Search

We collected data on mass mortality in Sandwich terns (Thalasseus sandvicensis) during the 2022 breeding season in the Netherlands. Mortality was associated with at least 2 variants of highly pathogenic avian influenza A(H5N1) virus clade 2.3.4.4b. We report on carcass removal efforts relative to survival in colonies. Mitigation strategies urgently require structured research. [ABSTRACT FROM AUTHOR]

Estimates of the per-contact probability of transmission between farms of Highly Pathogenic Avian Influenza virus of H7N7 subtype during the 2003 epidemic in the Netherlands are important for the design of better control and biosecurity strategies. We used standardized data collected during the epidemic and a model to extract data for untraced contacts based on the daily number of infectious farms within a given distance of a susceptible farm. With these data, we used a maximum likelihood estimation approach to estimate the transmission probabilities by the individual contact types, both traced and untraced. The estimated conditional probabilities, conditional on the contact originating from an infectious farm, of virus transmission were: 0.000057 per infectious farm within 1 km per day, 0.000413 per infectious farm between 1 and 3 km per day, 0.0000895 per infectious farm between 3 and 10 km per day, 0.0011 per crisis organisation contact, 0.0414 per feed delivery contact, 0.308 per egg transport contact, 0.133 per other-professional contact and, 0.246 per rendering contact. We validate these outcomes against literature data on virus genetic sequences for outbreak farms. These estimates can be used to inform further studies on the role that improved biosecurity between contacts and/or contact frequency reduction can play in eliminating between-farm spread of the virus during future epidemics. The findings also highlight the need to; 1) understand the routes underlying the infections without traced contacts and, 2) to review whether the contacttracing protocol is exhaustive in relation to all the farm's day-to-day activities and practices. [ABSTRACT FROM AUTHOR]

A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km. [ABSTRACT FROM AUTHOR]

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 belowthreshold 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. [ABSTRACT FROM AUTHOR]

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms. [ABSTRACT FROM AUTHOR]

An epidemic of high-pathogenicity avian influenza (HPAI) A virus subtype H7N7 occurred in The Netherlands in 2003 that affected 255 flocks and led to the culling of 30 million birds. To evaluate the effectiveness of the control measures, we quantified between-flock transmission characteristics of the virus in 2 affected areas, using the reproduction ratio Rh. The control measures markedly reduced the transmission of HPAI virus: Rh before detection of the outbreak in the first infected flock was 6.5 (95% confidence interval [CI], 3.1-9.9) in one area and 3.1 in another area, and it decreased to 1.2 (95% CI, 0.6-1.9) after detection of the first outbreak in both areas. The observation that Rh remained >1 suggests that the containment of the epidemic was probably due to the reduction in the number of susceptible flocks by complete depopulation of the infected areas rather than to the reduction of the transmission by the other control measures. [ABSTRACT FROM AUTHOR]

Digital Dermatitis (DD) is a claw disease mainly affecting the hind feet of dairy cattle. Digital Dermatitis is an infectious disease, transmitted via the environment, where the infectious "agent" is a combination of bacteria. The standardized classification for DD lesions developed by Döpfer et al. (1997) and extended by Berry et al. (2012) has six distinct classes: healthy (M0), an active granulomatous area of 0-2 cm (M1), an ulcerative lesion of >2 cm (M2), an ulcerative lesion covered by a scab (M3), alteration of the skin (M4), and a combination of M4 and M1 (M4.1). We hypothesize that classes M1, M2, M3, M4, and M4.1 are the potentially infectious classes that can contribute to the basic reproduction ratio (R 0 ), the average number of new infections caused by a typical infected individual. Here, we determine differences in infectivity between the classes, the sojourn time in each of the classes, and the contribution of each class to R 0. The analysis is based on data from twelve farms in the Netherlands that were visited every two weeks, eleven times. We found that 93.89% of the transitions from M0 was observed as a transition to class M4, and feet with another class-at-infection rapidly transitioned to class M4. As a consequence, about 70% of the infectious time was spent in class M4. Transmission rate parameters of class-at-infection M1, M2, M3, and M4 were not significantly different from each other, but differed from class-at-infection M4.1. However, due to the relative large amount of time spend in class M4, regardless of the class-at-infection, R 0 was almost completely determined by this class. The R 0 was 2.36, to which class-at-infection M4 alone contributed 88.5%. Thus, M4 lesions should be prevented to lower R 0 to a value below one, while painful M2 lesions should be prevented for animal welfare reasons., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

We investigated which variables possibly influence the amount of foot-and-mouth disease virus (FMDV) shed in secretions and excretions by FMDV infected animals, as it is likely that the amount of FMDV shed is related to transmission risk. First, in a separate analysis of laboratory data, we showed that the total amount of FMDV in secretions and excretions from infected animals is highly correlated with maximum titres of FMDV. Next, we collected data from 32 published scientific articles in which FMDV infection experiments were described. The maximum titres of FMDV reported in different secretions and excretions (the response variable) and the experimental conditions in which they occurred (the explanatory variables), were recorded in a database and analyzed using multivariate regression models with and without random effects. In both types of models, maximum titres of FMDV were significantly (p<0.05) associated with types of secretions and excretions, animal species, stage of the disease and days post infection. These results can be used to prioritize biosecurity measures in contingency plans., (Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.)

Unlabelled: ABSBACKGROUND: Since the detection of MRSA CC398 in pigs in 2004, it has emerged in livestock worldwide. MRSA CC398 has been found in people in contact with livestock and thus has become a public health issue. Data from a large-scale longitudinal study in two Danish and four Dutch pig herds were used to quantify MRSA CC398 transmission rates within pig herds and to identify factors affecting transmission between pigs., Results: Sows and their offspring were sampled at varying intervals during a production cycle. Overall MRSA prevalence of sows increased from 33% before farrowing to 77% before weaning. Overall MRSA prevalence of piglets was>60% during the entire study period. The recurrent finding of MRSA in the majority of individuals indicates true colonization or might be the result of contamination. Transmission rates were estimated using a Susceptible-Infectious-Susceptible (SIS-)model, which resulted in values of the reproduction ratio (R0) varying from 0.24 to 8.08. Transmission rates were higher in pigs treated with tetracyclins and β-lactams compared to untreated pigs implying a selective advantage of MRSA CC398 when these antimicrobials are used. Furthermore, transmission rates were higher in pre-weaning pigs compared to post-weaning pigs which might be explained by an age-related susceptibility or the presence of the sow as a primary source of MRSA CC398. Finally, transmission rates increased with the relative increase of the infection pressure within the pen compared to the total infection pressure, implying that within-pen transmission is a more important route compared to between-pen transmission and transmission through environmental exposure., Conclusion: Our results indicate that MRSA CC398 is able to spread and persist in pig herds, resulting in an endemic situation. Transmission rates are affected by the use of selective antimicrobials and by the age of pigs.

The prevalence of methicillin resistant Staphylococcus aureus (MRSA) in pigs at abattoirs is higher than in pigs sampled on farms. This study investigated whether MRSA negative pigs can become MRSA positive during transportation from the farm to the abattoir after exposure to other pigs and environmental sources of MRSA. Nasal swabs were collected from four batches of pigs during loading at the farm, on arrival at the abattoir and after stunning. Environmental wipes were taken from lorries after transporting pigs and from lairages after holding pigs. All pigs (n=117) tested MRSA negative before transportation. On arrival at the abattoir, 12/117 (10.3%) pigs in two batches tested MRSA positive. In lorries that tested positive after transportation, the prevalence of MRSA positive pigs was 21.1%, whereas no MRSA was detected in pigs that had been transported in lorries that tested negative after transportation. At stunning, all batches and 70/117 (59.8%) pigs tested MRSA positive. Pigs can become MRSA positive in the short period of time during transportation from the farm to stunning at the abattoir., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

In 2001 the epidemics of foot-and-mouth disease virus (FMDV) in Great Britain, The Netherlands and France have shown how fast FMDV may spread between farms. The massive socio-economic impact of these epidemics and the intervention measures taken demonstrate the need for quantitative assessments of the efficacy of candidate intervention strategies. Here we use a mathematical model to describe the spatial transmission of FMDV in The Netherlands and use the Dutch 2001 outbreak data to estimate model parameters. We assess the effect of ring culling strategies using a novel and fast approach producing risk maps, and discuss its consequences for ring vaccination. These risk maps identify both the geographical areas of low risk, where a given intervention strategy is likely to achieve epidemic control within only two or three farm-to-farm infection generations, and high-risk areas, where control is likely to take (much) longer. Our results indicate that certain densely populated livestock areas in the Netherlands remain high-risk areas even for strategies that extend EU minimum measures with culling or vaccination within a ring radius of several kilometres. Depending on an economic assessment, area-wide vaccination might be judged appropriate once an FMDV outbreak would have been confirmed in or close to such a high-density area. The modeling approach developed here could be readily applied to outbreak data for other diseases and in other countries., (Copyright © 2010 Elsevier B.V. All rights reserved.)

To optimize control of an avian influenza outbreak knowledge of within-flock transmission is needed. This study used field data to estimate the transmission rate parameter (beta) and the influence of risk factors on within-flock transmission of highly pathogenic avian influenza (HPAI) H7N7 virus in the 2003 epidemic in The Netherlands. The estimation is based on back-calculation of daily mortality data to fit a susceptible-infectious-dead format, and these data were analysed with a generalized linear model. This back-calculation method took into account the uncertainty of the length of the latent period, the survival of an infection by some birds and the influence of farm characteristics. After analysing the fit of the different databases created by back-calculation, it could be concluded that an absence of the latency period provided the best fit. The transmission rate parameter (beta) from these field data was estimated at 4.50 per infectious chicken per day (95% CI: 2.68-7.57), which was lower than what was reported from experimental data. In contrast to general belief, none of the studied risk factors (housing system, flock size, species, age of the birds in weeks and date of depopulation) had significant influence on the estimated beta.

We investigated the influence of the spatial pattern of farms on the geographical spread of infectious livestock diseases, such as classical swine fever, foot-and-mouth disease and avian influenza in a combined analytical-numerical approach. Our purpose of this paper is to develop a method to identify the areas in which an infection has the potential to spread in an outbreak. In our model, each infected farm can infect neighbouring farms and the probability of transmission is a function of the inter-farm distance (spatial kernel). Therefore, the density of farms in an area is a good indicator for the probability of a major outbreak. In the epidemiological nomenclature, such density corresponds to a local reproduction ratio and we studied the critical behaviour of both the local density and the local reproduction ratio. We found that a threshold can be defined above which major outbreaks can occur, and the threshold value depends on the spatial kernel. Our expression for the threshold value is derived based on scaling arguments and contains two parameters in the exponents of the equation. We estimated these parameters from numerical results for the spatial spread using one particular mathematical function for the form of the spatial kernel. Subsequently, we show that our expression for the threshold using these estimated parameters agrees very well with numerical results for a number of different other functional forms of the spatial kernel (thus suggesting that we are dealing with universal parameters). As an illustration of the practical relevance of the presented method, we calculated the threshold value for avian influenza in the Netherlands and use it to produce a risk map for this disease.

Despite continuing research efforts, knowledge of the transmission of the highly pathogenic avian influenza (HPAI) virus still has considerable gaps, which complicates epidemic control. The goal of this research was to develop a model to back-calculate the day HPAI virus is introduced into a flock, based on within-flock mortality data. The back-calculation method was based on a stochastic SEIR (susceptible (S) - latently infected (E) - infectious (I) - removed (= dead; R)) epidemic model. The latent and infectious period were assumed to be gamma distributed. Parameter values were based on experimental H7N7 within-flock transmission data. The model was used to estimate the day of virus introduction based on a defined within-flock mortality threshold (detection rule for determining AI). Our results indicate that approximately two weeks can elapse before a noticeable increase in mortality is observed after a single introduction into a flock. For example, it takes twelve (minimum 11 - maximum 15) days before AI is detected if the detection rule is fifty dead chickens on two consecutive days in a 10 000 chicken flock (current Dutch monitoring rule for notification). The results were robust for flock size and detection rule, but sensitive to the length of the latent and infectious periods. Furthermore, assuming multiple introductions on one day will result in a shorter estimated period between infection and detection. The implications of the model outcomes for detecting and tracing outbreaks of H7N7 HPAI virus are discussed.

The herd sensitivity (HSe) and herd specificity (Hsp) of clinical diagnosis of an infection with classical swine fever (CSF) virus during veterinary inspection of breeding sows in a herd was evaluated. Data gathered from visits to herds during the CSF outbreak in 1997-1998 in The Netherlands were used for the analysis. Herds were visited one or more times by the same or by different veterinarians. On the basis of the veterinarians' reports, each visit was coded as 0 (negative clinical diagnosis) or 1 (positive clinical diagnosis). The HSe for clinical diagnosis of CSF was modelled as a function of days elapsed since introduction of the virus. The moment of introduction of the CSF virus in the CSF-positive herds was unknown, so for each herd, a probability distribution for the unknown number of days since introduction was derived from serum samples collected at depopulation. The information from the reports of the veterinarians and from the test results of the serum samples at depopulation was combined in a Bayesian analysis. Data from CSF-negative herds were analysed to estimate HSp of clinical diagnosis of CSF. The HSe of clinical diagnosis was 0.5 at 37 days after virus introduction (95% CI: 31, 45) and reached 0.9 at 47 days after virus introduction (95% CI: 41, 54). The estimated herd specificity was 0.72 (95% CI: 0.64, 0.79). Dependence of HSe and HSp on characteristics of the veterinarians and the herds also was studied. Specialisation of the veterinarian significantly, although not markedly, affected the HSe.

The foot-and-mouth disease outbreak in The Netherlands in 2001 most likely started on a mixed veal-calf/dairy-goat farm. The outbreak among the 74 calves on this farm appeared to be limited to four animals, and no clinical signs of FMD were reported. Also on a second veal-calf farm minor clinical signs and limited virus transmission were observed. Since FMD is known to be a very contagious disease, and can cause severe lesions, these observations were disputed. Therefore, we carried out two experiments to determine whether the Dutch FMD virus isolate from 2001 does spread among individually housed calves with limited contacts, either indirect (experiment 1) or direct (experiment 2). In experiment 1, four pairs of calves were housed in an individual box at 1m distance from each other. In experiment 2, two groups of three calves were housed in individual boxes, directly bordering each other. We infected one animal per pair in experiment 1, and the calf in the middle in experiment 2. We recorded clinical signs, virus shedding in saliva and the development of antibodies. In addition, we determined whether the virus was transmitted from the inoculated calves to the neighbour(s). All inoculated calves showed mild signs of FMD--fever, and some vesicles on hooves and/or in the mouth--but only one calf showed signs that were visible without physical examination. All inoculated calves shed virus in the saliva and developed neutralising antibodies. None of the contact animals seroconverted, indicating that virus transmission did not occur. These experiments showed that no virus transmission among individual housed calves can occur. This finding supports the hypothesis of the route of virus introduction to The Netherlands in 2001 and show that the observations on the two veal-calf farms were not impossible.