US-UK Collab: Mycobacterial Transmission Dynamics in Agricultural Systems: Integrating Phylogenetics, Epidemiology, Ecology, and Economics

Lead Research Organisation: University of Glasgow
Department Name: College of Medical, Veterinary &Life Sci


Mathematical modeling of disease transmission is an important tool in studying infectious disease control; however, parameter estimation from field data is often difficult to quantify, especially with complex diseases. Whole-genome sequencing has become faster and more affordable in recent years, thanks to Next-Generation Sequencing techniques. As large databases of sequenced pathogen isolates become available, infectious disease epidemiologists will be able to use these databases, which are more fine-grained than previous serotyping methods, to improve our understanding of transmission dynamics. However, a general methodology is not yet available for such detailed data in bacteria with slow transmission timescales. This project proposes to develop a quantitative methodology for incorporating whole genome sequence (WGS) data into bacterial transmission models. For this, isolates will be used from mycobacterial infections in agricultural systems in the US and UK. Mycobacterial infections, including Mycobacterium avium subsp. paratuberculosis (MAP) and M. bovis (bovine tuberculosis or bTB), are usually studied in simple one-host systems. Mycobacterial disease is extremely difficult to control due to long latent periods, poor diagnostic sensitivity, wildlife and environmental reservoirs of infection, and heterogeneous strain infectiousness. The key to controlling these diseases is believed to be an integrated approach to understand the pathways through which pathogen transmission occurs at all levels in an ecosystem: within animals, between individual animals, between livestock and wildlife, and between livestock and the environment. A generalized, multi-scale methodology is proposed for determining transmission dynamics using WGS data and phylodynamics. These dynamics will be incorporated into predictive models of disease transmission and control within an economic framework, to help decision-makers make informed control choices.

Technical Summary

We will develop a new multi-scale model of infection transmission and control which will be used to better understand the principles, dynamics, and impacts of multi-host infections (particularly mycobacterial infections) at multiple levels. These models will be developed in an integrated, phylodynamic parameter estimation framework, using mathematical models that incorporate both our detailed farm and phylogenetic data. In particular, our work will provide a general framework for modeling infection dynamics of slow-moving pathogens within livestock herds and the connection to both wildlife populations and environmental reservoirs that can affect the dynamics of transmission and control. Our work will be based on unique and innovative data collection methods and data analyses. We will test our methods using expansive isolate collections and precise data on two mycobacterial infections: Mycobacterium avium subsp. paratuberculosis (MAP), the cause of Johne's disease (JD) in ruminants, and Mycobacterium bovis (M. bovis), the causal agent of bovine tuberculosis (bTB). Bovine tuberculosis will be studied in cattle and white-tailed (WT) deer (Odocoileus virginianus) in the US and compared to bTB in cattle and Eurasian badgers (Meles meles) in the UK, while MAP will be studied in dairy cattle and their environment in both the US and UK. These infections are active in complex ecosystems and affect human populations through direct contact, economic impact, and potential contamination of the food supply. By comparing across pathogens, we can examine the impact of the difference between wildlife reservoirs (M. bovis) and environmental reservoirs (MAP), with their differing mutation rates4 while determining the general principles involved in integrating WGS and epidemiological models.

Planned Impact

Transformative research in phylodynamics and disease ecology is proposed to improve our understanding of bacterial infection dynamics by developing 1) a generalized methodology for incorporating WGS data into transmission models, 2) a generalized ecosystem approach to modeling infectious diseases with agricultural production and economic components, and 3) research methods for modeling transmission dynamics in complicated multi-scale systems. This project will integrate innovative phylodynamic techniques with novel data collection and analysis across various scales in the US and UK to determine the minimum necessary data requirements for this model type. The results will allow for design of cost-effective data collection programs, which will be valuable in develop countries but essential in many livestock-dependent low-income countries.

phylodynamic framework at the core of this work will have broad use in public health policy and practices through identifying important factors in multi-host, systems; the generality of the framework will allow it to be adapted broadly to bacterial diseases affecting humans and animals. This interdisciplinary work will promote a cross-fertilization of ideas amongst students, researchers and faculty in molecular biology, epidemiology, ecology, and economics. The molecular biologists, epidemiologists, ecologists and economists in the team will collaborate closely to develop the techniques for this work. Other research-related education and outreach activities specific to this work will include workshops at NIMBioS, short-courses on transmission for veterinarians, and an intensive graduate-level course on endemic disease modeling. Furthermore, members of the group actively participate in science educational programs for 7th-9th grade girls in the Ithaca, NY community and in education for school-age children in the UK, as well as professional development classes in many countries.

At the completion of the project, a methodology will have been developed for multi-scale generalized systems modeling of multi-host infectious diseases in an ecosystem that includes livestock, environmental, wildlife, and economic components with a particular application in mycobacterial diseases and their control. A large impact is expected in core phylogenetic and mathematical epidemiology areas, including multi-scale modeling and inference from WGS data. In the process high school, undergraduates, graduate students and post-doctoral fellows will have been trained and enthused in the use of this approach.

Related Projects

Project Reference Relationship Related To Start End Award Value
BB/M01262X/1 01/09/2014 14/09/2017 £379,635
BB/M01262X/2 Transfer BB/M01262X/1 15/09/2017 14/08/2018 £109,862
Title Bioinformatics pipeline for generation of whole genome sequence dta 
Description Development of bioinformatics pipeline that is being used at the National Veterinary Science Laboratory (USDA) in Ames Iowa for generation of data on M. Avium Paratuberuclosis sequences (and use in analysing Johne's Disease outbreak data). 
Type Of Material Improvements to research infrastructure 
Year Produced 2015 
Provided To Others? Yes  
Impact While it is to be used for analysis of disease outbreaks, it is too early to quantify this as yet. 
Description US/UK EEID Project 
Organisation Cornell University
Department Department of Population Medicine and Diagnostic Sciences
Country United States of America 
Sector Academic/University 
PI Contribution Modelling of Bovine Tuberculosis epidemiology, use of bacterial deep sequencing in phylodynamic analyses
Collaborator Contribution Modelling of Johne's disease epidemioloy, economics models
Impact None as yet
Start Year 2014
Description Conference aimed at mixed academic, practitioner and policy-maker audience (Minnesota) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact International conference on One Health research, where I spoke of the potential role of whole genome sequencing as a tool for uncovering complex interactions in pathogens affecting multiple species, and using our ongoing work on bovine Tuberculosis in cattle and badgers as the key exemplar. There was both a short question and answer following my talk, as well as a panel discussion where I, together with a mixed group of speakers discussed the potential for "Science in Action: Big Data Methods and Approaches" - in order to highlight new data approaches that have the potential to shift paradigms in use of science to inform policy and practice. As a result I also had several informal discussions on the potential for whole genome sequencing as a new tool in epidemiology.
Year(s) Of Engagement Activity 2016
Description ISVEE conference talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talk at the ISVEE conference aimed at a mix of academics, practitioners/veterinarians and policy-makers. The talk led to further interactions with vets in Brazil's "Embrapa" (Brazilian Agricultural Research Corporation) which has since led to a funded project including Salvador and Kao as advisors.
Year(s) Of Engagement Activity 2015
Description Presentation to Meeting of the USAHA Tuberculosis Scientific Advisory Subcommittee 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Highlighted uses of modern genetic technology combined with mathematical models to understand tuberculosis epidemiology

Have had several continued email and phone conversations with persons within the USDA and other state organisations regarding this research area.
Year(s) Of Engagement Activity 2013,2014
Description TEDx talk - The Science of Networks 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact I gave a TEDx talk on the science of networks, including referring to the difficulties of identifying links between communities in multi-host pathogen systems (using bovine Tb as an exemplar) and also the effects of community separation on the polarisation of debate (again using bovine Tb in cattle and badgers as an example).
Year(s) Of Engagement Activity 2017