Modelling systems for managing bee disease: the epidemiology of European Foul Brood

Lead Research Organisation: University of Warwick
Department Name: Biological Sciences

Abstract

This project will provide a step-change in our understanding of managed pollinator disease. We will use a combined modelling and molecular approach to investigate the dynamics of European Foul Brood (EFB) as an exemplar of endemic brood disease of honey bee colonies using historic data derived from long-term monitoring of apiaries in England and Wales. We will utilise a program of statistical, analytical and spatially explicit modelling to address the problem. Statistical modelling approaches will be used to identify putative covariates involved in the epidemiology of disease (e.g. land use, weather, management practices) (Newcastle); analytical modelling approaches will be used to investigate the role of transmission processes in determining the epidemiology of disease (Warwick & Bath); and spatially explicit models to investigate spatial spread of disease in the context of investigating the efficacy of different practical control measures (Warwick & Newcastle). The modelling will be parameterised using historic datasets which include the timing and reported incidence of EFB distribution in honey bee apiaries across England and Wales (Fera). Molecular approaches based on microsatellite markers and comparative genomics will be employed to characterise host and parasite diversity (Fera & Bath) for use as additional covariates in the statistical, analytical and spatially explicit models exploring the epidemiology of EFB in relation to host resistance. These data will be used for the testing and validation of the theoretical and spatially explicit models. We (Fera & Bath) have, in collaboration with the Sanger centre in Cambridge, already generated a draft genome sequence for M. plutonius. These data will greatly facilitate the identification of suitable markers for the characterisation of large and representative population samples and will also shed light on the genes responsible for virulence, and how pathogenesis proceeds in the bee host. EFB will provide a paradigm which we can test against other pollinator diseases. For example, developed models will be used to investigate the epidemiology of 14 honey bee diseases collected across 5000 apiaries as part of an ongoing Defra funded monitoring programme (Fera). Dissemination of project results is explicit within the project framework and includes, the production of a list of key end-users, stakeholder workshops, bi-annual project newsletters, reporting in industry literature, a disease management summary document and conference attendance. The modelling analytical and spatially explicit models developed within this project will act as tools to guide strategy in the face of a plethora of disease threats for managed and wild pollinators.

Technical Summary

We will use a combined modelling and molecular approach to investigate the dynamics of the honey bee brood disease, European Foulbrood (EFB), as an exemplar of pollinator disease using historic data derived from long-term monitoring of apiaries in England and Wales. We will utilise a statistical, analytical and spatially explicit modelling program to investigate the epidemiology of EFB and to provide practical management solutions for this disease. Statistical modelling approaches will be used to identify putative covariates involved in the epidemiology of disease (e.g. land use, weather, management practices) analytical modelling approaches will be used to investigate the role of transmission processes in determining the epidemiology of disease; and spatially explicit models to investigate spatial spread of disease in the context of investigating the efficacy of different practical control measures. The modelling will be parameterised using historic datasets which include the timing and reported incidence of EFB distribution in honey bee apiaries across England and Wales. Molecular approaches based on microsatellite markers and comparative genomics will be employed to characterise host and parasite diversity for use as additional covariates in the statistical, analytical and spatially explicit models exploring the epidemiology of EFB in relation to host resistance. Molecular data from newly collected samples will be complemented by historical data generated from stored EFB test kits. These data will be used for the testing and validation of the theoretical and spatially explicit models. The models will be further tested on data on incidence of other pathogens present in 5000 apiaries across England and Wales (current Defra study) and a generic framework developed for investigating disease spread from these and exotic pathogens.

Planned Impact

This project will have tactical and strategic impacts at three levels. First, models will help to develop sustainable disease management practices that beekeepers can apply with guaranteed distribution to end-users via an existing framework of training and extension at the NBU. Second, this project will improve the regulatory risk based inspection programme for the control of bee pest and diseases across England and Wales by targeting approaches and procedures for disease control and driving future research. Third, this project will inform policy makers, including the Scottish Government, on the necessary strategies required to minimise the impact of endemic diseases and also ensure preparedness for emerging threats to bee health. Overall this project supports the aspirations of the Defra and Welsh Assembly Government's 10 year 'Healthy Bees' plan and will contribute significantly to our understanding of bee disease. Keeling has considerable experience in communicating science to policy makers, having been involved in the past two foot-and-mouth outbreaks (in 2001 and 2007) and planning against potential avian influenza in the poultry industry; both in connection with DEFRA. More recently he has been acting chair of the modelling panel for the governments Scientific Pandemic Influenza groups, and has therefore had to consider how to relate model and model uncertainty to policy makers and health-care planners.

Publications

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Datta S (2013) Modelling the spread of American foulbrood in honeybees. in Journal of the Royal Society, Interface

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Keeling MJ (2017) Efficient use of sentinel sites: detection of invasive honeybee pests and diseases in the UK. in Journal of the Royal Society, Interface

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Vanbergen A (2013) Threats to an ecosystem service: pressures on pollinators in Frontiers in Ecology and the Environment

 
Description We have developed sophisticated statistical methods that allow us to determine the parameters governing disease transmission from the reporting of disease from bee apiaries. This has been used to generate a mathematical model that can be used to both confirm the parameters (by comparing to the original outbreak) and to explore a range of control methods.
Using an outbreak of American Foul Brood on the island of Jersey, we were able to compare the potential impact of different control measures. We were able to show that given logistical constraints, the control actions taken were close to optimal.
On-going work is extending this model to data from England and Wales, and to a range of bee diseases.
Exploitation Route Our methodology is currently being extended to England and Wales (using data from Bee-Base), and will allow us to provide the National Bee Unit at FERA with detailed predictions of future incidence as well as considering the optimal deployment of resources to control endemic and invading infections.
Sectors Agriculture, Food and Drink

URL http://www.warwick.ac.uk/wider/activities/animal_infections/bees/
 
Description This project is in collaboration with the National Bee Unit at FERA. As such our modelling advice has directly impacted on control policy. In particular, we have shown the current practice of controlling new invasions of bee diseases is highly effective given logistical and financial constraints. During the project we investigated in detail an American Foul Brood outbreak on the island of Jersey, which provided an ideal test-case for our methodology. Work is now extending these methods to the whole of GB, and extending the scope to both European & American Foul Brood, and Varroa. Our findings for Jersey were directly communicated to the Jersey chief vet and local bee keepers in a range of meetings. Follow-on funds provided by DEFRA have allowed us to extend our exploration of Honey-bee diseases and pests. In particular, we have considered: Asian Hornet invasion, examining the spread from a detailed data-set in France and extrapolating to the UK. Small Hive beetle, where we have been involved in providing modelling advise to help with the Italian outbreak. Sentinel apiaries, where we have looked at the optimal placement of apiaries to minimise the time to detection of a new invasion.
First Year Of Impact 2013
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description DEFRA Follow-on funding
Amount £154,475 (GBP)
Funding ID PH0517 
Organisation Department For Environment, Food And Rural Affairs (DEFRA) 
Sector Public
Country United Kingdom
Start 04/2014 
End 03/2015
 
Title Development of Predictive Models 
Description Multiple models have arisen from the project that can predict the dynamics of honey-bee pests and diseases over a large scale. These have been matched to data and are parameterised to capture the dynamics of multiple pests and pathogens 
Type Of Material Computer model/algorithm 
Provided To Others? No  
Impact Models are being used to influence National Bee Unit policy, including: placement of sentinel apiaries, management of Foul brood and the invasion of Asian Hornet in 2016. Models also assisted the European Food Standards Agency in their battle against the invasion of Small Hive Beetle in Southern Italy in 2014. 
 
Description Vist to Jersey 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Professional Practitioners
Results and Impact Discussion meetings with local bee-keepers on Jersey and Jersey Chief Vet to share our findings and learn from their first-hand experience of the Fowl-Brood outbreak.

Greater appreciation for what science and modelling can do to help in outbreak control.
Year(s) Of Engagement Activity 2013