Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed.
Over the last few years, many European and North American countries have reported a high rate of disorders (mortality, dwindling and disappearance) affecting honeybee colonies (Apis mellifera). Although beekeeping has become an increasingly professional activity in recent years, the beekeeping industry remains poorly documented in Europe. The European Union Reference Laboratory for Honeybee Health sent a detailed questionnaire to each Member State, in addition to Kosovo and Norway, to determine the demographics and state of their beekeeping industries. Based on data supplied by the National Reference Laboratory for honeybee diseases in each European country, a European database was created to describe the beekeeping industry including the number and types of beekeepers, operation size, industry production, and health (notifiable diseases, mortalities). The total number of beekeepers in Europe was estimated at 620 000. European honey production was evaluated at around 220 000 tons in 2010. The price of honey varied from 1.5 to 40 €/kg depending on the country and on the distribution network. The estimated colony winter mortality varied from 7 to 28% depending on the country and the origin of the data (institutional survey or beekeeping associations). This survey documents the high heterogeneity of the apicultural industry within the European Union. The high proportion of non-professional beekeepers and the small mean number of colonies per beekeeper were the only common characteristics at European level. The tremendous variation in European apicultural industries has implication for any comprehensive epidemiological or economic analysis of the industry. This variability needs to be taken into account for such analysis as well as for future policy development. The industry would be served if beekeeping registration was uniformly implemented across member states. Better information on the package bee and queen production would help in understanding the ability of the industry to replace lost honey bee stocks.
BackgroundRegular and relevant evaluations of surveillance systems are essential to improve their performance and cost-effectiveness. With this in mind several organizations have developed evaluation approaches to facilitate the design and implementation of these evaluations.MethodsIn order to identify and to compare the advantages and limitations of these approaches, we implemented a systematic review using the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses).ResultsAfter applying exclusion criteria and identifying other additional documents via citations, 15 documents were retained. These were analysed to assess the field (public or animal health) and the type of surveillance systems targeted; the development process; the objectives; the evaluation process and its outputs; and the attributes covered. Most of the approaches identified were general and provided broad recommendations for evaluation. Several common steps in the evaluation process were identified: (i) defining the surveillance system under evaluation, (ii) designing the evaluation process, (iii) implementing the evaluation, and (iv) drawing conclusions and recommendations.ConclusionsA lack of information regarding the identification and selection of methods and tools to assess the evaluation attributes was highlighted; as well as a lack of consideration of economic attributes and sociological aspects.
Summary Unravelling the ecological structure of emerging plant pathogens persisting in multi‐host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs.We designed a mechanistic‐statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Susceptible–Infected–Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data.We applied our approach to French surveillance data on Xylella fastidiosa, a multi‐host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985.Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs.
After the unexpected emergence of Bluetongue virus serotype 8 (BTV-8) in northern Europe in 2006, another arbovirus, Schmallenberg virus (SBV), emerged in Europe in 2011 causing a new economically important disease in ruminants. The virus, belonging to the Orthobunyavirus genus in the Bunyaviridae family, was first detected in Germany, in The Netherlands and in Belgium in 2011 and soon after in the United Kingdom, France, Italy, Luxembourg, Spain, Denmark and Switzerland. This review describes the current knowledge on the emergence, epidemiology, clinical signs, molecular virology and diagnosis of SBV infection.
BackgroundSince 2005, France has been officially free of brucellosis, an infectious disease that causes abortion in cattle and can be transmitted from cattle to humans. Recent animal and human cases have drawn attention to the need to prevent infection of humans and animals from any primary outbreaks. In order to detect any new outbreaks as soon as possible, a clinical surveillance system requires farmers and veterinarians to report each abortion and to test the aborting cow for brucellosis. However, under-reporting limits the sensitivity of this system. Our objective was to identify the barriers and motivations influencing field actors in their decision to report or not to report bovine abortions. We used a qualitative approach with semi-structured interviews of 12 cattle farmers and their eight veterinarians.ResultsOur analysis showed that four main themes influence the decision-making process of farmers and veterinarians: 1) the perceived risk of brucellosis and other abortive diseases; 2) the definition of a suspected case of brucellosis and other abortive diseases adopted by field actors, which is less sensitive than the mandatory definition; 3) the cost-benefit analysis conducted by actors, taking into account regulatory and health aspects, economic and financial losses, technical and practical factors; 4) the level of cooperation within the socio-technical network. We discussed how early detection may be improved by revising the definition of abortion, extending the time frame for notification and generalising the differential diagnosis of the causes of abortion.ConclusionsIn contrast to quantitative approaches, qualitative studies can identify the factors (including unknown factors) influencing the decision-making process of field actors and reveal why they take those factors into consideration. Our qualitative study sheds light on the factors underlying the poor sensitivity of clinical brucellosis surveillance system for cattle in France, and suggests that early detection may be improved by considering actors’ perceptions. We believe our findings may provide further insight into ways of improving other clinical surveillance systems and thus reduce the risk of disease.
The purpose of this study was to develop a standardized tool for the assessment of surveillance systems on zoonoses and animal diseases. We reviewed three existing methods and combined them to develop a semi-quantitative assessment tool associating their strengths and providing a standardized way to display multilevel results. We developed a set of 78 assessment criteria divided into ten sections, representing the functional parts of a surveillance system. Each criterion was given a score according to the prescription of a scoring guide. Three graphical assessment outputs were generated using a specific combination of the scores. Output 1 is a general overview through a series of pie charts synthesizing the scores of each section. Output 2 is a histogram representing the quality of eight critical control points. Output 3 is a radar chart representing the level reached by ten system attributes. This tool was applied on five surveillance networks.
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