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Om nieuwe convenantafspraken gemaakt tussen overheid en veehouderijsectoren over de verdeling van de kosten die de overheid maakt te ondersteunen is een analyse uitgevoerd inzake de kans op introductie en de verwachte epidemiologische en economische gevolgen van mogelijke uitbraken van bestrijdingsplichtige dierziekten. De uitkomsten van deze analyse kunnen mede als basis gebruikt worden voor een nieuw te sluiten convenant tussen de veehouderijsectoren en de overheid met betrekking tot de financiering van het diergezondheidsfonds (DGF).

De berekende verwachte DGF-bijdrage in de bestrijdingskosten voor mond-en-klauwzeer (MKZ) en klassieke varkenspest (KVP), rekening houdend met een EU-bijdrage, is in de 2020/2024-scenario’s lager dan eerder berekend voor de periode 2015/2019. De gemiddelde DGF-bijdrage in de varkenshouderij voor MKZ en KVP wordt geschat op 3,12 mln. euro per 5 jaar in plaats van 13 mln. euro per 5 jaar. In de rundveehouderij zijn de gemiddelde bestrijdingskosten voor MKZ afgenomen van 9 mln. euro naar 2,89 mln. euro per 5 jaar. Voor de schapen- en geitenhouderij is dit 0,15 mln. euro per 5 jaar (was 0,49 mln. euro). In de pluimveehouderij is de DGF-bijdrage in de bestrijdingskosten voor aviaire influenza (AI) min of meer gelijk gebleven (36 mln. euro per 5 jaar), waarbij de kans op AI-insleep juist is toegenomen maar de omvang van een AI-uitbraak aanzienlijk minder is.

Toxoplasma gondii is the causative agent of the parasitic disease toxoplasmosis, which is an important foodborne zoonosis. Eating undercooked meat of infected animals, including pigs, has been considered the major transmission route of T. gondii to humans. Therefore, it is urgent to develop and implement intervention measures in the pork meat chain to reduce risks of acquiring a T. gondii infection. Proposed measures for control of T. gondii in pigs include serological testing of pigs and audits of pig farms on risk factors for T. gondii infection. So far, these ideas have not been tested in practice. In order to generate knowledge about the epidemiology and seroprevalence of T. gondii, as a basis for developing a surveillance system, we studied the long term seroprevalence over years, farming systems and regions, and seasonal patterns of T. gondii seroprevalence in Dutch slaughter pigs. During a five year study period from 2012 to 2016, serum samples were routinely collected in five Dutch pig slaughterhouses. The sera were tested in an ELISA for the presence of antibodies against Toxoplasma. In total 226,340 serum samples were collected and tested during the study period. The observed seroprevalence varied over years, with the highest overall seroprevalence in 2014 (2.8%) and the lowest in 2016 (1.4%). A higher seroprevalence was observed in pigs from organic farms compared to pigs from conventional farms. The overall risk of infection was on average 2.63 times significantly (p < 0.001) higher for organically raised pigs than for conventionally raised pigs. A seasonal pattern in seroprevalence was observed: the results showed a dominant annual periodicity with a seroprevalence peak in winter around week 1 and a minimum seroprevalence in summer around week 27. To our knowledge, this is the first large scale study on the seroprevalence of T. gondii in slaughter pigs. In comparison to other European serological studies, the observed seroprevalence seems to be relative

When outbreaks of Highly Pathogenic Avian Influenza (HPAI) occur in OIE member countries with until then disease-free status, member countries can use 'compartmentalisation'. A compartment may be defined as a subset of farms under a common management system, complying with certain stringent surveillance, control and biosecurity measures, and based on that may receive a disease-free status. Based on this disease-free status the compartment is exempted from certain transport restrictions coming into force in case of outbreaks occurring in the country. For deciding whether a candidate compartment is granted official compartment status, it is relevant to assess the additional HPAI transmission risks that would arise due to the exemptions granted. These risks consist of both additional local transmission risks as well as the additional risk of a 'jump' of HPAI infection from one poultry area, via the compartment, to another area. Here such risk assessment is carried out using a spatial mathematical model for between-farm transmission in the Netherlands, yielding insight in the roles of compartment composition and contact structure and identify relevant evaluation criteria for granting HPAI compartment status. At the core of this model are transmission probabilities associated with indirect between-farm contacts, e.g. through feed delivery, egg collection and professional visitors. These probabilities were estimated from Dutch epidemic outbreak data in earlier work. The additional risk of a jump of HPAI from one area, via the compartment, to another area is calculated relative to the direct jump risk. The results show that additional transmission risks caused by a compartment to other farms are mainly dependent on the distance of densely populated poultry areas (DPPAs) to the nearest compartment farm. Apart from conditions on these distances, we also recommend specific routing requirements for transport and other movements within the compartment.

Background Air pollution has been shown to increase the susceptibility to community-acquired pneumonia (CAP). Previously, we observed an increased incidence of CAP in adults living within 1 km from poultry farms, potentially related to particulate matter and endotoxin emissions. We aim to confirm the increased risk of CAP near poultry farms by refined spatial analyses, and we hypothesize that the oropharyngeal microbiota composition in CAP patients may be associated with residential proximity to poultry farms. Methods A spatial kernel model was used to analyze the association between proximity to poultry farms and CAP diagnosis, obtained from electronic medical records of 92,548 GP patients. The oropharyngeal microbiota composition was determined in 126 hospitalized CAP patients using 16S-rRNA-based sequencing, and analyzed in relation to residential proximity to poultry farms. Results Kernel analysis confirmed a significantly increased risk of CAP when living near poultry farms, suggesting an excess risk up to 1.15 km, followed by a sharp decline. Overall, the oropharyngeal microbiota composition differed borderline significantly between patients living <1 km and ≥1 km from poultry farms (PERMANOVA p = 0.075). Results suggested a higher abundance of Streptococcus pneumoniae (mean relative abundance 34.9% vs. 22.5%, p = 0.058) in patients living near poultry farms, which was verified by unsupervised clustering analysis, showing overrepresentation of a S. pneumoniae cluster near poultry farms (p = 0.049). Conclusion Living near poultry farms is associated with an 11% increased risk of CAP, possibly resulting from changes in the upper respiratory tract microbiota composition in susceptible individuals. The abundance of S. pneumoniae near farms needs to be replicated in larger, independent studies.

Background - Air pollution has been shown to increase the susceptibility to community-acquired pneumonia (CAP). Previously, we observed an increased incidence of CAP in adults living within 1 km from poultry farms, potentially related to particulate matter and endotoxin emissions. We aim to confirm the increased risk of CAP near poultry farms by refined spatial analyses, and we hypothesize that the oropharyngeal microbiota composition in CAP patients may be associated with residential proximity to poultry farms Methods - A spatial kernel model was used to analyze the association between proximity to poultry farms and CAP diagnosis, obtained from electronic medical records of 92,548 GP patients. The oropharyngeal microbiota composition was determined in 126 hospitalized CAP patients using 16S-rRNA-based sequencing, and analyzed in relation to residential proximity to poultry farms. Results - Kernel analysis confirmed a significantly increased risk of CAP when living near poultry farms, suggesting an excess risk up to 1.15 km, followed by a sharp decline. Overall, the oropharyngeal microbiota composition differed borderline significantly between patients living <1 km and ≥1 km from poultry farms (PERMANOVA p = 0.075). Results suggested a higher abundance of Streptococcus pneumoniae (mean relative abundance 34.9% vs. 22.5%, p = 0.058) in patients living near poultry farms, which was verified by unsupervised clustering analysis, showing overrepresentation of a S. pneumoniae cluster near poultry farms (p = 0.049). Conclusion - Living near poultry farms is associated with an 11% increased risk of CAP, possibly resulting from changes in the upper respiratory tract microbiota composition in susceptible individuals. The abundance of S. pneumoniae near farms needs to be replicated in larger, independent studies.

Toxoplasma gondii is recognized as one of the major foodborne pathogens. The European Food Safety Authority (EFSA) concluded that T. gondii is one of the public health hazards in pigs to be covered within a modern meat inspection and advised to include serological testing of pigs and audits of pig farms to control T. gondii. A project is presented that develops a framework where this idea is practically implemented in a pork supply chain. The aim of the program is to reduce the contribution from the pork chain to the human toxoplasmosis disease burden. In the pilot at least one blood sample per batch at delivery at the slaughterhouse is tested with a Toxoplasma Elisa. With this screening 20 (1%) high risk herds were identified. These high risk farms and their controls, 2 per high risk farm, were followed up. More samples of risk farms and their controls were collected to get a better estimate of the within herd prevalence and to follow the development of serology over time. Additional MC-PCR was performed on hearts of pigs from these herds to confirm presence of infection, tissue cysts. Also farm assessments were done to verify the presence of risk factors at the identified farms. In the first farm where hearts were tested by PCR the presence of toxoplasma tissue cysts was shown. The results give insight in how risk based approaches with food chain information (FCI) for animals sent to slaughter could work, by substantiating how risk herds can be practically identified and which interventions are feasible. The results are discussed in the perspective of human health risks.

As the size of livestock farms in The Netherlands is on the increase for economic reasons, an important question is how disease introduction risks and risks of onward transmission scale with farm size (i.e. with the number of animals on the farm). Here we use the epidemic data of the 1997–1998 epidemic of Classical Swine Fever (CSF) Virus in The Netherlands to address this question for CSF risks. This dataset is one of the most powerful ones statistically as in this epidemic a total of 428 pig farms where infected, with the majority of farm sizes ranging between 27 and 1750 pigs, including piglets. We have extended the earlier models for the transmission risk as a function of between-farm distance, by adding two factors. These factors describe the effect of farm size on the susceptibility of a ‘receiving’ farm and on the infectivity of a ‘sending’ farm (or ‘source’ farm), respectively. Using the best-fitting model, we show that the size of a farm has a significant influence on both farm-level susceptibility and infectivity for CSF. Although larger farms are both more susceptible to CSF and, when infected, more infectious to other farms than smaller farms, the increase is less than linear. The higher the farm size, the smaller the effect of increments of farm size on the susceptibility and infectivity of a farm. Because of changes in the Dutch pig farming characteristics, a straightforward extrapolation of the observed farm size dependencies from 1997/1998 to present times would not be justified. However, based on our results one may expect that also for the current pig farming characteristics in The Netherlands, farm susceptibility and infectivity depend non-linearly on farm size, with some saturation effect for relatively large farm sizes.

Two separate analyses were carried out to understand the epidemiology of Bluetongue virus serotype 8 (BTV-8) in 2007 in North West Europe: First, the temporal change in transmission rates was compared to the evolution of temperature during that season. Second, we evaluated the spatio-temporal dynamics of newly reported outbreaks, to estimate a spatial transmission kernel. For both analyses, the approach as used before in analysing the 2006 BTV-8 epidemic had to be adapted in order to take into account the fact that the 2007 epidemic was not a newly arising epidemic, but one advancing from whereto it had already spread in 2006. We found that within the area already affected by the 2006 outbreak, the pattern of newly infected farms in 2007 cannot be explained by between-farm transmission, but rather by local re-emergence of the virus throughout that region. This indicates that persistence through winter was ubiquitous for BTV-8. Just like in 2006, we also found that the temperature at which the infection starts to spread lies close to 15 °C. Finally, we found that the shape of the transmission kernel is in line with the one from the 2006 epidemic. In conclusion, despite the substantial differences between 2006 and 2007 in temperature patterns (2006 featured a heat wave in July, whereas 2007 was more regular) and spatial epidemic extent, both the minimum temperature required for transmission and the transmission kernel were similar to those estimated for the 2006 outbreak, indicating that they are robust properties, suitable for extrapolation to other years and similar regions.

Rift Valley fever virus (RVFV) is a zoonotic vector-borne infection and causes a potentially severe disease. Many mammals are susceptible to infection including important livestock species. Although currently confined to Africa and the near-East, this disease causes concern in countries in temperate climates where both hosts and potential vectors are present, such as the Netherlands. Currently, an assessment of the probability of an outbreak occurring in this country is missing. To evaluate the transmission potential of RVFV, a mathematical model was developed and used to determine the initial growth and the Floquet ratio, which are indicators of the probability of an outbreak and of persistence in a periodic changing environment caused by seasonality. We show that several areas of the Netherlands have a high transmission potential and risk of persistence of the infection. Counter-intuitively, these are the sparsely populated livestock areas, due to the high vector-host ratios in these areas. Culex pipiens s.l. is found to be the main driver of the spread and persistence, because it is by far the most abundant mosquito. Our investigation underscores the importance to determine the vector competence of this mosquito species for RVFV and its host preference.

In 2006 and 2007 pig farming in the region of Lombardy, in the north of Italy, was struck by an epidemic of Swine Vesicular Disease virus (SVDV). In fact this epidemic could be viewed as consisting of two sub-epidemics, as the reported outbreaks occurred in two separate time periods. These periods differed in terms of the provinces or municipalities that were affected and also in terms of the timing of implementation of movement restrictions. Here we use a simple mathematical model to analyse the epidemic data, quantifying between-farm transmission probability as a function of between-farm distance. The results show that the distance dependence of between-farm transmission differs between the two periods. In the first period transmission over relatively long distances occurred with higher probability than in the second period, reflecting the effect of movement restrictions in the second period. In the second period however, more intensive transmission occurred over relatively short distances. Our model analysis explains this in terms of the relatively high density of pig farms in the area most affected in this period, which exceeds a critical farm density for between-farm transmission. This latter result supports the rationale for the additional control measure taken in 2007 of pre-emptively culling farms in that area.

Dit artikel is een samenvatting van het rapport "Laag pathogene aviaire influenza virus iInfecties op pluimveebedrijven in Nederland" (CVI 2012). Dit rapport is geschreven naar aanleiding van vragen van het toenmalige Ministerie van Economische zaken, Landbouw en Innovatie. De vragen die werden gesteld zijn: - hebben pluimveebedrijven met vrije uitloop een grotere kans op introductie van LPAI virus infecties?; - is de kans op introductie gerelateerd aan wilde vogels?; - is er een periode in het jaar waarin het risico op infectie groter is? - kunnen er factoren geidentificeerd worden die de kans op introductie verminderen?

Many biological systems experience a periodic environment. Floquet theory is a mathematical tool to deal with such time periodic systems. It is not often applied in biology, because linkage between the mathematics and the biology is not available. To create this linkage, we derive the Floquet theory for natural systems. We construct a framework, where the rotation of the Earth is causing the periodicity. Within this framework the angular momentum operator is introduced to describe the Earth’s rotation. The Fourier operators and the Fourier states are defined to link the rotation to the biological system. Using these operators, the biological system can be transformed into a rotating frame in which the environment becomes static. In this rotating frame the Floquet solution can be derived. Two examples demonstrate how to apply this natural framework.

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.

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