Domestic livestock populations differ from unmanaged animals in fundamental ways that are highly conducive to pathogen evolution. Industrialization has been associated with increases in livestock population size and density and a decrease in rearing periods. Today, livestock accounts for about 20 per cent of the total terrestrial animal biomass. and while populations in the wild fluctuate in response to available resources, pathogens and predators, whereas domestic populations are managed to remain stable. As a result, pathogens are provided with globally abundant but genetically similar, densely packed hosts, promoting rapid disease spread. Concurrently, the management of consistent livestock populations inhibits the fitness costs a pathogen would usually pay for increased host mortality, therefore promoting higher pathogen virulence.

In much of my research (but not all) I explore the relationship between modern agricultural practices and the ecology of infectious diseases affecting a range of domestic and agricultural animal populations. I study this relationship across a range of pathogens and agricultural hosts, and broadly aim to answer the question: how do modern agricultural management practices impact infectious disease burden, the risk of disease outbreaks as well as the evolution of pathogen virulence?


Marek’s disease virus and industrialized poultry farming

Collaborators: Troy Day, Scott Greenhalgh

Poultry farming has undergone significant changes since the 1950s, when industry wide intensification began. Today, broiler chickens (chickens raised for meat) are raised with tens of thousands of genetically similar birds in crowded barns, with a lifespan as short as six weeks. These changes to animal husbandry have been implicated in the continual increase in virulence of Marek’s disease, a viral disease of poultry.

Figure 1: Broiler farm model schematic.

In our work, we investigated how poultry husbandry practices contribute to the evolution of Marek’s disease towards greater virulence.

Rozins, C. and Day, T. (2017). The industrialization of farming may be driving virulence evolution. Evol Appl, 10: 189-198.

Rozins, C. and Day, T. (2016). Disease eradication on large industrial farms, J. Math. Biol. 73(4): 885-902

Rozins, Carly, Troy Day, and Scott Greenhalgh. “Managing Marek’s disease in the egg industry.” Epidemics (2019).

In Canada, a shift from conventional laying hen cages, known as battery cages, to alternative enriched cages or free-range systems is underway in response to consumer demand. We have been able to directly inform policy makers with our mathematical model of Marek’s disease. I am working with the Egg Farmers of Canada to evaluate the economic impact of Marek’s disease on egg production through the use of alternative housing systems.

Controlling bovine tuberculosis when there is a wildlife reservoir.

Collaborators: Matthew Silk, Mike Boots, Darren P. Croft, Richard J. Delahay, Dave Hodgson, Robbie A. McDonaldNicola Weber

Bovine tuberculosis, bTB, while rare in most developed nations, continues to be a major animal and human health issue in the UK. Control of bTB in the UK is made difficult due to a wildlife reservoir of European badgers (Fig 3b). Culling of badger populations has been used to control the spread of bTB to cattle, but has proved unpopular and controversial with the public. Quantifying how the unique social organization of the badger populations alters disease dynamics is crucial in the development of successful strategies for controlling the spread of bTB in badgers and onwards transmission to cattle.

Figure 3: a) Badger social contact network, nodes colored by degree, b) European badger (photo by Keith Silk).


We address this question through the analysis of an exceptionally detailed social network dataset for a high-density population of European badgers that are naturally infected with bTB (Fig 3a).

Rozins*, C., Silk*, M., Croft, D.P., Delahay, R.J., Hodgson, D., McDonald, R.A., Weber, N., Boots, M. (2018), Social structure and individual variation in contacts protects against severe epidemics in European Badgers. Ecol. Evol. 8 (23), 12044-12055

*joint first author

The disease consequences of honeybee apiculture intensification.

Collaborators: Mike Boots, Lewis Bartlette, Lena Wilfert, Keith Delaplane, Berry Brosi and Jaap De Roode

Honeybee health and the apicultural industry is under threat from a variety of pressures including disease burden caused by parasites and pathogens.  A growing body of literature is documenting the damage emerging or re-emerging diseases are causing to apiculture. However, a key outstanding question is how modern agricultural intensification and novel agricultural practices impact the emergence and epidemiology of infectious disease in bees.

Figure 2: a) Single bee hive, b)-d) bee hive configurations for a 9-hive apiary considered in the model. Nodes represent hives and edges represent possible routes for between hive disease transmission.


We are the first to build a multi-hive mathematical model, on the scale of a single apiary (see Figure 2). We use our model to examine how apicultural intensification impacts honeybee pathogen epidemiology.

Bartlett*, L.J., Rozins*, C., Brosi, B.J., Delaplane, K.S., de Roode, J.C., White, A.R., Wilfert, L., Boots, M. (2018). Industrial bees: when agricultural intensification doesn’t impact local disease prevalence. bioRxiv 428656; doi:
*joint first author

Perception Kernel and Vector Movements

Collaborators: Janis Antonovics, Michael Hood

Pathogens must move between hosts to persist, and a critical component of disease control is to interrupt this route of transmission. The anther-smut disease, caused by the fungus Microbotryum, and the flower-host Dianthus pavonius (alpine carnation) is a well-established model for experimentally studying vector disease transmission in the field.DSC_1008.jpg

Currently I am using anther-smut transmission data from field experiments to infer vector movements (since they are responsible to some of the spore movements). Additionally we are working on software to aid in setup of large experimental designs.

…more coming soon.


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