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Understanding the context and drivers of farmers' decision-making is critical to designing successful voluntary disease control interventions. This study uses a questionnaire based on the Reasoned Action Approach framework to assess the determinants of farmers' intention to participate in a hypothetical reactive vaccination scheme against Bluetongue. Results suggest that farmers' attitude and social pressures best explained intention. A mix of policy instruments can be used in a complementary way to motivate voluntary vaccination based on the finding that participation is influenced by both internal and external motivation. Next to informational and incentive-based instruments, social pressures, which stem from different type of perceived norms, can spur farmers' vaccination behaviour and serve as catalysts in voluntary vaccination schemes., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Preparedness against vector-borne threats depends on the existence of a long-term, sustainable surveillance of vector-borne disease and their relevant vectors. This work reviewed the availability of such surveillance systems in five European countries (Denmark, France, The Netherlands, Sweden and United Kingdom, part of the CoVetLab network). A qualitative assessment was then performed focusing on surveillance directed particularly to BTV-8. Information regarding surveillance activities were reviewed for the years 2008 and 2012. The results were then complemented with a critical scoping review of the literature aimed at identifying disease surveillance strategies and methods that are currently suggested as best suited to target vector-borne diseases in order to guide future development of surveillance in the countries in question. Passive surveillance was found to be efficient for early detection of diseases during the early phase of introduction into a free country. However, its value diminished once the disease has been established in a territory. Detection of emerging diseases was found to be very context and area specific, and thus active surveillance designs need to take the available epidemiological, ecological and entomological information into account. This was demonstrated by the effectiveness of the bulk milk surveillance in detecting the first case in Sweden, highlighting the need for output based standards to allow the most effective, context dependent, surveillance strategies to be used. Preparedness was of fundamental importance in determining the timeliness of detection and control in each country and that this in turn was heavily influenced by knowledge of emerging diseases in neighboring countries. Therefore it is crucial to share information on outbreaks between researchers and decision-makers and across borders continuously in order to react timely in case of an outbreak. Furthermore, timely reaction to an outbreak was heavily influenced by availability of control measures (vaccines), which is also strengthened if knowledge is shared quickly between countries. The assessment of the bluetongue surveillance in the affected countries showed that the degree of voluntary engagement varied, and that it is important to engage the public by general awareness and dissemination of results. The degree of engagement will also aid in establishing a passive surveillance system., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In intra-EU trade, the health status of animals is warranted by issuing a health certificate after clinical inspection in the exporting country. This certificate cannot provide guarantee of absence of infection, especially not for diseases with a long incubation period and no overt clinical signs such as bovine tuberculosis (bTB). The Netherlands are officially free from bTB since 1999. However, frequent reintroductions occurred in the past 15 years through importation of infected cattle. Additional testing (AT) of imported cattle could enhance the probability of detecting an imported bTB infection in an early stage. The goal of this study was to evaluate the effectiveness of risk-based AT for bTB in cattle imported into The Netherlands. A generic stochastic import risk model was developed that simulates introduction of infection into an importing country through importation of live animals. Main output parameters are the number of infected animals that is imported (Ninf), the number of infected animals that is detected by testing (Ndet), and the economic losses incurred by importing infected animals (loss). The model was parameterized for bTB. Model calculations were optimized to either maximize Ndet or to minimize loss. Model results indicate that the risk of bTB introduction into The Netherlands is very high. For the current situation in which Dutch health checks on imported cattle are limited to a clinical inspection of a random sample of 5-10% of imported animals, the calculated annual Ninf=99 (median value). Random AT of 8% of all imported cattle results in Ndet=7 (median value), while the median Ndet=75 if the sampling strategy for AT is optimized to maximize Ndet. However, in the latter scenario, loss is more than twice as large as in the current situation, because only calves are tested for which cost of detection is higher than the expected gain of preventing a possible outbreak. When optimizing the sampling strategy for AT to minimize loss, only breeding and production cattle are selected for AT resulting in Ndet=1 (median value). Loss is; however, reduced by 75% if compared to the current situation. We conclude that the effectiveness of AT can greatly be improved by risk-based sampling. The optimal sampling strategy for risk-based AT for bTB is highly dependent on the objective of AT. If economic losses are to be contained, AT should focus on breeding and production cattle originating from high-risk countries., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Current knowledge does not allow the prediction of when low pathogenic avian influenza virus (LPAIV) of the H5 and H7 subtypes infecting poultry will mutate to their highly pathogenic phenotype (HPAIV). This mutation may already take place in the first infected flock; hence early detection of LPAIV outbreaks will reduce the likelihood of pathogenicity mutations and large epidemics. The objective of this study was the development of a model for the design and evaluation of serological-surveillance programmes, with a particular focus on early detection of LPAIV infections in layer chicken flocks. Early detection is defined as the detection of an infected flock before it infects on average more than one other flock (between-flock reproduction ratio Rf<1), hence a LPAI introduction will be detected when only one or a few other flocks are infected. We used a mathematical model that investigates the required sample size and sampling frequency for early detection by taking into account the LPAIV within- and between-flock infection dynamics as well as the diagnostic performance of the serological test used. Since layer flocks are the target of the surveillance, we also explored whether the use of eggs, is a good alternative to sera, as sample commodity. The model was used to refine the current Dutch serological-surveillance programme. LPAIV transmission-risk maps were constructed and used to target a risk-based surveillance strategy. In conclusion, we present a model that can be used to explore different sampling strategies, which combined with a cost-benefit analysis would enhance surveillance programmes for low pathogenic avian influenza., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Surveillance for new emerging animal diseases from a European perspective is complicated by the non-harmonised approach across Member States for data capture, recording livestock populations and case definitions. In the summer of 2011, a new vector-borne Orthobunyavirus emerged in Northern Europe and for the first time, a coordinated approach to horizon scanning, risk communication, data and diagnostic test sharing allowed EU Member States to develop early predictions of the disease, its impact and risk management options. There are many different systems in place across the EU for syndromic and scanning surveillance and the differences in these systems have presented epidemiologists and risk assessors with concerns about their combined use in early identification of an emerging disease. The emergence of a new disease always will raise challenging issues around lack of capability and lack of knowledge; however, Schmallenberg virus (SBV) gave veterinary authorities an additional complex problem: the infection caused few clinical signs in adult animals, with no indication of the possible source and little evidence about its spread or means of transmission. This paper documents the different systems in place in some of the countries (Germany and the Netherlands) which detected disease initially and predicted its spread (to the UK) and how information sharing helped to inform early warning and risk assessment for Member States. Microarray technology was used to identify SBV as a new pathogen and data from the automated cattle milking systems coupled with farmer-derived data on reporting non-specific clinical signs gave the first indications of a widespread issue while the UK used meteorological modelling to map disease incursion. The coordinating role of both EFSA and the European Commission were vital as are the opportunities presented by web-based publishing for disseminating information to industry and the public. The future of detecting emerging disease looks more positive in the light of this combined approach in the EU., (Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.)

In order to put a halt to the Bluetongue virus serotype 8 (BTV-8) epidemic in 2008, the European Commission promoted vaccination at a transnational level as a new measure to combat BTV-8. Most European member states opted for a mandatory vaccination campaign, whereas the Netherlands, amongst others, opted for a voluntary campaign. For the latter to be effective, the farmer's willingness to vaccinate should be high enough to reach satisfactory vaccination coverage to stop the spread of the disease. This study looked at a farmer's expected utility of vaccination, which is expected to have a positive impact on the willingness to vaccinate. Decision analysis was used to structure the vaccination decision problem into decisions, events and payoffs, and to define the relationships among these elements. Two scenarios were formulated to distinguish farmers' mindsets, based on differences in dairy heifer management. For each of the scenarios, a decision tree was run for two years to study vaccination behaviour over time. The analysis was done based on the expected utility criterion. This allows to account for the effect of a farmer's risk preference on the vaccination decision. Probabilities were estimated by experts, payoffs were based on an earlier published study. According to the results of the simulation, the farmer decided initially to vaccinate against BTV-8 as the net expected utility of vaccination was positive. Re-vaccination was uncertain due to less expected costs of a continued outbreak. A risk averse farmer in this respect is more likely to re-vaccinate. When heifers were retained for export on the farm, the net expected utility of vaccination was found to be generally larger and thus was re-vaccination more likely to happen. For future animal health programmes that rely on a voluntary approach, results show that the provision of financial incentives can be adjusted to the farmers' willingness to vaccinate over time. Important in this respect are the decision moment and the characteristics of the disease. Farmers' perceptions of the disease risk and about the efficacy of available control options cannot be neglected., (Copyright © 2014 Elsevier B.V. All rights reserved.)

This study aimed at estimating the Schmallenberg virus (SBV) seroprevalence in dairy heifers, non-dairy adult cattle, sheep and goats in the Netherlands after cessation of SBV transmission at the end of 2011. Archived serum samples from ruminants submitted to the GD Animal Health Service for monitoring purposes between November 2011 and March 2012 were selected and tested for presence of SBV-specific antibodies using an in-house ELISA. Animal seroprevalences were estimated at 63.4% in dairy heifers, 98.5% in adult non-dairy cattle, 89.0% in sheep and 50.8% in goats. Multivariable analyses were carried out to describe the relationship between potential risk factors and the ELISA outcome S/P%. The overall SBV seroprevalence in ruminants and ruminant herds in the Netherlands at the end of 2011 was high, with considerable differences between species and farm types. No gradient spatial pattern in final seroprevalence could be detected and therefore no suggestions about the site of introduction and spread of SBV in the Netherlands in 2011 could be made. In dairy heifers, it was shown that S/P% increased with age. In sheep, S/P% was lower in animals located in the coastal area. Whether herds were located near the German border did not affect the S/P% in sheep nor in dairy heifers. An attempt was made to gain insight in the spatiotemporal introduction of SBV in the Netherlands in 2011, by testing sheep serum samples from 2011. A seroprevalence of about 2% was found in samples from April, June and July 2011, but the ELISA positive samples could not be confirmed in a virus neutralization test. A clear increase in seroprevalence started at August 2011. From mid-August 2011 onwards, seropositive samples were confirmed positive by virus neutralization testing. This indicated the start of the epidemic, but without a clear spatial pattern., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Even though low pathogenic avian influenza viruses (LPAIv) affect the poultry industry of several countries in the world, information about their transmission characteristics in poultry is sparse. Outbreak reports of LPAIv in layer chickens have described drops in egg production that appear to be correlated with the virus transmission dynamics. The objective of this study was to use egg production data from LPAIv infected layer flocks to quantify the within-flock transmission parameters of the virus. Egg production data from two commercial layer chicken flocks which were infected with an H7N3 LPAIv were used for this study. In addition, an isolate of the H7N3 LPAIv causing these outbreaks was used in a transmission experiment. The field and experimental estimates showed that this is a virus with high transmission characteristics. Furthermore, with the field method, the day of introduction of the virus into the flock was estimated. The method here presented uses compartmental models that assume homogeneous mixing. This method is, therefore, best suited to study transmission in commercial flocks with a litter (floor-reared) housing system. It would also perform better, when used to study transmission retrospectively, after the outbreak has finished and there is egg production data from recovered chickens. This method cannot be used when a flock was affected with a LPAIv with low transmission characteristics (R(0)<2), since the drop in egg production would be low and likely to be confounded with the expected decrease in production due to aging of the flock. Because only two flocks were used for this analysis, this study is a preliminary basis for a proof of principle that transmission parameters of LPAIv infections in layer chicken flocks could be quantified using the egg production data from affected flocks., (Copyright © 2012 Elsevier B.V. All rights reserved.)

This study calculates the financial consequences of the bluetongue serotype 8 (BTV8) epidemics of 2006 and 2007 in the Netherlands. We constructed a deterministic economic model that is compatible with the Dutch livestock production systems for cattle, sheep and goats. Two hundred cattle farms and 270 sheep farms were infected with BTV8 in the epidemic of 2006, whereas 30,417 cattle farms, 45,022 sheep farms and 35,278 goat farms were estimated to be infected in the epidemic of 2007. The net costs (costs minus benefits) of the BTV8 epidemic of 2006 (BT2006) was estimated at 32.4 million Euros. The net costs of the BTV8 epidemic of 2007 (BT2007) was valued at 164-175 million Euros, depending on the mortality and morbidity rates for cattle used. The losses account for 2%, 10% and 11% of the gross value of the primary production within Dutch pasture-based livestock farming that equals 1.6 billion Euros. Control measures accounted for 91% of the net costs of the BT2006, while diagnostic costs represented 7%. By contrast, for the BT2007 92% of the net costs were in the form of production losses and veterinary treatment fees, while only 6% were related to control measures. Furthermore, the control costs dropped from 29,630 in BT2006 to 10,990 in BT2007 mainly due to the costly indoor housing that was not obligatory during the BT2007 epidemic. The cattle sector suffered 88% and 85% of the net costs for the BT2006 and BT2007, respectively; the highest of all sectors.

A major epidemic of bluetongue virus serotype 8 (BTV-8) occurred in Western Europe in 2006. During 2007 it became evident that BTV-8 had survived the winter and a re-emerging epidemic quickly developed. The objective of this study was to describe the severity and clinical impact of the BTV-8 epidemic in 2007 in The Netherlands in laboratory-confirmed outbreaks and to compare this with the situation in 2006. The relative frequency of clinical signs in BTV-8 affected sheep flocks and cattle herds in 2007 and 2006 was similar. The most prominent changes were a higher proportion of sheep flocks with lameness and a much higher proportion of cattle herds reporting a decrease in milk yield in 2007. BTV-8 associated morbidity and mortality incidence rates in sheep flocks and cattle herds were significantly (P<0.001) higher in 2007 than in 2006. Both in sheep flocks and cattle herds, BTV-8 associated case fatality was significantly (P<0.001) lower in 2007, which was probably due to better medical treatment of sick animals. There were significantly (P<0.001) more fertility problems associated with BTV-8 infection in outbreak cattle herds in 2007 compared to 2006.

Starting August 2006, a major epidemic of bluetongue (BT) was identified in North-West Europe, affecting The Netherlands, Belgium, Germany, Luxembourg and the North of France. It was caused by BT virus serotype 8 (BTV-8), a serotype previously unknown to the European Union (EU). In this outbreak, the virus caused clinical disease in a few individual animals within cattle herds, whereas overt clinical disease was usually restricted to sheep. Investigations in Belgium suggested that the first clinical signs of BTV-8 appeared mid July 2006 in a cattle herd, while the first suspicion of a BT-outbreak in Belgium was reported on 17 August 2006. In the first 10 BTV-8 outbreaks in the Netherlands, the owners indicated that the first clinical signs started approximately 12-17 days before a suspicion was reported to the veterinary authorities via a veterinary practitioner. In BTV-8 affected sheep flocks, erosions of the oral mucosa, fever, salivation, facial and mandibular oedema, apathy and tiredness, mortality, oedema of the lips, lameness, and dysphagia were among the most frequent clinical signs recorded. The most prominent clinical signs in BTV-8 affected cattle herds were: crusts/lesions of the nasal mucosa, erosions of lips/crusts in or around the nostrils, erosions of the oral mucosa, salivation, fever, conjunctivitis, coronitis, muscle necrosis, and stiffness of the limbs. Crusts/lesions of nasal mucosa, conjunctivitis, hyperaemic/purple coloration and lesions of the teats, and redness/hypersensitivity of the skin were relatively more seen on outbreak farms with cattle compared to sheep. Mortality, oedema of the head and ears, coronitis, redness of the oral mucosa, erosions/ulceration of tongue mucosa, purple coloration of the tongue and tongue protrusion and dyspneu were relatively more seen on outbreak farms with sheep compared to cattle.

In August 2006, bluetongue (BT) was notified in The Netherlands on several animal holdings. This was the onset of a rapidly spreading BT-epidemic in north-western Europe (latitude >51 degrees N) that affected cattle and sheep holdings in The Netherlands, Belgium, Germany, France and Luxembourg. The outbreaks were caused by bluetongue virus (BTV) serotype 8, which had not been identified in the European Union before. Bluetongue virus can be introduced into a free area by movement of infected ruminants, infected midges or by infected semen and embryos. In this study, information on animal movements or transfer of ruminant germ plasms (semen and embryos) into the Area of First Infection (AFI), which occurred before and during the onset of the epidemic, were investigated in order to establish the conditions for the introduction of this virus. All inbound transfers of domestic or wild ruminants, non-susceptible mammal species and ruminant germ plasms into the AFI during the high-risk period (HRP), registered by the Trade Control and Expert System (TRACES) of the EC, were obtained. Imports originating from countries with a known or suspected history of BTV-incidence of any serotype were identified. The list of countries with a reported history of BTV incidence was obtained from the OIE Handistatus II for the period from 1996 until 2004. No ruminants were imported from a Member State (MS) with a known history of BTV-8 or from any other country with a known or suspected history of BTV incidence of any serotype. Of all non-susceptible mammal species only 233 horses were transported directly into the AFI during the HRP. No importations of semen or embryos into the AFI were registered in TRACES during the period of interest. An obvious source for the introduction of BTV-8, such as import of infected ruminants, could not be identified and the exact origin and route of the introduction of BTV-8 thus far remains unknown. However, the absence of legal import of ruminants from outside the EU into the AFI and the absence of BTV-8 in southern Europe suggest that, the introduction of the BTV-8 infection into the north-western part of Europe took place via another route. Specifically, in relation to this, the potential for Culicoides to be imported along with or independently of the import of animals, plants or other 'materials', and the effectiveness of measures to reduce such a possibility, merit further study.

Data collected in the Netherlands during the Bluetongue serotype 8 (BTV-8) epidemic indicated that in outbreak cattle herds, predominantly dairy and nursing cows were clinically affected and not young stock, beef cattle, beef calves, or breeding animals. In outbreak sheep flocks, mainly ewes and--if present--rams, were clinically affected and not the lambs. Median morbidity rate in outbreak herds was 1.85 per 100 sheep-month at risk and 0.32 per 100 cattle-month at risk for sheep and cattle, respectively. The mean proportion of BT-affected animals in outbreak herds that recovered from clinical disease was approximately eight times higher for cattle compared to sheep in the Netherlands. Median mortality rate in outbreak herds was 0.5 per 100 sheep-month at risk of dying and 0 per 100 cattle-month at risk of dying for sheep and cattle, respectively. Median recovery time of both sheep and cattle that recovered from clinical disease in outbreak herds was 14 days. Median case fatality was 50% in sheep outbreak flocks and 0% in outbreak cattle herds. It is concluded that morbidity and mortality in outbreak cattle herds was very limited during the BTV-8 epidemic in the Netherlands in 2006. In outbreak sheep flocks, morbidity was limited, with exceptions for a few flocks. However, almost 50% of the clinically sick sheep died in outbreak sheep herds.

The knowledge of the place where a disease is first introduced and from where it later spreads is a key element for the understanding of an epizootic. For a contagious disease, the main method is back tracing. For a vector-borne disease such as the Bluetongue virus serotype 8 epizootic that occurred in 2006 in North-Western Europe, the efficiency of tracing is limited because many infected animals are not showing clinical signs. In the present study, we propose to use a statistical approach, random walk, to model local spread in order to derive the Area of First Infection (AFI) and spread rate. Local spread is basically described by the random movements of infected insect vectors. Our model localised the AFI centre, origin of the infection, in the Netherlands, South of Maastricht. This location is consistent with the location of the farms where the disease was first notified in the three countries (Netherlands, Belgium, and Germany) and the farm where retrospectively the earliest clinical signs were found. The derived rate of spread of 10-15 km/week is consistent with the rates observed in other Bluetongue epizootics. In another article Mintiens (2008), the AFI definition has then been used to investigate possible ways of introduction (upstream tracing) and to study the effect of animal movements from this area (downstream tracing).

Bluetongue virus (BTV) can be spread by movement or migration of infected ruminants. Infected midges (Culicoides sp.) can be dispersed with livestock or on the wind. Transmissions of infection from host to host by semen and trans-placental infection of the embryo from the dam have been found. As for any infectious animal disease, the spread of BTV can be heavily influenced by human interventions preventing or facilitating the transmission pathways. This paper describes the results of investigations that were conducted on the potential role of the above-mentioned human interventions on the spread of BTV-8 during the 2006 epidemic in north-western Europe. Data on surveillance and control measures implemented in the affected European Union (EU) Member States (MS) were extracted from the legislation and procedures adopted by the national authorities in Belgium, France, Germany, and The Netherlands. The impact of the control measures on the BTV-incidence in time and space was explored. Data on ruminant transports leaving the area of first infection (AFI) to other areas within and beyond the affected MS were obtained from the national identification and registration systems of the three initially affected MS (Belgium, Germany, The Netherlands) and from the Trade Control and Expert System (TRACES) of the European Commission. The association between the cumulative number of cases that occurred in a municipality outside the AFI and the number of movements or the number of animals moved from the AFI to that municipality was assessed using a linear negative binomial regression model. The results of this study indicated that the control measures which were implemented in the affected MS (in accordance with EU directives) were not able to fully stop further spread of BTV and to control the epidemic. This finding is not surprising because BT is a vector-borne disease and it is difficult to limit vector movements. We could not assess the consequences of not taking control measures at all but it is possible, if not most likely, that this would have resulted in even wider spread. The study also showed an indication of the possible involvement of animal movements in the spread of BTV during the epidemic. Therefore, the prevention of animal movements remains an important tool to control BTV outbreaks. The extension of the epidemic to the east cannot be explained by the movement of animals, which mainly occurred in a north-western direction. This indicates that it is important to consider other influential factors such as dispersal of infected vectors depending on wind direction, or local spread.

Clinical signs recorded in a classical swine fever (CSF)-suspect situation and the results of the subsequent post-mortem examination (PME) from swine submitted to post-mortem during the 1997-1998 CSF epidemic in the Netherlands, were presented in an experiment as anonymous cases (without knowledge of the actual infection status of the submission) to five veterinary pathologists for their judgment: CSF-suspect or non-suspect. It was presented to them in two hypothetical situations: country was free of CSF for 5 years and CSF was detected in the country 2 weeks ago. Subsequently, their judgment was compared to the gold standard (infection status of the submission on the basis of an immunofluoresence assay on tissue samples) and the sensitivity (Se) and specificity (Sp) of clinical diagnosis was estimated. Furthermore, intra- and inter-pathologist agreement on pathological diagnosis was measured. Adding information on clinical signs to information on PME resulted in a significant increase in median Se and a significant decrease in median Sp for a clinical judgment by pathologists. Also, median Se was significantly higher-and Sp significantly lower-for a clinical judgment by pathologists in a situation in which CSF was detected 2 weeks ago in the country compared to the situation in which the country had been free of CSF for 5 years. Apparently, the internal threshold of pathologists is severely adjusted depending on the actual disease situation in a country. Intra-rater agreement ranged from fair to almost perfect for a clinical diagnosis on the basis of PME. There was considerable variation between pathologists, especially if clinical diagnosis was based on the combined information on PME and clinical signs observed in the herd. Inter-rater agreement was substantial for the diagnosis based on information on PME. Inter-rater agreement was considerably lower for the diagnosis based on the combined information on PME and clinical signs observed in the herd.

Data of the 1997-1998 epidemic of classical swine fever (CSF) in The Netherlands were analysed in survival analysis to identify risk factors that were associated with the rate of neighbourhood infections. The study population consisted of herds within 1000 m of exclusively one previously infected herd. Dates of virus introduction into herds were drawn randomly from estimated probability distributions per herd of possible weeks of virus introduction. (To confirm the insensitivity of the results for this random data-selection procedure, the procedure was repeated 9 times (resulting in 10 different data sets).) The data set had 906 non-infected and 59 infected neighbour herds, which were distributed over 215 different neighbourhoods. Neighbour herds that never became infected were right-censored at the last date of the infectious period of the infected source herd. Neighbour herds that became empty within the infectious period or within the following 21 days due to preventive depopulation or due to the implemented buying-out programme were right-censored 21 days before the moment of becoming empty. This was done as a correction for the time a herd could be infected without being noticed as such. The median time to identified infection of neighbour herds was 2 weeks, whereas the median time to right censoring of non-infected neighbour herds was 3 weeks. The risk factors, radial distance < or =500 m, cattle present on source herd and increasing herd size of the neighbour herd were associated multivariably with the hazard for neighbour herds to become infected. We did not find an association between time down wind and infection risk for neighbour herds. Radial dispersion of CSFV seemed more important in neighbourhood infections than dispersion along the road on which the infected source herd is situated. The results of this study support the strategy of preventive depopulation in the neighbourhood of an infected herd. Recommendations are presented to adapt the applied control strategy for neighbourhood infections.

An outbreak of foot-and-mouth disease (FMD) in Great Britain was reported on 21 February 2001, followed by an outbreak of FMD in The Netherlands a month later. This Dutch index outbreak occurred on a mixed, veal-calf/dairy-goat farm in Oene, in the central part of The Netherlands. The most-likely route of infection was the import of Irish veal-calves to this Dutch herd via an FMD-contaminated staging point in France. With hindsight, more herds seemed to be infected by the time the index outbreak was confirmed. The regular EU control measures were implemented, in combination with pre-emptive culling of herds within 1km of each outbreak. Nevertheless, more outbreaks of FMD occurred. Most of the virus infections on those farms were "neighborhood infections". Because the situation seemed out of control locally and the destruction capacity became insufficient, it was decided to implement an emergency vaccination strategy for all biungulates in a large area around Oene to stop further spread of the virus. All susceptible animals on approximately 1800 farms in this area were vaccinated. All farms subsequently were depopulated, starting from 2 weeks after vaccination. In total, 26 outbreaks were detected (the last outbreak on 22 April 2001). In total, approximately 260,000 animals were killed.

The central and regional organisation of the campaign to eradicate the CSF epidemic in The Netherlands in 1997/1998 is described. The main instruments used in the campaign were based on stamping-out and movement restrictions specified by the European Union. Additional instruments were used for the first time, namely, pre-emptive culling of contact and neighbouring farms, compartmentalisation of transport, monthly serological screening in established surveillance areas and supervised repopulation of all farms in the former surveillance zone. Two other measures, the killing of very young piglets and a breeding ban were introduced to reduce production in established surveillance zones. Several factors complicated the eradication campaign, for instance, the late detection of the first infection; artificial insemination as a source of infection; the organisation of pig farming in The Netherlands, with its highly concentrated production and dependence on the transport of stock from one unit to another; insufficient rendering capacity; decreasing sensitivity of clinical inspection; and extremely high costs.

In this paper, we describe the transmission of Classical Swine Fever virus (CSF virus) within herds during the 1997-1998 epidemic in The Netherlands. In seven herds where the infection started among individually housed breeding stock, all breeding pigs had been tested for antibodies to CSF virus shortly before depopulation. Based upon these data, the transmission of CSF virus between pigs was described as exponential growth in time with a parameter r, that was estimated at 0.108 (95% confidence interval (95% CI) 0.060-0.156). The accompanying per-generation transmission (expressed as the basic reproduction ratio, R0) was estimated at 2.9. Based upon this characterisation, a calculation method was derived with which serological findings at depopulation can be used to calculate the period in which the virus was with a certain probability introduced into that breeding stock. This model was used to estimate the period when the virus had been introduced into 34 herds where the infection started in the breeding section. Of these herds, only a single contact with a herd previously infected had been traced. However, in contrast with the seven previously mentioned herds, only a sample of the breeding pigs had been tested before depopulation (as was the common procedure during the epidemic). The observed number of days between the single contact with an infected herd and the day of sampling of these 34 herds fitted well in the model. Thus, we concluded that the model and transmission parameter was in agreement with the transmission between breeding pigs in these herds. Because of the limited sample size and because it was usually unknown in which specific pen the infection started, we were unable to estimate transmission parameters for weaned piglets and finishing pigs from the data collected during the epidemic. However, from the results of controlled experiments in which R0 was estimated as 81 between weaned piglets and 14 between heavy finishing pigs (Laevens et al., 1998a. Vet. Quart. 20, 41-45; Laevens et al., 1999. Ph.D. Thesis), we constructed a simple model to describe the transmission of CSF virus in compartments (rooms) housing finishing pigs and weaned piglets. From the number of pens per compartment, the number of pigs per pen, the numbers of pigs tested for antibodies to CSF virus and the distribution of the seropositive pigs in the compartment, this model gives again a period in which the virus most probably entered the herd. Using the findings in 41 herds where the infection started in the section of the finishers or weaned piglets of the age of 8 weeks or older, and of which only a single contact with a herd previously infected was known, there was no reason to reject the model. Thus, we concluded that the transmission between weaned piglets and finishing pigs during the epidemic was not significantly different from the transmission observed in the experiments.

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.

In this study, we describe a method to quantify the transmission of Classical Swine Fever Virus (CSFV) between herds from data collected during the 1997-1998 epidemic in The Netherlands. From the contacts between infected herds and the serological findings shortly before depopulation, we estimated the week of virus introduction and the length of the period over which the herd emitted virus for each CSFV-infected herd. From these data, we estimated the infection-rate parameter beta (the average number of herds infected by one infectious herd during one week) and the herd reproduction ratio, Rh (the average total number of secondary outbreaks caused by one infectious herd, i.e. in its entire infectious period), using a SIR-model for different sets of CSF control measures. When Rh > 1, an epidemic continues to grow. On the other hand, when Rh < 1 an epidemic will fade out. During the phase before the first outbreak was diagnosed and no specific measures had been implemented, beta was estimated at 1.09 and Rh at 6.8. In the subsequent phase infected herds were depopulated, movement restrictions were implemented, infected herds were traced forward and backward and the herds in the protection and surveillance zones were clinically inspected by the veterinary authorities (regional screening). This set of measures significantly reduced beta to 0.38. However, Rh was 1.3 and thus still > 1. Consequently, the number of outbreaks continued to grow. After a number of additional measures were implemented, the value of Rh was reduced to 0.5 and the epidemic came to an end. These measures included pre-emptive slaughter of herds that had been in contact with infected herds or were located near an infected herd, increased hygienic procedures, replacement of transports of pigs for welfare reasons by killing of young piglets and a breeding ban, and regional screening for CSF-infected herds by local veterinary practitioners.