Total bacterial count and somatic cell count in bulk and individual goat milk around kidding: two longitudinal observational studies.

Total bacterial count (TBC) and somatic cell count (SCC) are important quality parameters in goat milk. Exceeding the bulk milk TBC (BMTBC) thresholds leads to price penalties for Dutch dairy goat farmers. Controlling these milk quality parameters can be challenging, especially around kidding. First, we describe the variation and the peaks around kidding of TBC and SCC in census data on Dutch bulk milk over the last 22 years. Second, to explore causes of these elevations, we studied the variation of TBC and SCC in individual goat milk from 3 weeks before to 5 weeks after kidding and their association with systemic response markers interferon-γ (IFN-γ), calprotectin, ß-hydroxybutyrate (BHB), body condition score (BCS) and fecal consistency. We visited 4 Dutch dairy goat farms weekly for 10 to 16 weeks around kidding. Some of the goats had been dried off, other goats were milked continuously throughout pregnancy. A total of 1,886 milk samples from 141 goats were collected for automated flowcytometric quantification of TBC and SCC measurement. IFN-γ, calprotectin and BHB were determined twice in blood of the same goats, most samples were collected after kidding. The BCS and fecal consistency were scored visually before and after kidding. We found a strong correlation between TBC and SCC (Spearman's rho = 0.87) around kidding. Furthermore, in the third week before kidding, the average TBC (5.67 log10 cfu/mL) and SCC (6.70 log10 cells/mL) were significantly higher compared with the fifth week after kidding, where the average TBC decreased to 4.20 log10 cfu/mL and the average SCC decreased to 5.92 log10 cells/mL. In multivariable linear regression models, farm and stage of lactation were significantly associated with TBC and SCC, but none of the systemic response markers correlated with TBC or SCC. In conclusion, TBC and SCC in dairy goats were high in late lactation and decreased shortly after parturition. For SCC, the dilution effect might have caused the decrease, but this was not plausible for TBC. Moreover, the excretion of bacteria and cells in goat milk was not associated with the selected systemic response markers that were chosen as a read out for general immunity status, intestinal health and metabolic diseases. Therefore, we assume that the TBC increase before kidding and the decrease after parturition is caused by other systemic, possibly hormonal, processes. To reduce BMTBC and BMSCC, it would be advisable to keep milk of goats with highest numbers of bacteria and cells in their milk out of the bulk milk during end lactation. Further studies are needed to investigate the effects of withholding this end lactation milk from the bulk tank.

Stochastic model to assess bioeconomic impact of PRRS on pig farms in Costa Rica.

Despite the economic importance of PRRS and its high prevalence in Costa Rica, there are no studies on the bioeconomic impact of the disease in the country or, even, in Central America. Such studies are essential in finding cost-effective preventive measures tailored for different production circumstances. Therefore, the objective of this study was to evaluate economic and production parameters of a PRRSV-infection for a medium-sized farrow-to-finish pig farm system in Costa Rica with a farm-level stochastic Monte Carlo simulation model. The effect of PRRS was assessed by scenario analysis, in which a baseline PRRS-free situation was compared against three alternative scenarios that assumed low, medium and high PRRS effects. The PRRS effects were based on data from local farms, scientific literature and expert opinion. Sensitivity analyses were performed to assess the impact of key input parameters on output variables. Results show that at the animal level, changes between the baseline and the PRRS-high scenario were estimated as: + 25 d in age to slaughter, - 9.9 pigs to slaughter (per breeding sow/yr), + 6% annual replacement rate, - 255 d in sow productive lifetime, - 6.9 mo in age at culling of sows, and + 24 non- productive days. For a medium size local farm (n = 588 sows), a reduction of 5826 fat pigs to slaughter per farm/yr from baseline compared to PRRS-high scenario was observed. PRRS-induced loss per farm per year was estimated at -US $142,542, US $180,109 and -US $524,719 for PRRS-low, medium and high scenarios, respectively. Revenues/costs ratio changed from 1.12 in the baseline to 0.89 in the PRRS-high scenario. The production cost per kg carcass weight increased from US $2.63 for the baseline to US $3.35 in the PRRS-high scenario. PRRS-induced loss was estimated at US $77.1 per slaughtered pig/yr and US $892 per breeding sow/yr for the PRRS-high scenario. Results from the model indicate that pig farms with medium to high prevalence of PRRS will require optimal market conditions in order to have positive economic outcomes. These results can be helpful in the design of better control strategies for PRRS.

Livestock producers' knowledge, attitude, and behavior (KAB) regarding antimicrobial use in Ethiopia.

Introduction: Inappropriate antimicrobial use (AMU) in livestock production is an important aspect of the global burden of antimicrobial resistance (AMR). In Ethiopia, a low-income country with a large and increasing livestock population, AMU in food animals is not properly regulated. Hence, farmers are fully free to use antimicrobials to their (perceived) benefit. Therefore, understanding farmers' mindsets is important to improve antimicrobial stewardship in the livestock sector. Methods: This cross-sectional study was conducted to assess livestock disease management practices and knowledge, attitude, and behavior (KAB) among livestock producers regarding AMU, residues, and resistance, as well as factors potentially explaining differences in KAB. We determined the KAB of livestock owners of three selected districts of central and western Ethiopia (n = 457), using a pretested questionnaire administered through face-to-face interviews. Logistic regression was used to evaluate the association between potential explanatory variables and the KAB scores of the respondents. Results: The results showed that 44% of the farmers used antimicrobials in the past few years, where antibiotics (21%) and trypanocides (11%) were most widely used to manage livestock diseases. Furthermore, most farmers showed poor knowledge about AMU, residues, and AMR (94%) and unfavorable attitudes (<50% correct answers) toward contributing factors for AMR (97%). On the contrary, 80% of the respondents had overall good behavior scores (≥50% correct answers) related to AMU. Multivariate analysis results showed that having good knowledge, keeping ≥2 animal species, and the occurrence of ≥4 livestock diseases on the farm in a year were strong predictors of bad behavior scores (p < 0.05). The findings of the current investigation also revealed that the incidence of livestock diseases on the farm and a higher level of formal education significantly contributed to better knowledge and desirable attitudes but bad AMU behavior. Conclusion: A low level of awareness about and undesirable attitudes toward AMU and AMR could potentially affect farmers' behavior toward judicious AMU, thus requiring awareness creation efforts on livestock disease management practices.

Northern Ireland farm-level management factors for recurrent bovine tuberculosis herd breakdowns.

Bovine tuberculosis (bTB) is a chronic, infectious and zoonotic disease of domestic and wild animals caused mainly by Mycobacterium bovis. This study investigated farm management factors associated with recurrent bTB herd breakdowns (n = 2935) disclosed in the period 23 May 2016 to 21 May 2018 and is a follow-up to our 2020 paper which looked at long duration bTB herd breakdowns. A case control study design was used to construct an explanatory set of farm-level management factors associated with recurrent bTB herd breakdowns. In Northern Ireland, a Department of Agriculture Environment and Rural Affairs (DAERA) Veterinarian investigates bTB herd breakdowns using standardised guidelines to allocate a disease source. In this study, source was strongly linked to carryover of infection, suggesting that the diagnostic tests had failed to clear herd infection during the breakdown period. Other results from this study associated with recurrent bTB herd breakdowns were herd size and type (dairy herds 43% of cases), with both these variables intrinsically linked. Other associated risk factors were time of application of slurry, badger access to silage clamps, badger setts in the locality, cattle grazing silage fields immediately post-harvest, number of parcels of land the farmer associated with bTB, number of land parcels used for grazing and region of the country.

Infection dynamics and persistence of hepatitis E virus on pig farms - a review.

BACKGROUND: Hepatitis E virus (HEV) genotype 3 and 4 is a zoonosis that causes hepatitis in humans. Humans can become infected by consumption of pork or contact with pigs. Pigs are the main reservoir of the virus worldwide and the virus is present on most pig farms. MAIN BODY: Though HEV is present on most farms, the proportion of infected pigs at slaughter and thus the level of exposure to consumers differs between farms and countries. Understanding the cause of that difference is necessary to install effective measures to lower HEV in pigs at slaughter. Here, HEV studies are reviewed that include infection dynamics of HEV in pigs and on farms, risk factors for HEV farm prevalence, and that describe mechanisms and sources that could generate persistence on farms. Most pigs become infected after maternal immunity has waned, at the end of the nursing or beginning of the fattening phase. Risk factors increasing the likelihood of a high farm prevalence or proportion of actively infected slaughter pigs comprise of factors such as farm demographics, internal and external biosecurity and immunomodulating coinfections. On-farm persistence of HEV is plausible, because of a high transmission rate and a constant influx of susceptible pigs. Environmental sources of HEV that enhance persistence are contaminated manure storages, water and fomites. CONCLUSION: As HEV is persistently present on most pig farms, current risk mitigation should focus on lowering transmission within farms, especially between farm compartments. Yet, one should be aware of the paradox of increasing the proportion of actively infected pigs at slaughter by reducing transmission insufficiently. Vaccination of pigs may aid HEV control in the future.

Northern Ireland farm-level management factors for prolonged bovine tuberculosis herd breakdowns.

This study determined farm management factors associated with long-duration bovine tuberculosis (bTB) breakdowns disclosed in the period 23 May 2016 to 21 May 2018; a study area not previously subject to investigation in Northern Ireland. A farm-level epidemiological investigation (n = 2935) was completed when one or more Single Intradermal Comparative Cervical Test (SICCT) reactors or when one or more confirmed (positive histological and/or bacteriological result) lesion at routine slaughter were disclosed. A case-control study design was used to construct an explanatory set of management factors associated with long-duration bTB herd breakdowns; with a case (n = 191) defined as an investigation into a breakdown of 365 days or longer. Purchase of infected animal(s) had the strongest association as the most likely source of infection for long-duration bTB herd breakdowns followed by badgers and then cattle-to-cattle contiguous herd spread. However, 73.5% (95% CI 61.1-85.9%) of the herd type contributing to the purchase of infection source were defined as beef fattening herds. This result demonstrates two subpopulations of prolonged bTB breakdowns, the first being beef fattening herds with main source continuous purchase of infected animals and a second group of primary production herds (dairy, beef cows and mixed) with risk from multiple sources.

Test characteristics of the tuberculin skin test and post-mortem examination for bovine tuberculosis diagnosis in cattle in Northern Ireland estimated by Bayesian latent class analysis with adjustments for covariates.

The single intradermal comparative cervical tuberculin (SICCT) test and post-mortem examination are the main diagnostic tools for bovine tuberculosis (bTB) in cattle in the British Isles. Latent class modelling is often used to estimate the bTB test characteristics due to the absence of a gold standard. However, the reported sensitivity of especially the SICCT test has shown a lot of variation. We applied both the Hui-Walter latent class model under the Bayesian framework and the Bayesian model specified at the animal level, including various risk factors as predictors, to estimate the SICCT test and post-mortem test characteristics. Data were collected from all cattle slaughtered in abattoirs in Northern Ireland in 2015. Both models showed comparable posterior median estimation for the sensitivity of the SICCT test (88.61% and 90.56%, respectively) using standard interpretation and for post-mortem examination (53.65% and 53.79%, respectively). Both models showed almost identical posterior median estimates for the specificity (99.99% vs. 99.80% for SICCT test at standard interpretation and 99.66% vs. 99.86% for post-mortem examination). The animal-level model showed slightly narrower posterior 95% credible intervals. Notably, this study was carried out in slaughtered cattle which may not be representative for the general cattle population.

Prediction model optimization using full model selection with regression trees demonstrated with FTIR data from bovine milk.

Predictive modeling is the development of a model that is best able to predict an outcome based on given input variables. Model algorithms are different processes that are used to define functions that transform the data within models. Common algorithms include logistic regression (LR), linear discriminant analysis (LDA), classification and regression trees (CART), naïve Bayes (NB), and k-nearest neighbor (KNN). Data preprocessing option, such as feature extraction and reduction, and model algorithms are commonly selected empirically in epidemiological studies even though these decisions can significantly affect model performance. Accordingly, full model selection (FMS) methods were developed to provide a systematic approach to select predictive modeling methods; however, current limitations of FMS, such as its dependency on user-selected hyperparameters, have prevented their routine incorporation into analyses for model performance optimization. Here we present the use of regression trees as an innovative method to apply FMS. Regression tree FMS (rtFMS) requires the development of a model for every combination of predictive modeling method options under consideration. The iterated, cross-validation performances of these models are then passed through a regression tree for selection of a final model. We demonstrate the benefits of rtFMS using a milk Fourier transform infrared spectroscopy dataset, wherein we build prediction models for two blood metabolic health parameters in dairy cows, nonesterified fatty acids (NEFA) and ß-hydroxybutyrate acid (BHBA). The goal for building NEFA and BHBA prediction models is to provide a milk-based screening tool for metabolic health in dairy cattle that can be incorporated automatically in milk analysis routines. These models could be used in conjunction with physical exams, cow side tests, and other indications to initiate medical intervention. In contrast to previously reported FMS methods, rtFMS is not a black box, is simple to implement and interpret, it does not have hyperparameters, and it illustrates the relative importance of modeling options. Additionally, rtFMS allows for indirect comparisons among models developed using different datasets. Finally, rtFMS eliminates user bias due to personal preference for certain methods and rtFMS removes the dependency on published comparisons of methods. Thus, rtFMS provides clear benefits over the empirical selection of data preprocessing options and model algorithms.

Veterinary medicinal product usage among food animal producers and its health implications in Central Ethiopia.

BACKGROUND: Antimicrobials and anthelmintics are the most commonly used veterinary drugs to control animal diseases. However, widespread use of these drugs could contribute to the emergence of drug resistance. Information on the practice of antimicrobial usage among food animal raising communities in Central Ethiopia is scarce. We used a standardised questionnaire survey to assess knowledge, awareness, and practices related to drug use and resistance in food animals among the farmers in and around Bishoftu town. RESULTS: Of the total of 220 livestock owners interviewed, around 80% of the respondents were not able to define what antimicrobials are and for what purposes they are used. Only 14.1% (n = 31) of the respondents had awareness about antimicrobial resistance (AMR) and its consequences; and 35.5% (n = 11/31) and 9.7% (n = 3/31) of them agreed that the irrational use of antimicrobials in animals could lead to AMR in animals and humans. Oxytetracycline was the most commonly available antibiotic in veterinary drug shops/pharmacies and the most widely used drug in the area. However, 43.3% of the respondents did not see clinical improvements after using antibiotics. Similarly, the respondents explained that no response was observed in 73.3, 70.8 and 52.5% of the cases after medication with anthelmintics, antiprotozoal and acaricides, respectively. About 56.7% of the respondents considered traditional medicines equally important to modern medicines. It was also noted that there were illegal drug vendors, dispensing medicines under unfavourable conditions which include a direct exposure to sunlight, which practice violates the drug handling and storage recommendations given by WHO. CONCLUSION: The study revealed that there is a general lack of awareness among food animal owners about the correct use of antibiotics and anthelmintics. The widespread misuse and improper drug dispensing and handling practices observed in this study can affect the drug quality and can also contribute to the development of drug resistance in central Ethiopia.

The impact of the number of tuberculin skin test reactors and infection confirmation on the risk of future bovine tuberculosis incidents; a Northern Ireland perspective.

Currently policies enabling cattle herds to regain Official Tuberculosis Free (OTF) status after a bovine tuberculosis (bTB) herd incident vary between individual parts of the British Isles from requiring only one negative single comparative intradermal tuberculin test (SCITT) herd test when bTB infection is not confirmed to needing two consecutively negative SCITT herd tests after disclosure of two or more reactors, irrespective of bTB confirmation. This study used Kaplan-Meier curves and univariable and multivariable Cox Proportional Hazard models to evaluate the effect of the number of SCITT reactors and bTB confirmation on the risk of future bTB herd incident utilising data extracted from the national animal health database in Northern Ireland. Based on multivariable analyses the risk of a future bTB herd incident was positively associated with the number of SCITT reactors identified during the incident period (hazard ratio = 1.861 in incidents >5 SCITT reactors compared to incidents with only one SCITT reactor; P < 0.001), but not with bTB confirmation. These findings suggest that the probability of residual bTB infection in a herd increases with an increasing number of SCITT reactors disclosed during a bTB herd incident. It was concluded that bTB herd incidents with multiple SCITT reactors should be subjected to stricter control measures irrespective of bTB infection confirmation status.

Identifying poor metabolic adaptation during early lactation in dairy cows using cluster analysis.

Currently, cows with poor metabolic adaptation during early lactation, or poor metabolic adaptation syndrome (PMAS), are often identified based on detection of hyperketonemia. Unfortunately, elevated blood ketones do not manifest consistently with indications of PMAS. Expected indicators of PMAS include elevated liver enzymes and bilirubin, decreased rumen fill, reduced rumen contractions, and a decrease in milk production. Cows with PMAS typically are higher producing, older cows that are earlier in lactation and have greater body condition score at the start of lactation. It was our aim to evaluate commonly used measures of metabolic health (input variables) that were available [i.e., blood ß-hydroxybutyrate acid, milk fat:protein ratio, blood nonesterified fatty acids (NEFA)] to characterize PMAS. Bavarian farms (n = 26) with robotic milking systems were enrolled for weekly visits for an average of 6.7 wk. Physical examinations of the cows (5-50 d in milk) were performed by veterinarians during each visit, and blood and milk samples were collected. Resulting data included 790 observations from 312 cows (309 Simmental, 1 Red Holstein, 2 Holstein). Principal component analysis was conducted on the 3 input variables, followed by K-means cluster analysis of the first 2 orthogonal components. The 5 resulting clusters were then ascribed to low, intermediate, or high PMAS classes based on their degree of agreement with expected PMAS indicators and characteristics in comparison with other clusters. Results revealed that PMAS classes were most significantly associated with blood NEFA levels. Next, we evaluated NEFA values that classify observations into appropriate PMAS classes in this data set, which we called separation values. Our resulting NEFA separation values [<0.39 mmol/L (95% confidence limits = 0.360-0.410) to identify low PMAS observations and ≥0.7 mmol/L (95% confidence limits = 0.650-0.775) to identify high PMAS observations] were similar to values determined for Holsteins in conventional milking settings diagnosed with hyperketonemia and clinical symptoms such as anorexia and a reduction in milk yield, as reported in the literature. Future studies evaluating additional clinical and laboratory data, breeds, and milking systems are needed to validate these finding. The aim of future studies would be to build a PMAS prediction model to alert producers of cows needing attention and help evaluate on-farm metabolic health management at the herd level.

Host and Environmental Factors Affecting the Intestinal Microbiota in Chickens.

The initial development of intestinal microbiota in poultry plays an important role in production performance, overall health and resistance against microbial infections. Multiplexed sequencing of 16S ribosomal RNA gene amplicons is often used in studies, such as feed intervention or antimicrobial drug trials, to determine corresponding effects on the composition of intestinal microbiota. However, considerable variation of intestinal microbiota composition has been observed both within and across studies. Such variation may in part be attributed to technical factors, such as sampling procedures, sample storage, DNA extraction, the choice of PCR primers and corresponding region to be sequenced, and the sequencing platforms used. Furthermore, part of this variation in microbiota composition may also be explained by different host characteristics and environmental factors. To facilitate the improvement of design, reproducibility and interpretation of poultry microbiota studies, we have reviewed the literature on confounding factors influencing the observed intestinal microbiota in chickens. First, it has been identified that host-related factors, such as age, sex, and breed, have a large effect on intestinal microbiota. The diversity of chicken intestinal microbiota tends to increase most during the first weeks of life, and corresponding colonization patterns seem to differ between layer- and meat-type chickens. Second, it has been found that environmental factors, such as biosecurity level, housing, litter, feed access and climate also have an effect on the composition of the intestinal microbiota. As microbiota studies have to deal with many of these unknown or hidden host and environmental variables, the choice of study designs can have a great impact on study outcomes and interpretation of the data. Providing details on a broad range of host and environmental factors in articles and sequence data repositories is highly recommended. This creates opportunities to combine data from different studies for meta-analysis, which will facilitate scientific breakthroughs toward nutritional and husbandry associated strategies to improve animal health and performance.

Bovine tuberculosis in Northern Ireland: quantification of the population disease-level effect from cattle leaving herds detected as a source of infection.

Determination of the proportion of bovine tuberculosis (bTB) breakdowns attributed to a herd purchasing infected animals has not been previously quantified using data from the Animal and Public Health Information System (APHIS) database in Northern Ireland. We used a case-control study design to account for the infection process occurring in the disclosing bTB breakdown herds. Cases (N = 6926) were cattle moving to a future confirmed bTB breakdown where they would disclose as a confirmed bTB reactor or a Lesion at Routine Slaughter (LRS). Controls (N = 303 499) were cattle moving to a future confirmed bTB breakdown where they did not become a bTB reactor or LRS. Our study showed that the cattle leaving herds which disclosed bTB within 450 days had an increased odds of becoming a confirmed bTB reactor or LRS compared with the cattle which left herds that remained free for 450 days (odds ratio (OR) = 2·09: 95% CI 1·96-2·22). Of the 12 060 confirmed bTB breakdowns included in our study (2007-2015 inclusive), 31% (95% CI 29·8-31·5) contained a confirmed bTB reactor(s) or LRS(s) at the disclosing test which entered the herd within the previous 450 days. After controlling for the infection process occurring in the disclosing bTB breakdown herd, our study showed that 6·4% (95% CI 5·9-6·8) of bTB breakdowns in Northern Ireland were directly attributable to the movement of infected animals.

Genetic Characterization of Porcine Circovirus Type 2 (PCV2) in Pigs of Bhutan.

Porcine circovirus (PCV) is a small non-enveloped virus with a single-stranded circular DNA with two antigenically and genetically different species, PCV1 and PCV2. Among these two, PCV2 is responsible for multifactorial disease syndromes, the most important disease known as PCV2-systemic disease (PCV2-SD), previously known as post-weaning multisystemic wasting syndrome (PMWS). The epidemiological situation is dynamically changing and new strains including recombinant PCV2 have emerged in Asia. In Bhutan, pigs are important livestock and play a very important role in providing meat and income for rural farmers. Although high rate of pigs seropositive against PCV2 was described in Bhutan, there was no virological evidence for PCV2 infections. This study was conducted to confirm the presence of PCV2 through detection of PCV2 DNA and molecular characterization of PCV2 strains in tissue and blood samples collected from Bhutanese pigs. Porcine circovirus type 2 genome was detected in 16 of 34 tissue samples pigs from the government farm. In 9 pigs, very high level of viral replication indicated that PCV2-SD was detected. Phylogenetic analysis performed with a set of GenBank sequences revealed that the Bhutanese PCV2 strains belonged to the PCV2b genotype and grouped with cluster 1C.

Experimental validation of the AVIVET trap, a tool to quantitatively monitor the dynamics of Dermanyssus gallinae populations in laying hens.

Dermanyssus gallinae (D.gallinae) infestation causes economic losses due to impaired health and production of hens and costs of parasite control across the world. Moreover, infestations are associated with reduced welfare of hens and may cause itching in humans. To effectively implement control methods it is crucially important to have high quality information about the D.gallinae populations in poultry houses in space and time. At present no validated tool is available to quantitatively monitor the dynamics of all four stages of D.gallinae (i.e., eggs, larvae, nymphs, and adults) in poultry houses.This article describes the experimental validation of the AVIVET trap, a device to quantitatively monitor dynamics of D.gallinae infestations. We used the device to study D.gallinae in fully equipped cages with two white specific pathogen free Leghorn laying hens experimentally exposed to three different infestation levels of D.gallinae (low to high).The AVIVET trap was successfully able to detect D.gallinae at high (5,000 D.gallinae), medium (2,500 D.gallinae), and low (50 D.gallinae) level of D.gallinae infestation. The linear equation Y = 10∧10∧(0.47 + 1.21X) with Y = log10 (Total number of D.gallinae nymphs and adults) in the cage and X = log10 (Total number of D.gallinae nymphs and adults) in the AVIVET trap explained 93.8% of the variation.The weight of D.gallinae in the AVIVET trap also appears to be a reliable parameter for quantifying D.gallinae infestation in a poultry house. The weight of D.gallinae in the AVIVET trap correlates 99.6% (P < 0.000) to the counted number of all stages of D.gallinae in the trap (i.e., eggs, larvae, nymphs, and adults) indicating that the trap is highly specific.From this experiment it can be concluded that the AVIVET trap is promising as quantitative tool for monitoring D.gallinae dynamics in a poultry house.

Evaluation of Oral Bait Vaccine Efficacy Against Classical Swine Fever in Village Backyard Pig Farms in Bhutan.

Control and eradication of classical swine fever (CSF) in countries with a high proportion of backyard holdings is a challenge. Conventional attenuated Chinese C-strain vaccines, though safe and effective, are difficult to use in backyard farms due to various practical reasons. The aim of this study was to evaluate the efficacy of the CSF oral bait vaccine in village backyard pig farms and to assess the farmers' knowledge on CSF and motivation on using oral vaccines. The pigs were fed the bait by the farmers themselves; one bait was given on day 0, followed by second bait on the next day. Seventy-three per cent (140 of 193 pigs) of vaccinated pigs had either a slight (2-fold-3-fold; 60 pigs) or significant (at least 4-fold; 80 pigs) increase of the antibody titre against CSFV. A significant increase of the antibody titres was mainly observed in pigs with no pre-vaccination titre (OR = 12, 95% CI = 4-40). The number of pigs with protective antibody titres (≥40) rose from 47 (24%) to 115 (60%) following vaccination. Only 30% of the farmers claimed to be familiar with CSF, although clinical signs they mentioned were rather unspecific and could relate to many other pig diseases. Most of the farmers claimed to be motivated to use oral vaccines if made available. The oral vaccine could be a substitute for the conventional attenuated CSF vaccines in areas where it is logistically difficult for veterinarians to visit. It may therefore be a useful tool to combat endemic CSF disease in regions where the disease continues to have a serious impact on the backyard farmers who depend on pig farming for their sustenance and livelihoods.

The validity of a monitoring system based on routinely collected dairy cattle health data relative to a standardized herd check.

Dairy cattle health is often assessed during farm visits. However, farm visits are time consuming and cattle health is assessed at only one point in time. Moreover, farm visits are poorly comparable and/or repeatable when inspection is carried out by many different professionals. Many countries register cattle health parameters such as bulk milk somatic cell count (BMSCC) and mortality in central databases. A great advantage of such routinely available data is that they are uniformly gathered and registered throughout time. This makes comparison between dairy cattle herds possible and could result in opportunities to develop reliable tools for assessing cattle health based on routinely available data. In 2005, a monitoring system for the assessment of cattle health in Dutch dairy herds based on routinely available data was developed. This system had to serve as an alternative for the compulsory quarterly farm visits, which were implemented in 2002. However, before implementation of the alternative system for dairy cows, the validity of the data-based monitoring system and the compulsory quarterly visits relative to the real health status of the herd should be known. The aim of this study was to assess the validity of the data-based monitoring system and the compulsory quarterly visits relative to a standardized herd check for detecting dairy herds with health problems. The results showed that routinely available data can be used to develop an effective screening instrument for detecting herds with poor cattle health. Routinely available data such as cattle mortality and BMSCC that were used in this study had a significant association with animal-based measurements such as the general health impression of the dairy cows (including e.g. rumen fill and body condition). Our study supports the view that cattle health parameters based on routinely available data can serve as a tool for detecting herds with a poor cattle health status which can reduce the number of expensive farm visits. Veterinarians and other herd health advisors could use this tool to target visits to those farms that are identified as at risk for poor cattle health. The development of similar tools in other countries seems possible because many countries have similar data in central databases.

Risk based surveillance for early detection of low pathogenic avian influenza outbreaks in layer chickens.

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.

Simulation study of the mechanisms underlying outbreaks of clinical disease caused by Actinobacillus pleuropneumoniae in finishing pigs.

Actinobacillus pleuropneumoniae is a major cause of respiratory disease in pigs. Many farms are endemically infected without apparent disease, but occasionally severe outbreaks of pleuropneumonia occur. To prevent and control these outbreaks without antibiotics, the underlying mechanisms of these outbreaks need to be understood. Outbreaks are probably initiated by a trigger (common risk factor) changing the host-pathogen interaction, but it is unclear whether this trigger causes all cases directly (trigger mechanism), or whether the first case starts a transmission chain inducing disease in the infected contacts (transmission mechanism). The aim of this study was to identify conditions under which these mechanisms could cause A. pleuropneumoniae outbreaks, and to assess means for prevention and control. Outbreaks were first characterised by data from a literature review, defining an average outbreak at 12 weeks of age, affecting 50% of animals within 4 days. Simple mathematical models describing the two mechanisms can reproduce average outbreaks, with two observations supporting the trigger mechanism: (1) disease should be transmitted 50 times faster than supported by literature if there is a transmission chain; and (2) the trigger mechanism is consistent with the absence of reported outbreaks in young pigs as they have not yet been colonised by the bacterium. In conclusion, outbreaks of A. pleuropneumoniae on endemic farms are most likely caused by a trigger inducing pneumonia in already infected pigs, but more evidence is needed to identify optimum preventive interventions.

Transmission of Actinobacillus pleuropneumoniae among weaned piglets on endemically infected farms.

Clinical outbreaks due to Actinobacillus pleuropneumoniae occur recurrently, despite the wide-scale use of antimicrobials or vaccination. Therefore, new approaches for the prevention and control of these outbreaks are necessary. For the development of alternative measures, more insight into the transmission of the bacterium on farms is necessary. The aim of this cohort study was to quantify transmission of A. pleuropneumoniae amongst weaned piglets on farms. We investigated three possible transmission routes: (i) indirect transmission by infected piglets within the same compartment, (ii) transmission by infected pigs in adjacent pens and (iii) transmission by direct contact within pens. Additionally, we evaluated the effect of independent litter characteristics on the probability of infection. Two farms participated in our study. Serum and tonsil brush samples were collected from sows pre-farrowing. Serum was analysed for antibodies against Apx toxins and Omp. Subsequently, tonsil brush samples were collected from all piglets from these dams (N=542) in three cohorts, 3 days before weaning and 6 weeks later. Tonsil samples were analysed by qPCR for the presence of the apxIVA gene of A. pleuropneumoniae. Before weaning, 25% of the piglets tested positive; 6 weeks later 47% tested positive. Regression and stochastic transmission models were used to assess the contribution of each of the three transmission routes and to estimate transmission rates. Transmission between piglets in adjacent pens did not differ significantly from that between non-adjacent pens. The transmission rate across pens was estimated to be 0.0058 day(-1) (95% CI: 0.0030-0.010), whereas the transmission rate within pens was ten times higher 0.059 day(-1) (95% CI: 0.048-0.072). Subsequently, the effects of parity and serological response of the dam and litter age at weaning on the probability of infection of pigs were evaluated by including these into the regression model. A higher dam ApxII antibody level was associated with a lower probability of infection of the pig after weaning; age at weaning was associated with a higher probability of infection of the pig after weaning. Finally, transmission rate estimates were used in a scenario study in which the litters within a compartment were mixed across pens at weaning instead of raising litter mates together in a pen. The results showed that the proportion of infected piglets increased to 69% if litters were mixed at weaning, indicating that farm management measures may affect spread of A. pleuropneumoniae.