Since the 1980s, efforts have been made to develop sensors that measure a parameter from an individual cow. The development started with individual cow recognition and was followed by sensors that measure the electrical conductivity of milk and pedometers that measure activity. The aim of this review is to provide a structured overview of the published sensor systems for dairy health management. The development of sensor systems can be described by the following 4 levels: (I) techniques that measure something about the cow (e.g., activity); (II) interpretations that summarize changes in the sensor data (e.g., increase in activity) to produce information about the cow's status (e.g., estrus); (III) integration of information where sensor information is supplemented with other information (e.g., economic information) to produce advice (e.g., whether to inseminate a cow or not); and (IV) the farmer makes a decision or the sensor system makes the decision autonomously (e.g., the inseminator is called). This review has structured a total of 126 publications describing 139 sensor systems and compared them based on the 4 levels. The publications were published in the Thomson Reuters (formerly ISI) Web of Science database from January 2002 until June 2012 or in the proceedings of 3 conferences on precision (dairy) farming in 2009, 2010, and 2011. Most studies concerned the detection of mastitis (25%), fertility (33%), and locomotion problems (30%), with fewer studies (16%) related to the detection of metabolic problems. Many studies presented sensor systems at levels I and II, but none did so at levels III and IV. Most of the work for mastitis (92%) and fertility (75%) is done at level II. For locomotion (53%) and metabolism (69%), more than half of the work is done at level I. The performance of sensor systems varies based on the choice of gold standards, algorithms, and test sizes (number of farms and cows). Studies on sensor systems for mastitis and estrus have shown that sensor systems are brought to a higher level; however, the need to improve detection performance still exists. Studies on sensor systems for locomotion problems have shown that the search continues for the most appropriate indicators, sensor techniques, and gold standards. Studies on metabolic problems show that it is still unclear which indicator reflects best the metabolic problems that should be detected. No systems with integrated decision support models have been found.

Our 'One Health' approach provides an integrated evaluation of the molecular relatedness of ESBL/AmpC-EC from numerous sources. The analysis showed distinguishable ESBL/AmpC-EC transmission cycles in different hosts and failed to demonstrate a close epidemiological linkage of ESBL/AmpC genes and plasmid replicon types between livestock farms and people in the general population.

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In the Dutch poultry meat production chain, first week mortality (FWM) of the chicks is an important measure to quality and is therefore highly related to the price of the chicks that the broiler farm has to pay to the hatchery. Therefore, next to the total number of broiler eggs produced per hen and hatchability, this figure is often used as a measure of efficiency in the breeder-hatchery-broiler production chain. In this study, factors that are related to chick mortality in the first week at broiler farms were investigated. Field data obtained from 2 commercial Dutch hatcheries, for which 482 broiler farms voluntarily recorded FWM of 16,365 flocks of broiler chicks over the years 2004, 2005, and 2006, were analyzed. These represented 79% of the total number of day-old chicks delivered to separate broiler farms. First week mortality was significantly related to breeder age, egg storage length at the hatchery, season, strain, feed company of the breeder farm, year, and hatchery. Furthermore, FWM differed significantly between chicks originating from eggs of different breeder flocks and which were kept for grow-out at different broiler farms.

Interactions between pathogens and hosts at the population level should be considered when studying the effectiveness of control measures for infectious diseases. The advantage of doing transmission experiments compared to field studies is that they offer a controlled environment in which the effect of a single factor can be investigated, while variation due to other factors is minimized. This paper gives an overview of the biological and mathematical aspects, bottlenecks and solutions of developing and executing transmission experiments with animals. Different methods of analysis and different experimental designs are discussed. Final size methods are often used for analysing transmission data, but have never been published in a refereed journal; therefore, they will be described in detail in this paper. We hope that this information is helpful for scientists who are considering performing transmission experiments.

The attitude of Dutch dairy farmers toward selective dry cow treatment (SDCT) is unknown, although a favorable mindset toward application of SDCT seems crucial for successful implementation. Given the fact that blanket dry cow treatment has been strongly promoted until recently, the implementation of SDCT was expected to be quite a challenge. This study aimed to provide insight into the level of implementation of SDCT in 2013 in the Netherlands, the methods used by farmers for selection of cows for dry cow treatment (DCT), the relation between SDCT and udder health and antimicrobial usage (AMU) in 2013, and the mindset of farmers toward SDCT. In 2014, a questionnaire was conducted in a group of 177 herds included in a large-scale udder health study in 2013 and for which all clinical mastitis cases during this year were recorded. In addition, data on somatic cell count (SCC) parameters and AMU was available for these herds. The questionnaire included questions with regard to DCT with a special emphasis on farmers' attitude and mindset with regard to applying DCT in 2013. The data that were obtained from the questionnaire were combined with the data on clinical mastitis, SCC, and AMU. Descriptive statistics were used to evaluate the data and to study the association between DCT, udder health, and AMU. Univariable and multivariable logistic regression models with a logit link function were applied to evaluate potential associations between DCT and farmers' mindset. Selective DCT was taken up progressively by the farmers in our study, with 75% of them implementing SDCT in 2013. The main criterion used to select cows for DCT was the SCC history during the complete previous lactation. The herds were divided into 3 groups based on the percentage of cows dried off with antibiotics in 2013 as indicated by the farmers during interviews. The first group applied BDCT, and the herds for which SDCT was applied were split in 2 equally sized groups based on the median percentage of cows dried off with antibiotics (67%). The incidence rate of subclinical and clinical mastitis were comparable between the groups. Results of the multivariable model showed that 4 factors related to farmers' mindset were associated with the probability to apply SDCT: "financial consequences of SDCT," "uncertainty whether a cow will recover without antimicrobials," the statement "I do not have a problem with the (potential) negative consequences of SDCT," and the usage of internal teat sealants. Application of SDCT appeared to be associated with farmers' attitude. The mindset of farmers with respect to reduction of AMU and the implementation of SDCT was generally positive.

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Impacts• Overview of the different types of socio-economic impact induced by Rift Valley fever disease is presented with a description of their broad characteristics.• Studies on the socio-economic impact of RVF are scarce and mostly based only on partial cost-analysis, however the figures provided point out clearly significant impact.• Recommendations on the needs for research on the socio-economic impact of RVF are discussed, along with potential tools to apply and outputs of such studies in terms of improvement of RVF disease management. SummaryRift Valley fever (RVF) is a severe mosquito-borne disease affecting humans and domestic ruminants. RVF virus has been reported in most African countries, as well as in the Arabic Peninsula. This paper reviews the different types of socio-economic impact induced by RVF disease and the attempts to evaluate them. Of the 52 papers selected for this review, 13 types of socio-economic impact were identified according to the sector impacted, the level and temporal scale of the impact. RVF has a dramatic impact on producers and livestock industries, affecting public and animal health, food security and the livelihood of the pastoralist communities. RVF also has an impact on international trade and other agro-industries. The risk of introducing RVF into disease-free countries via the importation of an infected animal or mosquito is real, and the consequent restriction of access to export markets may induce dramatic economic consequences for national and local economies. Despite the important threat of RVF, few studies have been conducted to assess the socio-economic impact of the disease. The 17 studies identified for quantitative analysis in this review relied only on partial cost analysis, with limited reference to mid-and long-term impact, public health or risk mitigation measures. However, the estimated impacts were high (ranging from $5 to $470 million USD losses). To reduce the impact of RVF, early detection and rapid response should be implemented. Comprehensive disease impact studies are required to provide decision-makers with science-based information on the best intervention measure to implement ensuring efficient resource allocation. Through the analysis of RVF socio-economic impact, this scoping study proposes insights into the mechanisms underpinning its often-underestimated importance. This study highlights the need for comparative socio-economic studies to help decision-makers with their choices related to RVF disease management.