Оформление конструкторской документации на печатные платы в условиях автоматизированного проектирования и подготовки производства

Предложен подход к оформлению чертежей печатных плат, позволяющий значительно упростить документацию, а также упорядочить документооборот

Inferences about the transmission of Schmallenberg virus within and between farms

In the summer of 2011 Schmallenberg virus (SBV), a Culicoides-borne orthobunyavirus, emerged in Germany and The Netherlands and subsequently spread across much of Europe. To draw inferences about the transmission of SBV we have developed two models to describe its spread within and between farms. The within-farm model was fitted to seroprevalence data for cattle and sheep farms in Belgium and The Netherlands, with parameters estimated using approximate Bayesian computation. Despite the short duration of viraemia in cattle and sheep (mean of 3–4 days) the within-farm seroprevalence can reach high levels (mean within-herd seroprevalence >80%), largely because the probability of transmission from host to vector is high (14%) and SBV is able to replicate quickly (0.03 per day-degree) and at relatively low temperatures (threshold for replication: 12.3 °C). Parameter estimates from the within-farm model were then used in a separate between-farm model to simulate the regional spread of SBV. This showed that the rapid spread of SBV at a regional level is primarily a consequence of the high probability of transmission from host to vector and the temperature requirements for virus replication. Our results, obtained for a region of the UK in a typical year with regard to animal movements, indicate that there is no need to invoke additional transmission mechanisms to explain the observed patterns of rapid spread of SBV in Europe. Moreover, the imposition of movement restrictions, even a total movement ban, has little effect on the spread of SBV at this scale

Coverage and Representativeness of Passive Surveillance Components for Cattle and Swine in The Netherlands

Common aims of animal health surveillance systems are the timely detection of emerging diseases and health status monitoring. This study aimed to evaluate the coverage and representativeness of passive surveillance components for cattle and swine in the Netherlands from 2015–2019. The passive surveillance components consisted of a telephone helpdesk for veterinary advice and diagnostic and postmortem facilities. Spatial analysis showed heterogeneity (range in RR = 0.26–5.37) of participation across the Netherlands. Generalized linear mixed models showed that distance to the diagnostic facility and farm density were associated with the number of contacts of farmers with the helpdesk and postmortem examination. The contact rate of veterinary practices was associated with their number of clients, ranging in RR from 0.39 to 1.59. We concluded that the evaluation indicated differences in coverage of the passive surveillance components across regions, farms and veterinary practices. Due to the absence of emerging infections in the study period, we were unable to estimate the consequences of the observed differences for the early detection of disease. Nevertheless, regions and veterinary practices with low participation in passive surveillance might be a risk for early detection, and consequently, further understanding of the motivation to participate in passive surveillance components is needed

The economic impact of endemic respiratory disease in pigs and related interventions - a systematic review

Background: Understanding the financial consequences of endemically prevalent pathogens within the porcine respiratory disease complex (PRDC) and the effects of interventions assists decision-making regarding disease prevention and control. The aim of this systematic review was to identify what economic studies have been carried out on infectious endemic respiratory disease in pigs, what methods are being used, and, when feasible, to identify the economic impacts of PRDC pathogens and the costs and benefits of interventions. Results: By following the PRISMA method, a total of 58 studies were deemed eligible for the purpose of this systematic review. Twenty-six studies used data derived from European countries, 18 from the US, 6 from Asia, 4 from Oceania, and 4 from other countries, i.e., Canada, Mexico, and Brazil. Main findings from selected publications were: (1) The studies mainly considered endemic scenarios on commercial fattening farms; (2) The porcine reproductive and respiratory syndrome virus was by far the most studied pathogen, followed by Mycoplasma hyopneumoniae, but the absence or presence of other endemic respiratory pathogens was often not verified or accounted for; (3) Most studies calculated the economic impact using primary production data, whereas twelve studies modelled the impact using secondary data only; (4) Seven different economic methods were applied across studies; (5) A large variation exists in the cost and revenue components considered in calculations, with feed costs and reduced carcass value included the most often; (6) The reported median economic impact of one or several co-existing respiratory pathogen(s) ranged from €1.70 to €8.90 per nursery pig, €2.30 to €15.35 per fattening pig, and €100 to €323 per sow per year; and (7) Vaccination was the most studied intervention, and the outcomes of all but three intervention-focused studies were neutral or positive. Conclusion: The outcomes and discussion from this systematic review provide insight into the studies, their methods, the advantages and limitations of the existing research, and the reported impacts from the endemic respiratory disease complex for pig production systems worldwide. Future research should improve the consistency and comparability of economic assessments by ensuring the inclusion of high impact cost and revenue components and expressing results similarly

Antibiotic prescription patterns and non-clinical factors influencing antibiotic use by Ecuadorian veterinarians working on cattle and poultry farms: A cross-sectional study

Understanding antibiotic prescription patterns and non-clinical factors influencing antibiotic use is essential for implementing strategies to promote appropriate antibiotic use. There is, however, limited research exploring these issues with Ecuadorian veterinarians. Therefore, a questionnaire was developed and applied cross-sectionally to veterinarians (n = 173) from two professional organizations to explore the antibiotic prescription patterns and non-clinical factors (e.g., attitudes and perceptions) influencing antibiotic use, and to identify strategies to reduce antibiotic use. The response rate was 78.4%. Responses were compared between veterinarians working mainly on cattle and poultry farms using Mann-Whitney U tests. The most important attitudes, beliefs and perceptions towards antimicrobial resistance (AMR) and antibiotic use were identified with the Relative Importance Index (RII). Veterinarians showed high awareness of AMR and its implications for public health, as well as the necessity of reducing antibiotic use. However, some veterinarians appear to underestimate the potential contribution of veterinary antibiotic use on AMR in humans. Veterinarians self-reported high prescription (> 20%) of antibiotics for cattle and poultry that are critically important for human medicine, such as 3rd and 4th generation cephalosporins, polymyxins and quinolones. Further, antibiotic therapy was not tailored to disease type. Cattle and poultry veterinarians perceived similar barriers to increasing antibiotic stewardship including: poor biosecurity measures, animal confinement, low feed quality, farmers’ behaviors (such as stopping antibiotic treatment, storing antibiotics on farms, buying antibiotics in veterinary supply stores), and sales agents’ roles as non-professional prescribers of antibiotics. Overall, veterinarians were broadly supportive (>90%) of most strategies to promote appropriate antibiotic use. They saw more merit in improving biosecurity of farms and implementing educational programs for farmers and veterinarians. This study provides insight into the complexity of antibiotic use on Ecuadorian farms and the need for holistic strategies in a One Health context, to achieve antibiotic stewardship

Standardizing output-based surveillance to control non-regulated cattle diseases:Aspiring for a single general regulatory framework in the European Union

Several European countries have implemented country specific programmes to control cattle diseases with little or no regulation in the European Union (EU). These control programmes vary between member states, impairing a confident comparison of freedom from disease when cattle originate from different countries. In order to facilitate safe trade, there is a need to support the development of transparent methods that enable comparison of outputs of surveillance, control or eradication programmes. The aim of the COST Action (CA 17110), Standardizing OUtput-based surveillance to control Non-regulated Diseases in the EU (SOUND control), is the development of a generic and joint understanding of the requirements and characteristics needed for a flexible output-based framework. This framework should be able to substantiate the confidence of disease freedom and cost-effectiveness of heterogeneous surveillance, control or eradication programmes for cattle diseases in the EU. This project supports other initiatives in the development of an output-based framework which will subsequently facilitate safe trade and support the improvement of disease control measures, which is of great importance as the cattle sector contributes to one third of the total gross production value of EU agriculture

Genetic analysis of infectious bronchitis virus (IBV) in vaccinated poultry populations over a period of 10 years

Infectious bronchitis virus (IBV) is an avian pathogen from the Coronavirus family causing major health issues in poultry flocks worldwide. Because of its negative impact on health, performance, and bird welfare, commercial poultry are routinely vaccinated by administering live attenuated virus. However, field strains are capable of rapid adaptation and may evade vaccine-induced immunity. We set out to describe dynamics within and between lineages and assess potential escape from vaccine-induced immunity. We investigated a large nucleotide sequence database of over 1700 partial sequences of the S1 spike protein gene collected from clinical samples of Dutch chickens submitted to the laboratory of Royal GD between 2011 and 2020. Relative frequencies of the two major lineages GI-13 (793B) and GI-19 (QX) did not change in the investigated period, but we found a succession of distinct GI-19 sublineages. Analysis of dN/dS ratio over all sequences demonstrated episodic diversifying selection acting on multiple sites, some of which overlap predicted N-glycosylation motifs. We assessed several measures that would indicate divergence from vaccine strains, both in the overall database and in the two major lineages. However, the frequency of vaccine-homologous lineages did not decrease, no increase in genetic variation with time was detected, and the sequences did not grow more divergent from vaccine sequences in the examined time window. Concluding, our results show sublineage turnover within the GI-19 lineage and we demonstrate episodic diversifying selection acting on the partial sequence, but we cannot confirm nor rule out escape from vaccine-induced immunity. RESEARCH HIGHLIGHTS Succession of GI-19 IBV variants in broiler populations. IBV lineages overrepresented in either broiler, or layer production chickens. Ongoing episodic selection at the IBV S1 spike protein gene sequence. Several positively selected codons coincident with N-glycosylation motifs

A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

International audienceThe collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs