is termed 'high-risk' for spread of CSFV, while the latter type is termed 'low-risk'. Results As we show for the case of The Netherlands, once the distance-dependent probability of local transmission has been estimated from CSFV outbreak data, it is possible to produce a map of the country in which areas of high-risk herds and of low-risk herds are identified. We made these maps even more informative by estimating border zones between the two types of areas. In these border zones the risk of local transmission of infection to a nearby high-risk area exceeds a certain level. Conclusion The risk maps provide an easily understandable visualization of the spatial heterogeneities in transmission risk. They serve as a tool for area-specific designs of control strategies, and possibly also for spatial planning of areas where livestock farming is allowed. Similar risk maps can in principle be constructed for other highly-transmissible livestock infections that spread via neighborhood transmission.