Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SARerr model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SARerr model, which led to a trend SARerr model. Overall, BT spread from north-eastern to south-western France. The average trend SARerr-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SARerr-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SARerr models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases

Brood thermoregulation effectiveness is positively linked to the amount of brood but not to the number of bees in honeybee colonies

To ensure the optimal development of brood, a honeybee colony needs to regulate its temperature within a certain range of values (thermoregulation), regardless of environmental changes in biotic and abiotic factors. While the set of behavioural and physiological responses implemented by honeybees to regulate the brood temperature has been well studied, less is known about the factors that may influence the effectiveness of this thermoregulation. Based on the response threshold model of task allocation, increased effectiveness of colony homeostasis should be driven by increases in group size. Therefore, we determined whether colony size (number of adult bees and amount of brood) positively influenced the effectiveness of brood thermoregulation that we measured via two criteria: (i) the brood temperature accuracy, via mean brood temperature, supposedly close to the optimum value for brood rearing, and (ii) the stability of the temperature around the mean value. Finally, within the applied perspective of honeybee colony monitoring, we assessed whether the effectiveness of thermoregulation could be used as a proxy of colony size. For that purpose, we followed 29 honeybee colonies over two years, measured both brood and adult population size regularly over the beekeeping season, and monitored the brood temperature over the 24 hours preceding the inspections of these colonies. We then studied the effect of the size of the colony (number of adult bees and number of brood cells), as well as meteorological variables, on the effectiveness of thermoregulation (mean and stability of brood temperature). We found a clear link between meteorological conditions and brood thermoregulation (mean temperature and its stability). Interestingly, mean brood temperature was also positively linked to the amount of brood, while its stability did not seem influenced by the size of the colony (number of bees or brood amount). The relationship between brood amount and mean temperature was however too weak for clearly discriminating colony population size based solely on the brood thermoregulatory effectiveness. These results demonstrate an extremely high effectiveness of honeybee colonies to thermoregulate the brood regardless of colony size

Honeybee Colony Vibrational Measurements to Highlight the Brood Cycle

Insect pollination is of great importance to crop production worldwide and honey bees are amongst its chief facilitators. Because of the decline of managed colonies, the use of sensor technology is growing in popularity and it is of interest to develop new methods which can more accurately and less invasively assess honey bee colony status. Our approach is to use accelerometers to measure vibrations in order to provide information on colony activity and development. The accelerometers provide amplitude and frequency information which is recorded every three minutes and analysed for night time only. Vibrational data were validated by comparison to visual inspection data, particularly the brood development. We show a strong correlation between vibrational amplitude data and the brood cycle in the vicinity of the sensor. We have further explored the minimum data that is required, when frequency information is also included, to accurately predict the current point in the brood cycle. Such a technique should enable beekeepers to reduce the frequency with which visual inspections are required, reducing the stress this places on the colony and saving the beekeeper time

Produire du miel de tournesol : quelle est l’influence de la structure de la colonie, de Varroa et des pesticides ?

National audienc

Observatoire des résidus de pesticides « Focus sur la miellée de tournesol »

National audienc

Antiparasitaires et biocides : un facteur de risque pour l’abeille ?

National audienc